diff --git a/iree_tests/README.md b/iree_tests/README.md index 256c3c7ad..db7cc11fb 100644 --- a/iree_tests/README.md +++ b/iree_tests/README.md @@ -48,7 +48,7 @@ Tests are run using the [pytest](https://docs.pytest.org/en/stable/) framework. A [`conftest.py`](conftest.py) file collects test cases from subdirectories, wrapping each directory matching the format described above to one test case per test configuration. Test configurations are defined in JSON config files -like [`configs/config_cpu.json`](./configs/config_cpu.json). +like [`configs/config_cpu_llvm_sync.json`](./configs/config_cpu_llvm_sync.json). ### Common venv setup with deps @@ -89,7 +89,7 @@ $ pytest iree_tests -n auto Run tests using custom config files: ```bash -$ export IREE_TEST_CONFIG_FILES=/iree/config_cpu.json;/iree/config_gpu.json +$ export IREE_TEST_CONFIG_FILES=/iree/config_cpu_llvm_sync.json;/iree/config_gpu_vulkan.json $ pytest iree_tests ``` diff --git a/iree_tests/configs/config_cpu.json b/iree_tests/configs/config_cpu_llvm_sync.json similarity index 77% rename from iree_tests/configs/config_cpu.json rename to iree_tests/configs/config_cpu_llvm_sync.json index 86790fe9a..9b37c8c0f 100644 --- a/iree_tests/configs/config_cpu.json +++ b/iree_tests/configs/config_cpu_llvm_sync.json @@ -1,29 +1,36 @@ { - "config_name": "cpu", + "config_name": "cpu_llvm_sync", "iree_compile_flags" : [ "--iree-hal-target-backends=llvm-cpu" ], "iree_run_module_flags": [ - "--device=local-task" + "--device=local-sync" ], "skip_compile_tests": [], "skip_run_tests": [], "expected_compile_failures": [ - "test_acos", "test_acos_example", - "test_acosh", + "test_acos", "test_acosh_example", - "test_adagrad", + "test_acosh", "test_adagrad_multiple", - "test_adam", + "test_adagrad", "test_adam_multiple", + "test_adam", "test_add_uint8", - "test_affine_grid_2d", + "test_affine_grid_2d_align_corners_expanded", "test_affine_grid_2d_align_corners", - "test_affine_grid_3d", + "test_affine_grid_2d_expanded", + "test_affine_grid_2d", + "test_affine_grid_3d_align_corners_expanded", "test_affine_grid_3d_align_corners", + "test_affine_grid_3d_expanded", + "test_affine_grid_3d", "test_ai_onnx_ml_array_feature_extractor", "test_ai_onnx_ml_binarizer", + "test_ai_onnx_ml_label_encoder_string_int_no_default", + "test_ai_onnx_ml_label_encoder_string_int", + "test_ai_onnx_ml_label_encoder_tensor_value_only_mapping", "test_argmax_default_axis_example_select_last_index", "test_argmax_default_axis_random_select_last_index", "test_argmax_keepdims_example_select_last_index", @@ -40,20 +47,20 @@ "test_argmin_negative_axis_keepdims_random_select_last_index", "test_argmin_no_keepdims_example_select_last_index", "test_argmin_no_keepdims_random_select_last_index", - "test_asin", "test_asin_example", - "test_asinh", + "test_asin", "test_asinh_example", - "test_atanh", + "test_asinh", "test_atanh_example", + "test_atanh", "test_averagepool_1d_default", "test_averagepool_2d_ceil", "test_averagepool_2d_default", "test_averagepool_2d_dilations", - "test_averagepool_2d_pads", "test_averagepool_2d_pads_count_include_pad", - "test_averagepool_2d_precomputed_pads", + "test_averagepool_2d_pads", "test_averagepool_2d_precomputed_pads_count_include_pad", + "test_averagepool_2d_precomputed_pads", "test_averagepool_2d_precomputed_same_upper", "test_averagepool_2d_precomputed_strides", "test_averagepool_2d_same_lower", @@ -69,84 +76,148 @@ "test_basic_deform_conv_without_padding", "test_batchnorm_epsilon_training_mode", "test_batchnorm_example_training_mode", - "test_bernoulli_double", "test_bernoulli_double_expanded", + "test_bernoulli_double", "test_bernoulli_expanded", - "test_bernoulli_seed", "test_bernoulli_seed_expanded", - "test_blackmanwindow", + "test_bernoulli_seed", "test_blackmanwindow_expanded", - "test_blackmanwindow_symmetric", "test_blackmanwindow_symmetric_expanded", - "test_celu", + "test_blackmanwindow_symmetric", + "test_blackmanwindow", + "test_cast_FLOAT_to_FLOAT8E4M3FN", + "test_cast_FLOAT_to_FLOAT8E4M3FNUZ", + "test_cast_FLOAT_to_FLOAT8E5M2", + "test_cast_FLOAT_to_FLOAT8E5M2FNUZ", + "test_cast_FLOAT_to_STRING", + "test_cast_FLOAT16_to_FLOAT8E4M3FN", + "test_cast_FLOAT16_to_FLOAT8E4M3FNUZ", + "test_cast_FLOAT16_to_FLOAT8E5M2", + "test_cast_FLOAT16_to_FLOAT8E5M2FNUZ", + "test_cast_FLOAT8E4M3FN_to_FLOAT", + "test_cast_FLOAT8E4M3FN_to_FLOAT16", + "test_cast_FLOAT8E4M3FNUZ_to_FLOAT", + "test_cast_FLOAT8E4M3FNUZ_to_FLOAT16", + "test_cast_FLOAT8E5M2_to_FLOAT", + "test_cast_FLOAT8E5M2_to_FLOAT16", + "test_cast_FLOAT8E5M2FNUZ_to_FLOAT", + "test_cast_FLOAT8E5M2FNUZ_to_FLOAT16", + "test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN", + "test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ", + "test_cast_no_saturate_FLOAT_to_FLOAT8E5M2", + "test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ", + "test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN", + "test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ", + "test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2", + "test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ", + "test_cast_STRING_to_FLOAT", + "test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded", + "test_castlike_FLOAT_to_FLOAT8E4M3FN", + "test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded", + "test_castlike_FLOAT_to_FLOAT8E4M3FNUZ", + "test_castlike_FLOAT_to_FLOAT8E5M2_expanded", + "test_castlike_FLOAT_to_FLOAT8E5M2", + "test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded", + "test_castlike_FLOAT_to_FLOAT8E5M2FNUZ", + "test_castlike_FLOAT_to_STRING_expanded", + "test_castlike_FLOAT_to_STRING", + "test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded", + "test_castlike_FLOAT8E4M3FN_to_FLOAT", + "test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded", + "test_castlike_FLOAT8E4M3FNUZ_to_FLOAT", + "test_castlike_FLOAT8E5M2_to_FLOAT_expanded", + "test_castlike_FLOAT8E5M2_to_FLOAT", + "test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded", + "test_castlike_FLOAT8E5M2FNUZ_to_FLOAT", + "test_castlike_STRING_to_FLOAT_expanded", + "test_castlike_STRING_to_FLOAT", "test_celu_expanded", - "test_center_crop_pad_crop", - "test_center_crop_pad_crop_and_pad", + "test_celu", "test_center_crop_pad_crop_and_pad_expanded", + "test_center_crop_pad_crop_and_pad", + "test_center_crop_pad_crop_axes_chw_expanded", "test_center_crop_pad_crop_axes_chw", + "test_center_crop_pad_crop_axes_hwc_expanded", "test_center_crop_pad_crop_axes_hwc", "test_center_crop_pad_crop_expanded", + "test_center_crop_pad_crop_negative_axes_hwc_expanded", "test_center_crop_pad_crop_negative_axes_hwc", - "test_center_crop_pad_pad", + "test_center_crop_pad_crop", "test_center_crop_pad_pad_expanded", + "test_center_crop_pad_pad", "test_clip_default_inbounds_expanded", + "test_clip_default_inbounds", "test_clip_default_int8_inbounds_expanded", - "test_col2im", + "test_clip_default_int8_inbounds", + "test_clip_default_int8_max", + "test_clip_default_max", "test_col2im_5d", "test_col2im_dilations", "test_col2im_pads", "test_col2im_strides", + "test_col2im", "test_compress_0", "test_compress_1", "test_compress_default_axis", "test_compress_negative_axis", - "test_constant_pad", "test_constant_pad_axes", "test_constant_pad_negative_axes", + "test_constant_pad", + "test_constantofshape_float_ones", + "test_constantofshape_int_shape_zero", + "test_constantofshape_int_zeros", "test_conv_with_autopad_same", "test_convinteger_with_padding", "test_convinteger_without_padding", "test_convtranspose_autopad_same", "test_convtranspose_kernel_shape", "test_convtranspose_output_shape", - "test_cosh", "test_cosh_example", - "test_cumsum_1d", + "test_cosh", "test_cumsum_1d_exclusive", - "test_cumsum_1d_reverse", "test_cumsum_1d_reverse_exclusive", + "test_cumsum_1d_reverse", + "test_cumsum_1d", "test_cumsum_2d_axis_0", "test_cumsum_2d_axis_1", "test_cumsum_2d_negative_axis", "test_deform_conv_with_mask_bias", "test_deform_conv_with_multiple_offset_groups", - "test_dequantizelinear", "test_dequantizelinear_axis", "test_dequantizelinear_blocked", + "test_dequantizelinear_e4m3fn_zero_point", + "test_dequantizelinear_e4m3fn", + "test_dequantizelinear_e5m2", "test_dequantizelinear_int16", "test_dequantizelinear_uint16", + "test_dequantizelinear", "test_det_2d", "test_det_nd", "test_dft_axis_opset19", + "test_dft_axis", "test_dft_inverse_opset19", + "test_dft_inverse", "test_dft_opset19", + "test_dft", "test_div_uint8", "test_dropout_default_mask_ratio", "test_dropout_default_old", "test_dropout_default_ratio", "test_dropout_random_old", - "test_dynamicquantizelinear", "test_dynamicquantizelinear_expanded", - "test_dynamicquantizelinear_max_adjusted", "test_dynamicquantizelinear_max_adjusted_expanded", - "test_dynamicquantizelinear_min_adjusted", + "test_dynamicquantizelinear_max_adjusted", "test_dynamicquantizelinear_min_adjusted_expanded", + "test_dynamicquantizelinear_min_adjusted", + "test_dynamicquantizelinear", "test_edge_pad", "test_einsum_batch_diagonal", "test_einsum_batch_matmul", "test_einsum_inner_prod", "test_einsum_sum", "test_einsum_transpose", + "test_equal_string_broadcast", + "test_equal_string", "test_expand_dim_changed", "test_expand_dim_unchanged", "test_eyelike_populate_off_main_diagonal", @@ -162,48 +233,51 @@ "test_flatten_negative_axis3", "test_flatten_negative_axis4", "test_gathernd_example_float32", - "test_gathernd_example_int32", "test_gathernd_example_int32_batch_dim1", + "test_gathernd_example_int32", "test_gelu_tanh_1", "test_gelu_tanh_2", "test_gemm_default_no_bias", - "test_globalaveragepool", "test_globalaveragepool_precomputed", - "test_globalmaxpool", + "test_globalaveragepool", "test_globalmaxpool_precomputed", - "test_greater", + "test_globalmaxpool", "test_greater_bcast", - "test_gridsample", + "test_greater", "test_gridsample_aligncorners_true", - "test_gridsample_bicubic", "test_gridsample_bicubic_align_corners_0_additional_1", "test_gridsample_bicubic_align_corners_1_additional_1", - "test_gridsample_bilinear", + "test_gridsample_bicubic", "test_gridsample_bilinear_align_corners_0_additional_1", "test_gridsample_bilinear_align_corners_1_additional_1", + "test_gridsample_bilinear", "test_gridsample_border_padding", - "test_gridsample_nearest", "test_gridsample_nearest_align_corners_0_additional_1", "test_gridsample_nearest_align_corners_1_additional_1", + "test_gridsample_nearest", "test_gridsample_reflection_padding", "test_gridsample_volumetric_bilinear_align_corners_0", "test_gridsample_volumetric_bilinear_align_corners_1", "test_gridsample_volumetric_nearest_align_corners_0", "test_gridsample_volumetric_nearest_align_corners_1", "test_gridsample_zeros_padding", - "test_group_normalization_epsilon", + "test_gridsample", "test_group_normalization_epsilon_expanded", - "test_group_normalization_example", + "test_group_normalization_epsilon", "test_group_normalization_example_expanded", + "test_group_normalization_example", "test_gru_batchwise", - "test_hammingwindow", + "test_gru_defaults", + "test_gru_seq_length", + "test_gru_with_initial_bias", "test_hammingwindow_expanded", - "test_hammingwindow_symmetric", "test_hammingwindow_symmetric_expanded", - "test_hannwindow", + "test_hammingwindow_symmetric", + "test_hammingwindow", "test_hannwindow_expanded", - "test_hannwindow_symmetric", "test_hannwindow_symmetric_expanded", + "test_hannwindow_symmetric", + "test_hannwindow", "test_hardmax_axis_0", "test_hardmax_axis_1", "test_hardmax_axis_2", @@ -212,44 +286,84 @@ "test_hardmax_negative_axis", "test_hardmax_one_hot", "test_hardswish", + "test_if", "test_image_decoder_decode_bmp_rgb", - "test_image_decoder_decode_jpeg2k_rgb", "test_image_decoder_decode_jpeg_bgr", "test_image_decoder_decode_jpeg_grayscale", "test_image_decoder_decode_jpeg_rgb", + "test_image_decoder_decode_jpeg2k_rgb", "test_image_decoder_decode_png_rgb", "test_image_decoder_decode_pnm_rgb", "test_image_decoder_decode_tiff_rgb", "test_image_decoder_decode_webp_rgb", "test_instancenorm_epsilon", "test_instancenorm_example", - "test_isinf", "test_isinf_float16", "test_isinf_negative", "test_isinf_positive", - "test_isnan", + "test_isinf", "test_isnan_float16", - "test_logsoftmax_axis_0", - "test_logsoftmax_axis_0_expanded", + "test_isnan", + "test_layer_normalization_2d_axis_negative_1_expanded_ver18", + "test_layer_normalization_2d_axis_negative_1_expanded", + "test_layer_normalization_2d_axis_negative_2_expanded_ver18", + "test_layer_normalization_2d_axis_negative_2_expanded", + "test_layer_normalization_2d_axis0_expanded_ver18", + "test_layer_normalization_2d_axis0_expanded", + "test_layer_normalization_2d_axis1_expanded_ver18", + "test_layer_normalization_2d_axis1_expanded", + "test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18", + "test_layer_normalization_3d_axis_negative_1_epsilon_expanded", + "test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18", + "test_layer_normalization_3d_axis_negative_2_epsilon_expanded", + "test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18", + "test_layer_normalization_3d_axis_negative_3_epsilon_expanded", + "test_layer_normalization_3d_axis0_epsilon_expanded_ver18", + "test_layer_normalization_3d_axis0_epsilon_expanded", + "test_layer_normalization_3d_axis1_epsilon_expanded_ver18", + "test_layer_normalization_3d_axis1_epsilon_expanded", + "test_layer_normalization_3d_axis2_epsilon_expanded_ver18", + "test_layer_normalization_3d_axis2_epsilon_expanded", + "test_layer_normalization_4d_axis_negative_1_expanded_ver18", + "test_layer_normalization_4d_axis_negative_1_expanded", + "test_layer_normalization_4d_axis_negative_2_expanded_ver18", + "test_layer_normalization_4d_axis_negative_2_expanded", + "test_layer_normalization_4d_axis_negative_3_expanded_ver18", + "test_layer_normalization_4d_axis_negative_3_expanded", + "test_layer_normalization_4d_axis_negative_4_expanded_ver18", + "test_layer_normalization_4d_axis_negative_4_expanded", + "test_layer_normalization_4d_axis0_expanded_ver18", + "test_layer_normalization_4d_axis0_expanded", + "test_layer_normalization_4d_axis1_expanded_ver18", + "test_layer_normalization_4d_axis1_expanded", + "test_layer_normalization_4d_axis2_expanded_ver18", + "test_layer_normalization_4d_axis2_expanded", + "test_layer_normalization_4d_axis3_expanded_ver18", + "test_layer_normalization_4d_axis3_expanded", + "test_layer_normalization_default_axis_expanded_ver18", + "test_layer_normalization_default_axis_expanded", "test_logsoftmax_axis_0_expanded_ver18", - "test_logsoftmax_axis_1", - "test_logsoftmax_axis_1_expanded", + "test_logsoftmax_axis_0_expanded", + "test_logsoftmax_axis_0", "test_logsoftmax_axis_1_expanded_ver18", - "test_logsoftmax_axis_2", - "test_logsoftmax_axis_2_expanded", + "test_logsoftmax_axis_1_expanded", + "test_logsoftmax_axis_1", "test_logsoftmax_axis_2_expanded_ver18", - "test_logsoftmax_default_axis", - "test_logsoftmax_default_axis_expanded", + "test_logsoftmax_axis_2_expanded", + "test_logsoftmax_axis_2", "test_logsoftmax_default_axis_expanded_ver18", - "test_logsoftmax_example_1", - "test_logsoftmax_example_1_expanded", + "test_logsoftmax_default_axis_expanded", + "test_logsoftmax_default_axis", "test_logsoftmax_example_1_expanded_ver18", - "test_logsoftmax_large_number", - "test_logsoftmax_large_number_expanded", + "test_logsoftmax_example_1_expanded", + "test_logsoftmax_example_1", "test_logsoftmax_large_number_expanded_ver18", - "test_logsoftmax_negative_axis", - "test_logsoftmax_negative_axis_expanded", + "test_logsoftmax_large_number_expanded", + "test_logsoftmax_large_number", "test_logsoftmax_negative_axis_expanded_ver18", + "test_logsoftmax_negative_axis_expanded", + "test_logsoftmax_negative_axis", + "test_loop11", "test_lppool_1d_default", "test_lppool_2d_default", "test_lppool_2d_dilations", @@ -258,9 +372,12 @@ "test_lppool_2d_same_upper", "test_lppool_2d_strides", "test_lppool_3d_default", - "test_lrn", "test_lrn_default", + "test_lrn", "test_lstm_batchwise", + "test_lstm_defaults", + "test_lstm_with_initial_bias", + "test_lstm_with_peepholes", "test_matmulinteger", "test_max_one_input", "test_maxpool_1d_default", @@ -276,9 +393,9 @@ "test_maxpool_2d_strides", "test_maxpool_2d_uint8", "test_maxpool_3d_default", - "test_maxpool_3d_dilations", - "test_maxpool_3d_dilations_use_ref_impl", "test_maxpool_3d_dilations_use_ref_impl_large", + "test_maxpool_3d_dilations_use_ref_impl", + "test_maxpool_3d_dilations", "test_maxpool_with_argmax_2d_precomputed_pads", "test_maxpool_with_argmax_2d_precomputed_strides", "test_maxunpool_export_with_output_shape", @@ -288,8 +405,8 @@ "test_mean_two_inputs", "test_melweightmatrix", "test_min_one_input", - "test_mish", "test_mish_expanded", + "test_mish", "test_mod_broadcast", "test_mod_int64_fmod", "test_mod_mixed_sign_float16", @@ -303,55 +420,55 @@ "test_mod_uint32", "test_mod_uint64", "test_mod_uint8", - "test_momentum", "test_momentum_multiple", - "test_mvn", - "test_mvn_expanded", + "test_momentum", "test_mvn_expanded_ver18", + "test_mvn_expanded", + "test_mvn", "test_nesterov_momentum", - "test_nllloss_NC", "test_nllloss_NC_expanded", - "test_nllloss_NCd1", + "test_nllloss_NC", "test_nllloss_NCd1_expanded", - "test_nllloss_NCd1_ii", "test_nllloss_NCd1_ii_expanded", - "test_nllloss_NCd1_mean_weight_negative_ii", + "test_nllloss_NCd1_ii", "test_nllloss_NCd1_mean_weight_negative_ii_expanded", - "test_nllloss_NCd1_weight", + "test_nllloss_NCd1_mean_weight_negative_ii", "test_nllloss_NCd1_weight_expanded", - "test_nllloss_NCd1_weight_ii", "test_nllloss_NCd1_weight_ii_expanded", - "test_nllloss_NCd1d2", + "test_nllloss_NCd1_weight_ii", + "test_nllloss_NCd1_weight", + "test_nllloss_NCd1", "test_nllloss_NCd1d2_expanded", - "test_nllloss_NCd1d2_no_weight_reduction_mean_ii", "test_nllloss_NCd1d2_no_weight_reduction_mean_ii_expanded", - "test_nllloss_NCd1d2_reduction_mean", + "test_nllloss_NCd1d2_no_weight_reduction_mean_ii", "test_nllloss_NCd1d2_reduction_mean_expanded", - "test_nllloss_NCd1d2_reduction_sum", + "test_nllloss_NCd1d2_reduction_mean", "test_nllloss_NCd1d2_reduction_sum_expanded", - "test_nllloss_NCd1d2_with_weight", + "test_nllloss_NCd1d2_reduction_sum", "test_nllloss_NCd1d2_with_weight_expanded", - "test_nllloss_NCd1d2_with_weight_reduction_mean", "test_nllloss_NCd1d2_with_weight_reduction_mean_expanded", - "test_nllloss_NCd1d2_with_weight_reduction_sum", + "test_nllloss_NCd1d2_with_weight_reduction_mean", "test_nllloss_NCd1d2_with_weight_reduction_sum_expanded", - "test_nllloss_NCd1d2_with_weight_reduction_sum_ii", "test_nllloss_NCd1d2_with_weight_reduction_sum_ii_expanded", - "test_nllloss_NCd1d2d3_none_no_weight_negative_ii", + "test_nllloss_NCd1d2_with_weight_reduction_sum_ii", + "test_nllloss_NCd1d2_with_weight_reduction_sum", + "test_nllloss_NCd1d2_with_weight", + "test_nllloss_NCd1d2", "test_nllloss_NCd1d2d3_none_no_weight_negative_ii_expanded", - "test_nllloss_NCd1d2d3_sum_weight_high_ii", + "test_nllloss_NCd1d2d3_none_no_weight_negative_ii", "test_nllloss_NCd1d2d3_sum_weight_high_ii_expanded", - "test_nllloss_NCd1d2d3d4d5_mean_weight", + "test_nllloss_NCd1d2d3_sum_weight_high_ii", "test_nllloss_NCd1d2d3d4d5_mean_weight_expanded", - "test_nllloss_NCd1d2d3d4d5_none_no_weight", + "test_nllloss_NCd1d2d3d4d5_mean_weight", "test_nllloss_NCd1d2d3d4d5_none_no_weight_expanded", + "test_nllloss_NCd1d2d3d4d5_none_no_weight", "test_nonmaxsuppression_center_point_box_format", "test_nonmaxsuppression_flipped_coordinates", "test_nonmaxsuppression_identical_boxes", "test_nonmaxsuppression_limit_output_size", "test_nonmaxsuppression_single_box", - "test_nonmaxsuppression_suppress_by_IOU", "test_nonmaxsuppression_suppress_by_IOU_and_scores", + "test_nonmaxsuppression_suppress_by_IOU", "test_nonmaxsuppression_two_batches", "test_nonmaxsuppression_two_classes", "test_nonzero_example", @@ -360,6 +477,8 @@ "test_onehot_with_negative_axis", "test_onehot_without_axis", "test_optional_get_element_tensor", + "test_optional_has_element_empty_no_input_name_optional_input", + "test_optional_has_element_empty_no_input_name_tensor_input", "test_optional_has_element_empty_no_input_optional_input", "test_optional_has_element_empty_no_input_tensor_input", "test_pow_types_int32_float32", @@ -377,75 +496,79 @@ "test_qlinearmatmul_3D_int8_float32", "test_qlinearmatmul_3D_uint8_float16", "test_qlinearmatmul_3D_uint8_float32", - "test_quantizelinear", "test_quantizelinear_axis", "test_quantizelinear_blocked", + "test_quantizelinear_e4m3fn", + "test_quantizelinear_e5m2", "test_quantizelinear_int16", "test_quantizelinear_uint16", + "test_quantizelinear", + "test_range_float_type_positive_delta_expanded", "test_range_float_type_positive_delta", + "test_range_int32_type_negative_delta_expanded", "test_range_int32_type_negative_delta", "test_reduce_l1_default_axes_keepdims_example", "test_reduce_l1_default_axes_keepdims_random", - "test_reduce_l1_do_not_keepdims_example", "test_reduce_l1_do_not_keepdims_example_expanded", - "test_reduce_l1_do_not_keepdims_random", + "test_reduce_l1_do_not_keepdims_example", "test_reduce_l1_do_not_keepdims_random_expanded", - "test_reduce_l1_empty_set", + "test_reduce_l1_do_not_keepdims_random", "test_reduce_l1_empty_set_expanded", - "test_reduce_l1_keep_dims_example", + "test_reduce_l1_empty_set", "test_reduce_l1_keep_dims_example_expanded", - "test_reduce_l1_keep_dims_random", + "test_reduce_l1_keep_dims_example", "test_reduce_l1_keep_dims_random_expanded", - "test_reduce_l1_negative_axes_keep_dims_example", + "test_reduce_l1_keep_dims_random", "test_reduce_l1_negative_axes_keep_dims_example_expanded", - "test_reduce_l1_negative_axes_keep_dims_random", + "test_reduce_l1_negative_axes_keep_dims_example", "test_reduce_l1_negative_axes_keep_dims_random_expanded", - "test_reduce_l2_default_axes_keepdims_example", + "test_reduce_l1_negative_axes_keep_dims_random", "test_reduce_l2_default_axes_keepdims_example_expanded", - "test_reduce_l2_default_axes_keepdims_random", + "test_reduce_l2_default_axes_keepdims_example", "test_reduce_l2_default_axes_keepdims_random_expanded", - "test_reduce_l2_do_not_keepdims_example", + "test_reduce_l2_default_axes_keepdims_random", "test_reduce_l2_do_not_keepdims_example_expanded", - "test_reduce_l2_do_not_keepdims_random", + "test_reduce_l2_do_not_keepdims_example", "test_reduce_l2_do_not_keepdims_random_expanded", - "test_reduce_l2_empty_set", + "test_reduce_l2_do_not_keepdims_random", "test_reduce_l2_empty_set_expanded", - "test_reduce_l2_keep_dims_example", + "test_reduce_l2_empty_set", "test_reduce_l2_keep_dims_example_expanded", - "test_reduce_l2_keep_dims_random", + "test_reduce_l2_keep_dims_example", "test_reduce_l2_keep_dims_random_expanded", - "test_reduce_l2_negative_axes_keep_dims_example", + "test_reduce_l2_keep_dims_random", "test_reduce_l2_negative_axes_keep_dims_example_expanded", - "test_reduce_l2_negative_axes_keep_dims_random", + "test_reduce_l2_negative_axes_keep_dims_example", "test_reduce_l2_negative_axes_keep_dims_random_expanded", - "test_reduce_log_sum_asc_axes", + "test_reduce_l2_negative_axes_keep_dims_random", "test_reduce_log_sum_asc_axes_expanded", - "test_reduce_log_sum_default", + "test_reduce_log_sum_asc_axes", "test_reduce_log_sum_default_expanded", - "test_reduce_log_sum_desc_axes", + "test_reduce_log_sum_default", "test_reduce_log_sum_desc_axes_expanded", - "test_reduce_log_sum_empty_set", + "test_reduce_log_sum_desc_axes", "test_reduce_log_sum_empty_set_expanded", - "test_reduce_log_sum_exp_default_axes_keepdims_example", + "test_reduce_log_sum_empty_set", "test_reduce_log_sum_exp_default_axes_keepdims_example_expanded", - "test_reduce_log_sum_exp_default_axes_keepdims_random", + "test_reduce_log_sum_exp_default_axes_keepdims_example", "test_reduce_log_sum_exp_default_axes_keepdims_random_expanded", - "test_reduce_log_sum_exp_do_not_keepdims_example", + "test_reduce_log_sum_exp_default_axes_keepdims_random", "test_reduce_log_sum_exp_do_not_keepdims_example_expanded", - "test_reduce_log_sum_exp_do_not_keepdims_random", + "test_reduce_log_sum_exp_do_not_keepdims_example", "test_reduce_log_sum_exp_do_not_keepdims_random_expanded", - "test_reduce_log_sum_exp_empty_set", + "test_reduce_log_sum_exp_do_not_keepdims_random", "test_reduce_log_sum_exp_empty_set_expanded", - "test_reduce_log_sum_exp_keepdims_example", + "test_reduce_log_sum_exp_empty_set", "test_reduce_log_sum_exp_keepdims_example_expanded", - "test_reduce_log_sum_exp_keepdims_random", + "test_reduce_log_sum_exp_keepdims_example", "test_reduce_log_sum_exp_keepdims_random_expanded", - "test_reduce_log_sum_exp_negative_axes_keepdims_example", + "test_reduce_log_sum_exp_keepdims_random", "test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded", - "test_reduce_log_sum_exp_negative_axes_keepdims_random", + "test_reduce_log_sum_exp_negative_axes_keepdims_example", "test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded", - "test_reduce_log_sum_negative_axes", + "test_reduce_log_sum_exp_negative_axes_keepdims_random", "test_reduce_log_sum_negative_axes_expanded", + "test_reduce_log_sum_negative_axes", "test_reduce_max_bool_inputs", "test_reduce_max_do_not_keepdims_example", "test_reduce_max_do_not_keepdims_random", @@ -480,28 +603,31 @@ "test_reduce_prod_negative_axes_keepdims_random", "test_reduce_sum_do_not_keepdims_example", "test_reduce_sum_do_not_keepdims_random", - "test_reduce_sum_empty_set", "test_reduce_sum_empty_set_non_reduced_axis_zero", + "test_reduce_sum_empty_set", "test_reduce_sum_keepdims_example", "test_reduce_sum_keepdims_random", "test_reduce_sum_negative_axes_keepdims_example", "test_reduce_sum_square_default_axes_keepdims_example", "test_reduce_sum_square_default_axes_keepdims_random", - "test_reduce_sum_square_do_not_keepdims_example", "test_reduce_sum_square_do_not_keepdims_example_expanded", - "test_reduce_sum_square_do_not_keepdims_random", + "test_reduce_sum_square_do_not_keepdims_example", "test_reduce_sum_square_do_not_keepdims_random_expanded", - "test_reduce_sum_square_empty_set", + "test_reduce_sum_square_do_not_keepdims_random", "test_reduce_sum_square_empty_set_expanded", - "test_reduce_sum_square_keepdims_example", + "test_reduce_sum_square_empty_set", "test_reduce_sum_square_keepdims_example_expanded", - "test_reduce_sum_square_keepdims_random", + "test_reduce_sum_square_keepdims_example", "test_reduce_sum_square_keepdims_random_expanded", - "test_reduce_sum_square_negative_axes_keepdims_example", + "test_reduce_sum_square_keepdims_random", "test_reduce_sum_square_negative_axes_keepdims_example_expanded", - "test_reduce_sum_square_negative_axes_keepdims_random", + "test_reduce_sum_square_negative_axes_keepdims_example", "test_reduce_sum_square_negative_axes_keepdims_random_expanded", + "test_reduce_sum_square_negative_axes_keepdims_random", "test_reflect_pad", + "test_regex_full_match_basic", + "test_regex_full_match_email_domain", + "test_regex_full_match_empty", "test_reshape_allowzero_reordered", "test_reshape_extended_dims", "test_reshape_negative_dim", @@ -512,136 +638,178 @@ "test_reshape_reordered_last_dims", "test_reshape_zero_and_negative_dim", "test_reshape_zero_dim", + "test_resize_downsample_scales_cubic_A_n0p5_exclude_outside", + "test_resize_downsample_scales_cubic_align_corners", + "test_resize_downsample_scales_cubic_antialias", + "test_resize_downsample_scales_cubic", + "test_resize_downsample_scales_linear_align_corners", + "test_resize_downsample_scales_linear_antialias", + "test_resize_downsample_scales_linear_half_pixel_symmetric", + "test_resize_downsample_scales_linear", + "test_resize_downsample_scales_nearest", + "test_resize_downsample_sizes_cubic_antialias", + "test_resize_downsample_sizes_cubic", + "test_resize_downsample_sizes_linear_antialias", + "test_resize_downsample_sizes_linear_pytorch_half_pixel", + "test_resize_downsample_sizes_nearest_not_larger", + "test_resize_downsample_sizes_nearest_not_smaller", + "test_resize_downsample_sizes_nearest", + "test_resize_tf_crop_and_resize_axes_2_3", + "test_resize_tf_crop_and_resize_axes_3_2", + "test_resize_tf_crop_and_resize", + "test_resize_upsample_scales_cubic_A_n0p5_exclude_outside", + "test_resize_upsample_scales_cubic_align_corners", + "test_resize_upsample_scales_cubic_asymmetric", + "test_resize_upsample_scales_cubic", + "test_resize_upsample_scales_linear_align_corners", + "test_resize_upsample_scales_linear_half_pixel_symmetric", + "test_resize_upsample_scales_linear", + "test_resize_upsample_scales_nearest_axes_2_3", + "test_resize_upsample_scales_nearest_axes_3_2", + "test_resize_upsample_scales_nearest", + "test_resize_upsample_sizes_cubic", + "test_resize_upsample_sizes_nearest_axes_2_3", + "test_resize_upsample_sizes_nearest_axes_3_2", + "test_resize_upsample_sizes_nearest_ceil_half_pixel", + "test_resize_upsample_sizes_nearest_floor_align_corners", + "test_resize_upsample_sizes_nearest_not_larger", + "test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric", + "test_resize_upsample_sizes_nearest", "test_reversesequence_batch", "test_reversesequence_time", + "test_rnn_seq_length", "test_roialign_aligned_false", "test_roialign_aligned_true", "test_roialign_mode_max", + "test_scan_sum", + "test_scan9_sum", "test_scatter_elements_with_duplicate_indices", "test_scatter_elements_with_reduction_max", "test_scatter_elements_with_reduction_min", "test_scatter_with_axis", "test_scatter_without_axis", - "test_scatternd", "test_scatternd_add", "test_scatternd_max", "test_scatternd_min", "test_scatternd_multiply", - "test_sce_NCd1_mean_weight_negative_ii", - "test_sce_NCd1_mean_weight_negative_ii_expanded", - "test_sce_NCd1_mean_weight_negative_ii_log_prob", - "test_sce_NCd1_mean_weight_negative_ii_log_prob_expanded", - "test_sce_NCd1d2d3_none_no_weight_negative_ii", - "test_sce_NCd1d2d3_none_no_weight_negative_ii_expanded", - "test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob", - "test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob_expanded", - "test_sce_NCd1d2d3_sum_weight_high_ii", - "test_sce_NCd1d2d3_sum_weight_high_ii_expanded", - "test_sce_NCd1d2d3_sum_weight_high_ii_log_prob", - "test_sce_NCd1d2d3_sum_weight_high_ii_log_prob_expanded", - "test_sce_NCd1d2d3d4d5_mean_weight", - "test_sce_NCd1d2d3d4d5_mean_weight_expanded", - "test_sce_NCd1d2d3d4d5_mean_weight_log_prob", - "test_sce_NCd1d2d3d4d5_mean_weight_log_prob_expanded", - "test_sce_NCd1d2d3d4d5_none_no_weight", - "test_sce_NCd1d2d3d4d5_none_no_weight_expanded", - "test_sce_NCd1d2d3d4d5_none_no_weight_log_prob", - "test_sce_NCd1d2d3d4d5_none_no_weight_log_prob_expanded", - "test_sce_mean", - "test_sce_mean_3d", + "test_scatternd", "test_sce_mean_3d_expanded", - "test_sce_mean_3d_log_prob", "test_sce_mean_3d_log_prob_expanded", + "test_sce_mean_3d_log_prob", + "test_sce_mean_3d", "test_sce_mean_expanded", - "test_sce_mean_log_prob", "test_sce_mean_log_prob_expanded", - "test_sce_mean_no_weight_ii", - "test_sce_mean_no_weight_ii_3d", + "test_sce_mean_log_prob", "test_sce_mean_no_weight_ii_3d_expanded", - "test_sce_mean_no_weight_ii_3d_log_prob", "test_sce_mean_no_weight_ii_3d_log_prob_expanded", - "test_sce_mean_no_weight_ii_4d", + "test_sce_mean_no_weight_ii_3d_log_prob", + "test_sce_mean_no_weight_ii_3d", "test_sce_mean_no_weight_ii_4d_expanded", - "test_sce_mean_no_weight_ii_4d_log_prob", "test_sce_mean_no_weight_ii_4d_log_prob_expanded", + "test_sce_mean_no_weight_ii_4d_log_prob", + "test_sce_mean_no_weight_ii_4d", "test_sce_mean_no_weight_ii_expanded", - "test_sce_mean_no_weight_ii_log_prob", "test_sce_mean_no_weight_ii_log_prob_expanded", - "test_sce_mean_weight", + "test_sce_mean_no_weight_ii_log_prob", + "test_sce_mean_no_weight_ii", "test_sce_mean_weight_expanded", - "test_sce_mean_weight_ii", - "test_sce_mean_weight_ii_3d", "test_sce_mean_weight_ii_3d_expanded", - "test_sce_mean_weight_ii_3d_log_prob", "test_sce_mean_weight_ii_3d_log_prob_expanded", - "test_sce_mean_weight_ii_4d", + "test_sce_mean_weight_ii_3d_log_prob", + "test_sce_mean_weight_ii_3d", "test_sce_mean_weight_ii_4d_expanded", - "test_sce_mean_weight_ii_4d_log_prob", "test_sce_mean_weight_ii_4d_log_prob_expanded", + "test_sce_mean_weight_ii_4d_log_prob", + "test_sce_mean_weight_ii_4d", "test_sce_mean_weight_ii_expanded", - "test_sce_mean_weight_ii_log_prob", "test_sce_mean_weight_ii_log_prob_expanded", - "test_sce_mean_weight_log_prob", + "test_sce_mean_weight_ii_log_prob", + "test_sce_mean_weight_ii", "test_sce_mean_weight_log_prob_expanded", - "test_sce_none", + "test_sce_mean_weight_log_prob", + "test_sce_mean_weight", + "test_sce_mean", + "test_sce_NCd1_mean_weight_negative_ii_expanded", + "test_sce_NCd1_mean_weight_negative_ii_log_prob_expanded", + "test_sce_NCd1_mean_weight_negative_ii_log_prob", + "test_sce_NCd1_mean_weight_negative_ii", + "test_sce_NCd1d2d3_none_no_weight_negative_ii_expanded", + "test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob_expanded", + "test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob", + "test_sce_NCd1d2d3_none_no_weight_negative_ii", + "test_sce_NCd1d2d3_sum_weight_high_ii_expanded", + "test_sce_NCd1d2d3_sum_weight_high_ii_log_prob_expanded", + "test_sce_NCd1d2d3_sum_weight_high_ii_log_prob", + "test_sce_NCd1d2d3_sum_weight_high_ii", + "test_sce_NCd1d2d3d4d5_mean_weight_expanded", + "test_sce_NCd1d2d3d4d5_mean_weight_log_prob_expanded", + "test_sce_NCd1d2d3d4d5_mean_weight_log_prob", + "test_sce_NCd1d2d3d4d5_mean_weight", + "test_sce_NCd1d2d3d4d5_none_no_weight_expanded", + "test_sce_NCd1d2d3d4d5_none_no_weight_log_prob_expanded", + "test_sce_NCd1d2d3d4d5_none_no_weight_log_prob", + "test_sce_NCd1d2d3d4d5_none_no_weight", "test_sce_none_expanded", - "test_sce_none_log_prob", "test_sce_none_log_prob_expanded", - "test_sce_none_weights", + "test_sce_none_log_prob", "test_sce_none_weights_expanded", - "test_sce_none_weights_log_prob", "test_sce_none_weights_log_prob_expanded", - "test_sce_sum", + "test_sce_none_weights_log_prob", + "test_sce_none_weights", + "test_sce_none", "test_sce_sum_expanded", - "test_sce_sum_log_prob", "test_sce_sum_log_prob_expanded", + "test_sce_sum_log_prob", + "test_sce_sum", "test_shape_end_1", "test_shape_end_negative_1", - "test_shape_start_1", "test_shape_start_1_end_2", "test_shape_start_1_end_negative_1", + "test_shape_start_1", "test_shape_start_negative_1", "test_shrink_hard", "test_shrink_soft", "test_simple_rnn_batchwise", - "test_sinh", + "test_simple_rnn_defaults", + "test_simple_rnn_with_initial_bias", "test_sinh_example", - "test_size", + "test_sinh", "test_size_example", - "test_slice", + "test_size", "test_slice_default_axes", "test_slice_default_steps", "test_slice_end_out_of_bounds", - "test_slice_neg", "test_slice_neg_steps", + "test_slice_neg", "test_slice_negative_axes", "test_slice_start_out_of_bounds", - "test_softmax_axis_0_expanded", + "test_slice", "test_softmax_axis_0_expanded_ver18", - "test_softmax_axis_1_expanded", + "test_softmax_axis_0_expanded", "test_softmax_axis_1_expanded_ver18", - "test_softmax_axis_2_expanded", + "test_softmax_axis_1_expanded", "test_softmax_axis_2_expanded_ver18", - "test_softmax_default_axis_expanded", + "test_softmax_axis_2_expanded", "test_softmax_default_axis_expanded_ver18", - "test_softmax_example_expanded", + "test_softmax_default_axis_expanded", "test_softmax_example_expanded_ver18", - "test_softmax_large_number_expanded", + "test_softmax_example_expanded", "test_softmax_large_number_expanded_ver18", - "test_softmax_negative_axis_expanded", + "test_softmax_large_number_expanded", "test_softmax_negative_axis_expanded_ver18", - "test_softplus", + "test_softmax_negative_axis_expanded", "test_softplus_example", - "test_softsign", + "test_softplus", "test_softsign_example", - "test_spacetodepth", + "test_softsign", "test_spacetodepth_example", + "test_spacetodepth", "test_split_1d_uneven_split_opset18", "test_split_2d_uneven_split_opset18", "test_split_equal_parts_1d_opset13", "test_split_equal_parts_1d_opset18", - "test_split_equal_parts_2d", "test_split_equal_parts_2d_opset13", + "test_split_equal_parts_2d", "test_split_equal_parts_default_axis_opset13", "test_split_equal_parts_default_axis_opset18", "test_split_variable_parts_1d_opset13", @@ -652,9 +820,27 @@ "test_split_variable_parts_default_axis_opset18", "test_split_zero_size_splits_opset13", "test_split_zero_size_splits_opset18", - "test_squeeze", "test_squeeze_negative_axes", + "test_squeeze", "test_stft_with_window", + "test_stft", + "test_string_concat_broadcasting", + "test_string_concat_empty_string", + "test_string_concat_utf8", + "test_string_concat_zero_dimensional", + "test_string_concat", + "test_string_split_basic", + "test_string_split_consecutive_delimiters", + "test_string_split_empty_string_delimiter", + "test_string_split_empty_tensor", + "test_string_split_maxsplit", + "test_string_split_no_delimiter", + "test_strnormalizer_export_monday_casesensintive_lower", + "test_strnormalizer_export_monday_casesensintive_nochangecase", + "test_strnormalizer_export_monday_casesensintive_upper", + "test_strnormalizer_export_monday_empty_output", + "test_strnormalizer_export_monday_insensintive_upper_twodim", + "test_strnormalizer_nostopwords_nochangecase", "test_sub_uint8", "test_tfidfvectorizer_tf_batch_onlybigrams_skip0", "test_tfidfvectorizer_tf_batch_onlybigrams_skip5", @@ -663,41 +849,41 @@ "test_tfidfvectorizer_tf_onlybigrams_levelempty", "test_tfidfvectorizer_tf_onlybigrams_skip5", "test_tfidfvectorizer_tf_uniandbigrams_skip5", - "test_thresholdedrelu", "test_thresholdedrelu_default", "test_thresholdedrelu_example", - "test_tile", + "test_thresholdedrelu", "test_tile_precomputed", - "test_top_k", + "test_tile", "test_top_k_negative_axis", "test_top_k_smallest", - "test_training_dropout", - "test_training_dropout_default", + "test_top_k", "test_training_dropout_default_mask", + "test_training_dropout_default", "test_training_dropout_mask", - "test_training_dropout_zero_ratio", "test_training_dropout_zero_ratio_mask", - "test_tril", + "test_training_dropout_zero_ratio", + "test_training_dropout", "test_tril_neg", "test_tril_one_row_neg", "test_tril_out_neg", "test_tril_out_pos", "test_tril_pos", - "test_tril_square", "test_tril_square_neg", + "test_tril_square", "test_tril_zero", - "test_triu", + "test_tril", "test_triu_neg", "test_triu_one_row", "test_triu_out_neg_out", "test_triu_out_pos", "test_triu_pos", - "test_triu_square", "test_triu_square_neg", + "test_triu_square", "test_triu_zero", + "test_triu", "test_unique_not_sorted_without_axis", - "test_unique_sorted_with_axis", "test_unique_sorted_with_axis_3d", + "test_unique_sorted_with_axis", "test_unique_sorted_with_negative_axis", "test_unique_sorted_without_axis", "test_unsqueeze_axis_0", diff --git a/iree_tests/configs/config_gpu_vulkan.json b/iree_tests/configs/config_gpu_vulkan.json index 1a0b7b91a..f59b60da4 100644 --- a/iree_tests/configs/config_gpu_vulkan.json +++ b/iree_tests/configs/config_gpu_vulkan.json @@ -9,21 +9,28 @@ "skip_compile_tests": [], "skip_run_tests": [], "expected_compile_failures": [ - "test_acos", "test_acos_example", - "test_acosh", + "test_acos", "test_acosh_example", - "test_adagrad", + "test_acosh", "test_adagrad_multiple", - "test_adam", + "test_adagrad", "test_adam_multiple", + "test_adam", "test_add_uint8", - "test_affine_grid_2d", + "test_affine_grid_2d_align_corners_expanded", "test_affine_grid_2d_align_corners", - "test_affine_grid_3d", + "test_affine_grid_2d_expanded", + "test_affine_grid_2d", + "test_affine_grid_3d_align_corners_expanded", "test_affine_grid_3d_align_corners", + "test_affine_grid_3d_expanded", + "test_affine_grid_3d", "test_ai_onnx_ml_array_feature_extractor", "test_ai_onnx_ml_binarizer", + "test_ai_onnx_ml_label_encoder_string_int_no_default", + "test_ai_onnx_ml_label_encoder_string_int", + "test_ai_onnx_ml_label_encoder_tensor_value_only_mapping", "test_argmax_default_axis_example_select_last_index", "test_argmax_default_axis_random_select_last_index", "test_argmax_keepdims_example_select_last_index", @@ -40,20 +47,20 @@ "test_argmin_negative_axis_keepdims_random_select_last_index", "test_argmin_no_keepdims_example_select_last_index", "test_argmin_no_keepdims_random_select_last_index", - "test_asin", "test_asin_example", - "test_asinh", + "test_asin", "test_asinh_example", - "test_atanh", + "test_asinh", "test_atanh_example", + "test_atanh", "test_averagepool_1d_default", "test_averagepool_2d_ceil", "test_averagepool_2d_default", "test_averagepool_2d_dilations", - "test_averagepool_2d_pads", "test_averagepool_2d_pads_count_include_pad", - "test_averagepool_2d_precomputed_pads", + "test_averagepool_2d_pads", "test_averagepool_2d_precomputed_pads_count_include_pad", + "test_averagepool_2d_precomputed_pads", "test_averagepool_2d_precomputed_same_upper", "test_averagepool_2d_precomputed_strides", "test_averagepool_2d_same_lower", @@ -69,84 +76,148 @@ "test_basic_deform_conv_without_padding", "test_batchnorm_epsilon_training_mode", "test_batchnorm_example_training_mode", - "test_bernoulli_double", "test_bernoulli_double_expanded", + "test_bernoulli_double", "test_bernoulli_expanded", - "test_bernoulli_seed", "test_bernoulli_seed_expanded", - "test_blackmanwindow", + "test_bernoulli_seed", "test_blackmanwindow_expanded", - "test_blackmanwindow_symmetric", "test_blackmanwindow_symmetric_expanded", - "test_celu", + "test_blackmanwindow_symmetric", + "test_blackmanwindow", + "test_cast_FLOAT_to_FLOAT8E4M3FN", + "test_cast_FLOAT_to_FLOAT8E4M3FNUZ", + "test_cast_FLOAT_to_FLOAT8E5M2", + "test_cast_FLOAT_to_FLOAT8E5M2FNUZ", + "test_cast_FLOAT_to_STRING", + "test_cast_FLOAT16_to_FLOAT8E4M3FN", + "test_cast_FLOAT16_to_FLOAT8E4M3FNUZ", + "test_cast_FLOAT16_to_FLOAT8E5M2", + "test_cast_FLOAT16_to_FLOAT8E5M2FNUZ", + "test_cast_FLOAT8E4M3FN_to_FLOAT", + "test_cast_FLOAT8E4M3FN_to_FLOAT16", + "test_cast_FLOAT8E4M3FNUZ_to_FLOAT", + "test_cast_FLOAT8E4M3FNUZ_to_FLOAT16", + "test_cast_FLOAT8E5M2_to_FLOAT", + "test_cast_FLOAT8E5M2_to_FLOAT16", + "test_cast_FLOAT8E5M2FNUZ_to_FLOAT", + "test_cast_FLOAT8E5M2FNUZ_to_FLOAT16", + "test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN", + "test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ", + "test_cast_no_saturate_FLOAT_to_FLOAT8E5M2", + "test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ", + "test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN", + "test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ", + "test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2", + "test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ", + "test_cast_STRING_to_FLOAT", + "test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded", + "test_castlike_FLOAT_to_FLOAT8E4M3FN", + "test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded", + "test_castlike_FLOAT_to_FLOAT8E4M3FNUZ", + "test_castlike_FLOAT_to_FLOAT8E5M2_expanded", + "test_castlike_FLOAT_to_FLOAT8E5M2", + "test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded", + "test_castlike_FLOAT_to_FLOAT8E5M2FNUZ", + "test_castlike_FLOAT_to_STRING_expanded", + "test_castlike_FLOAT_to_STRING", + "test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded", + "test_castlike_FLOAT8E4M3FN_to_FLOAT", + "test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded", + "test_castlike_FLOAT8E4M3FNUZ_to_FLOAT", + "test_castlike_FLOAT8E5M2_to_FLOAT_expanded", + "test_castlike_FLOAT8E5M2_to_FLOAT", + "test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded", + "test_castlike_FLOAT8E5M2FNUZ_to_FLOAT", + "test_castlike_STRING_to_FLOAT_expanded", + "test_castlike_STRING_to_FLOAT", "test_celu_expanded", - "test_center_crop_pad_crop", - "test_center_crop_pad_crop_and_pad", + "test_celu", "test_center_crop_pad_crop_and_pad_expanded", + "test_center_crop_pad_crop_and_pad", + "test_center_crop_pad_crop_axes_chw_expanded", "test_center_crop_pad_crop_axes_chw", + "test_center_crop_pad_crop_axes_hwc_expanded", "test_center_crop_pad_crop_axes_hwc", "test_center_crop_pad_crop_expanded", + "test_center_crop_pad_crop_negative_axes_hwc_expanded", "test_center_crop_pad_crop_negative_axes_hwc", - "test_center_crop_pad_pad", + "test_center_crop_pad_crop", "test_center_crop_pad_pad_expanded", + "test_center_crop_pad_pad", "test_clip_default_inbounds_expanded", + "test_clip_default_inbounds", "test_clip_default_int8_inbounds_expanded", - "test_col2im", + "test_clip_default_int8_inbounds", + "test_clip_default_int8_max", + "test_clip_default_max", "test_col2im_5d", "test_col2im_dilations", "test_col2im_pads", "test_col2im_strides", + "test_col2im", "test_compress_0", "test_compress_1", "test_compress_default_axis", "test_compress_negative_axis", - "test_constant_pad", "test_constant_pad_axes", "test_constant_pad_negative_axes", + "test_constant_pad", + "test_constantofshape_float_ones", + "test_constantofshape_int_shape_zero", + "test_constantofshape_int_zeros", "test_conv_with_autopad_same", "test_convinteger_with_padding", "test_convinteger_without_padding", "test_convtranspose_autopad_same", "test_convtranspose_kernel_shape", "test_convtranspose_output_shape", - "test_cosh", "test_cosh_example", - "test_cumsum_1d", + "test_cosh", "test_cumsum_1d_exclusive", - "test_cumsum_1d_reverse", "test_cumsum_1d_reverse_exclusive", + "test_cumsum_1d_reverse", + "test_cumsum_1d", "test_cumsum_2d_axis_0", "test_cumsum_2d_axis_1", "test_cumsum_2d_negative_axis", "test_deform_conv_with_mask_bias", "test_deform_conv_with_multiple_offset_groups", - "test_dequantizelinear", "test_dequantizelinear_axis", "test_dequantizelinear_blocked", + "test_dequantizelinear_e4m3fn_zero_point", + "test_dequantizelinear_e4m3fn", + "test_dequantizelinear_e5m2", "test_dequantizelinear_int16", "test_dequantizelinear_uint16", + "test_dequantizelinear", "test_det_2d", "test_det_nd", "test_dft_axis_opset19", + "test_dft_axis", "test_dft_inverse_opset19", + "test_dft_inverse", "test_dft_opset19", + "test_dft", "test_div_uint8", "test_dropout_default_mask_ratio", "test_dropout_default_old", "test_dropout_default_ratio", "test_dropout_random_old", - "test_dynamicquantizelinear", "test_dynamicquantizelinear_expanded", - "test_dynamicquantizelinear_max_adjusted", "test_dynamicquantizelinear_max_adjusted_expanded", - "test_dynamicquantizelinear_min_adjusted", + "test_dynamicquantizelinear_max_adjusted", "test_dynamicquantizelinear_min_adjusted_expanded", + "test_dynamicquantizelinear_min_adjusted", + "test_dynamicquantizelinear", "test_edge_pad", "test_einsum_batch_diagonal", "test_einsum_batch_matmul", "test_einsum_inner_prod", "test_einsum_sum", "test_einsum_transpose", + "test_equal_string_broadcast", + "test_equal_string", "test_expand_dim_changed", "test_expand_dim_unchanged", "test_eyelike_populate_off_main_diagonal", @@ -162,48 +233,51 @@ "test_flatten_negative_axis3", "test_flatten_negative_axis4", "test_gathernd_example_float32", - "test_gathernd_example_int32", "test_gathernd_example_int32_batch_dim1", + "test_gathernd_example_int32", "test_gelu_tanh_1", "test_gelu_tanh_2", "test_gemm_default_no_bias", - "test_globalaveragepool", "test_globalaveragepool_precomputed", - "test_globalmaxpool", + "test_globalaveragepool", "test_globalmaxpool_precomputed", - "test_greater", + "test_globalmaxpool", "test_greater_bcast", - "test_gridsample", + "test_greater", "test_gridsample_aligncorners_true", - "test_gridsample_bicubic", "test_gridsample_bicubic_align_corners_0_additional_1", "test_gridsample_bicubic_align_corners_1_additional_1", - "test_gridsample_bilinear", + "test_gridsample_bicubic", "test_gridsample_bilinear_align_corners_0_additional_1", "test_gridsample_bilinear_align_corners_1_additional_1", + "test_gridsample_bilinear", "test_gridsample_border_padding", - "test_gridsample_nearest", "test_gridsample_nearest_align_corners_0_additional_1", "test_gridsample_nearest_align_corners_1_additional_1", + "test_gridsample_nearest", "test_gridsample_reflection_padding", "test_gridsample_volumetric_bilinear_align_corners_0", "test_gridsample_volumetric_bilinear_align_corners_1", "test_gridsample_volumetric_nearest_align_corners_0", "test_gridsample_volumetric_nearest_align_corners_1", "test_gridsample_zeros_padding", - "test_group_normalization_epsilon", + "test_gridsample", "test_group_normalization_epsilon_expanded", - "test_group_normalization_example", + "test_group_normalization_epsilon", "test_group_normalization_example_expanded", + "test_group_normalization_example", "test_gru_batchwise", - "test_hammingwindow", + "test_gru_defaults", + "test_gru_seq_length", + "test_gru_with_initial_bias", "test_hammingwindow_expanded", - "test_hammingwindow_symmetric", "test_hammingwindow_symmetric_expanded", - "test_hannwindow", + "test_hammingwindow_symmetric", + "test_hammingwindow", "test_hannwindow_expanded", - "test_hannwindow_symmetric", "test_hannwindow_symmetric_expanded", + "test_hannwindow_symmetric", + "test_hannwindow", "test_hardmax_axis_0", "test_hardmax_axis_1", "test_hardmax_axis_2", @@ -212,44 +286,84 @@ "test_hardmax_negative_axis", "test_hardmax_one_hot", "test_hardswish", + "test_if", "test_image_decoder_decode_bmp_rgb", - "test_image_decoder_decode_jpeg2k_rgb", "test_image_decoder_decode_jpeg_bgr", "test_image_decoder_decode_jpeg_grayscale", "test_image_decoder_decode_jpeg_rgb", + "test_image_decoder_decode_jpeg2k_rgb", "test_image_decoder_decode_png_rgb", "test_image_decoder_decode_pnm_rgb", "test_image_decoder_decode_tiff_rgb", "test_image_decoder_decode_webp_rgb", "test_instancenorm_epsilon", "test_instancenorm_example", - "test_isinf", "test_isinf_float16", "test_isinf_negative", "test_isinf_positive", - "test_isnan", + "test_isinf", "test_isnan_float16", - "test_logsoftmax_axis_0", - "test_logsoftmax_axis_0_expanded", + "test_isnan", + "test_layer_normalization_2d_axis_negative_1_expanded_ver18", + "test_layer_normalization_2d_axis_negative_1_expanded", + "test_layer_normalization_2d_axis_negative_2_expanded_ver18", + "test_layer_normalization_2d_axis_negative_2_expanded", + "test_layer_normalization_2d_axis0_expanded_ver18", + "test_layer_normalization_2d_axis0_expanded", + "test_layer_normalization_2d_axis1_expanded_ver18", + "test_layer_normalization_2d_axis1_expanded", + "test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18", + "test_layer_normalization_3d_axis_negative_1_epsilon_expanded", + "test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18", + "test_layer_normalization_3d_axis_negative_2_epsilon_expanded", + "test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18", + "test_layer_normalization_3d_axis_negative_3_epsilon_expanded", + "test_layer_normalization_3d_axis0_epsilon_expanded_ver18", + "test_layer_normalization_3d_axis0_epsilon_expanded", + "test_layer_normalization_3d_axis1_epsilon_expanded_ver18", + "test_layer_normalization_3d_axis1_epsilon_expanded", + "test_layer_normalization_3d_axis2_epsilon_expanded_ver18", + "test_layer_normalization_3d_axis2_epsilon_expanded", + "test_layer_normalization_4d_axis_negative_1_expanded_ver18", + "test_layer_normalization_4d_axis_negative_1_expanded", + "test_layer_normalization_4d_axis_negative_2_expanded_ver18", + "test_layer_normalization_4d_axis_negative_2_expanded", + "test_layer_normalization_4d_axis_negative_3_expanded_ver18", + "test_layer_normalization_4d_axis_negative_3_expanded", + "test_layer_normalization_4d_axis_negative_4_expanded_ver18", + "test_layer_normalization_4d_axis_negative_4_expanded", + "test_layer_normalization_4d_axis0_expanded_ver18", + "test_layer_normalization_4d_axis0_expanded", + "test_layer_normalization_4d_axis1_expanded_ver18", + "test_layer_normalization_4d_axis1_expanded", + "test_layer_normalization_4d_axis2_expanded_ver18", + "test_layer_normalization_4d_axis2_expanded", + "test_layer_normalization_4d_axis3_expanded_ver18", + "test_layer_normalization_4d_axis3_expanded", + "test_layer_normalization_default_axis_expanded_ver18", + "test_layer_normalization_default_axis_expanded", "test_logsoftmax_axis_0_expanded_ver18", - "test_logsoftmax_axis_1", - "test_logsoftmax_axis_1_expanded", + "test_logsoftmax_axis_0_expanded", + "test_logsoftmax_axis_0", "test_logsoftmax_axis_1_expanded_ver18", - "test_logsoftmax_axis_2", - "test_logsoftmax_axis_2_expanded", + "test_logsoftmax_axis_1_expanded", + "test_logsoftmax_axis_1", "test_logsoftmax_axis_2_expanded_ver18", - "test_logsoftmax_default_axis", - "test_logsoftmax_default_axis_expanded", + "test_logsoftmax_axis_2_expanded", + "test_logsoftmax_axis_2", "test_logsoftmax_default_axis_expanded_ver18", - "test_logsoftmax_example_1", - "test_logsoftmax_example_1_expanded", + "test_logsoftmax_default_axis_expanded", + "test_logsoftmax_default_axis", "test_logsoftmax_example_1_expanded_ver18", - "test_logsoftmax_large_number", - "test_logsoftmax_large_number_expanded", + "test_logsoftmax_example_1_expanded", + "test_logsoftmax_example_1", "test_logsoftmax_large_number_expanded_ver18", - "test_logsoftmax_negative_axis", - "test_logsoftmax_negative_axis_expanded", + "test_logsoftmax_large_number_expanded", + "test_logsoftmax_large_number", "test_logsoftmax_negative_axis_expanded_ver18", + "test_logsoftmax_negative_axis_expanded", + "test_logsoftmax_negative_axis", + "test_loop11", "test_lppool_1d_default", "test_lppool_2d_default", "test_lppool_2d_dilations", @@ -258,9 +372,12 @@ "test_lppool_2d_same_upper", "test_lppool_2d_strides", "test_lppool_3d_default", - "test_lrn", "test_lrn_default", + "test_lrn", "test_lstm_batchwise", + "test_lstm_defaults", + "test_lstm_with_initial_bias", + "test_lstm_with_peepholes", "test_matmulinteger", "test_max_one_input", "test_maxpool_1d_default", @@ -276,9 +393,9 @@ "test_maxpool_2d_strides", "test_maxpool_2d_uint8", "test_maxpool_3d_default", - "test_maxpool_3d_dilations", - "test_maxpool_3d_dilations_use_ref_impl", "test_maxpool_3d_dilations_use_ref_impl_large", + "test_maxpool_3d_dilations_use_ref_impl", + "test_maxpool_3d_dilations", "test_maxpool_with_argmax_2d_precomputed_pads", "test_maxpool_with_argmax_2d_precomputed_strides", "test_maxunpool_export_with_output_shape", @@ -288,8 +405,8 @@ "test_mean_two_inputs", "test_melweightmatrix", "test_min_one_input", - "test_mish", "test_mish_expanded", + "test_mish", "test_mod_broadcast", "test_mod_int64_fmod", "test_mod_mixed_sign_float16", @@ -303,55 +420,55 @@ "test_mod_uint32", "test_mod_uint64", "test_mod_uint8", - "test_momentum", "test_momentum_multiple", - "test_mvn", - "test_mvn_expanded", + "test_momentum", "test_mvn_expanded_ver18", + "test_mvn_expanded", + "test_mvn", "test_nesterov_momentum", - "test_nllloss_NC", "test_nllloss_NC_expanded", - "test_nllloss_NCd1", + "test_nllloss_NC", "test_nllloss_NCd1_expanded", - "test_nllloss_NCd1_ii", "test_nllloss_NCd1_ii_expanded", - "test_nllloss_NCd1_mean_weight_negative_ii", + "test_nllloss_NCd1_ii", "test_nllloss_NCd1_mean_weight_negative_ii_expanded", - "test_nllloss_NCd1_weight", + "test_nllloss_NCd1_mean_weight_negative_ii", "test_nllloss_NCd1_weight_expanded", - "test_nllloss_NCd1_weight_ii", "test_nllloss_NCd1_weight_ii_expanded", - "test_nllloss_NCd1d2", + "test_nllloss_NCd1_weight_ii", + "test_nllloss_NCd1_weight", + "test_nllloss_NCd1", "test_nllloss_NCd1d2_expanded", - "test_nllloss_NCd1d2_no_weight_reduction_mean_ii", "test_nllloss_NCd1d2_no_weight_reduction_mean_ii_expanded", - "test_nllloss_NCd1d2_reduction_mean", + "test_nllloss_NCd1d2_no_weight_reduction_mean_ii", "test_nllloss_NCd1d2_reduction_mean_expanded", - "test_nllloss_NCd1d2_reduction_sum", + "test_nllloss_NCd1d2_reduction_mean", "test_nllloss_NCd1d2_reduction_sum_expanded", - "test_nllloss_NCd1d2_with_weight", + "test_nllloss_NCd1d2_reduction_sum", "test_nllloss_NCd1d2_with_weight_expanded", - "test_nllloss_NCd1d2_with_weight_reduction_mean", "test_nllloss_NCd1d2_with_weight_reduction_mean_expanded", - "test_nllloss_NCd1d2_with_weight_reduction_sum", + "test_nllloss_NCd1d2_with_weight_reduction_mean", "test_nllloss_NCd1d2_with_weight_reduction_sum_expanded", - "test_nllloss_NCd1d2_with_weight_reduction_sum_ii", "test_nllloss_NCd1d2_with_weight_reduction_sum_ii_expanded", - "test_nllloss_NCd1d2d3_none_no_weight_negative_ii", + "test_nllloss_NCd1d2_with_weight_reduction_sum_ii", + "test_nllloss_NCd1d2_with_weight_reduction_sum", + "test_nllloss_NCd1d2_with_weight", + "test_nllloss_NCd1d2", "test_nllloss_NCd1d2d3_none_no_weight_negative_ii_expanded", - "test_nllloss_NCd1d2d3_sum_weight_high_ii", + "test_nllloss_NCd1d2d3_none_no_weight_negative_ii", "test_nllloss_NCd1d2d3_sum_weight_high_ii_expanded", - "test_nllloss_NCd1d2d3d4d5_mean_weight", + "test_nllloss_NCd1d2d3_sum_weight_high_ii", "test_nllloss_NCd1d2d3d4d5_mean_weight_expanded", - "test_nllloss_NCd1d2d3d4d5_none_no_weight", + "test_nllloss_NCd1d2d3d4d5_mean_weight", "test_nllloss_NCd1d2d3d4d5_none_no_weight_expanded", + "test_nllloss_NCd1d2d3d4d5_none_no_weight", "test_nonmaxsuppression_center_point_box_format", "test_nonmaxsuppression_flipped_coordinates", "test_nonmaxsuppression_identical_boxes", "test_nonmaxsuppression_limit_output_size", "test_nonmaxsuppression_single_box", - "test_nonmaxsuppression_suppress_by_IOU", "test_nonmaxsuppression_suppress_by_IOU_and_scores", + "test_nonmaxsuppression_suppress_by_IOU", "test_nonmaxsuppression_two_batches", "test_nonmaxsuppression_two_classes", "test_nonzero_example", @@ -360,6 +477,8 @@ "test_onehot_with_negative_axis", "test_onehot_without_axis", "test_optional_get_element_tensor", + "test_optional_has_element_empty_no_input_name_optional_input", + "test_optional_has_element_empty_no_input_name_tensor_input", "test_optional_has_element_empty_no_input_optional_input", "test_optional_has_element_empty_no_input_tensor_input", "test_pow_types_int32_float32", @@ -377,75 +496,79 @@ "test_qlinearmatmul_3D_int8_float32", "test_qlinearmatmul_3D_uint8_float16", "test_qlinearmatmul_3D_uint8_float32", - "test_quantizelinear", "test_quantizelinear_axis", "test_quantizelinear_blocked", + "test_quantizelinear_e4m3fn", + "test_quantizelinear_e5m2", "test_quantizelinear_int16", "test_quantizelinear_uint16", + "test_quantizelinear", + "test_range_float_type_positive_delta_expanded", "test_range_float_type_positive_delta", + "test_range_int32_type_negative_delta_expanded", "test_range_int32_type_negative_delta", "test_reduce_l1_default_axes_keepdims_example", "test_reduce_l1_default_axes_keepdims_random", - "test_reduce_l1_do_not_keepdims_example", "test_reduce_l1_do_not_keepdims_example_expanded", - "test_reduce_l1_do_not_keepdims_random", + "test_reduce_l1_do_not_keepdims_example", "test_reduce_l1_do_not_keepdims_random_expanded", - "test_reduce_l1_empty_set", + "test_reduce_l1_do_not_keepdims_random", "test_reduce_l1_empty_set_expanded", - "test_reduce_l1_keep_dims_example", + "test_reduce_l1_empty_set", "test_reduce_l1_keep_dims_example_expanded", - "test_reduce_l1_keep_dims_random", + "test_reduce_l1_keep_dims_example", "test_reduce_l1_keep_dims_random_expanded", - "test_reduce_l1_negative_axes_keep_dims_example", + "test_reduce_l1_keep_dims_random", "test_reduce_l1_negative_axes_keep_dims_example_expanded", - "test_reduce_l1_negative_axes_keep_dims_random", + "test_reduce_l1_negative_axes_keep_dims_example", "test_reduce_l1_negative_axes_keep_dims_random_expanded", - "test_reduce_l2_default_axes_keepdims_example", + "test_reduce_l1_negative_axes_keep_dims_random", "test_reduce_l2_default_axes_keepdims_example_expanded", - "test_reduce_l2_default_axes_keepdims_random", + "test_reduce_l2_default_axes_keepdims_example", "test_reduce_l2_default_axes_keepdims_random_expanded", - "test_reduce_l2_do_not_keepdims_example", + "test_reduce_l2_default_axes_keepdims_random", "test_reduce_l2_do_not_keepdims_example_expanded", - "test_reduce_l2_do_not_keepdims_random", + "test_reduce_l2_do_not_keepdims_example", "test_reduce_l2_do_not_keepdims_random_expanded", - "test_reduce_l2_empty_set", + "test_reduce_l2_do_not_keepdims_random", "test_reduce_l2_empty_set_expanded", - "test_reduce_l2_keep_dims_example", + "test_reduce_l2_empty_set", "test_reduce_l2_keep_dims_example_expanded", - "test_reduce_l2_keep_dims_random", + "test_reduce_l2_keep_dims_example", "test_reduce_l2_keep_dims_random_expanded", - "test_reduce_l2_negative_axes_keep_dims_example", + "test_reduce_l2_keep_dims_random", "test_reduce_l2_negative_axes_keep_dims_example_expanded", - "test_reduce_l2_negative_axes_keep_dims_random", + "test_reduce_l2_negative_axes_keep_dims_example", "test_reduce_l2_negative_axes_keep_dims_random_expanded", - "test_reduce_log_sum_asc_axes", + "test_reduce_l2_negative_axes_keep_dims_random", "test_reduce_log_sum_asc_axes_expanded", - "test_reduce_log_sum_default", + "test_reduce_log_sum_asc_axes", "test_reduce_log_sum_default_expanded", - "test_reduce_log_sum_desc_axes", + "test_reduce_log_sum_default", "test_reduce_log_sum_desc_axes_expanded", - "test_reduce_log_sum_empty_set", + "test_reduce_log_sum_desc_axes", "test_reduce_log_sum_empty_set_expanded", - "test_reduce_log_sum_exp_default_axes_keepdims_example", + "test_reduce_log_sum_empty_set", "test_reduce_log_sum_exp_default_axes_keepdims_example_expanded", - "test_reduce_log_sum_exp_default_axes_keepdims_random", + "test_reduce_log_sum_exp_default_axes_keepdims_example", "test_reduce_log_sum_exp_default_axes_keepdims_random_expanded", - "test_reduce_log_sum_exp_do_not_keepdims_example", + "test_reduce_log_sum_exp_default_axes_keepdims_random", "test_reduce_log_sum_exp_do_not_keepdims_example_expanded", - "test_reduce_log_sum_exp_do_not_keepdims_random", + "test_reduce_log_sum_exp_do_not_keepdims_example", "test_reduce_log_sum_exp_do_not_keepdims_random_expanded", - "test_reduce_log_sum_exp_empty_set", + "test_reduce_log_sum_exp_do_not_keepdims_random", "test_reduce_log_sum_exp_empty_set_expanded", - "test_reduce_log_sum_exp_keepdims_example", + "test_reduce_log_sum_exp_empty_set", "test_reduce_log_sum_exp_keepdims_example_expanded", - "test_reduce_log_sum_exp_keepdims_random", + "test_reduce_log_sum_exp_keepdims_example", "test_reduce_log_sum_exp_keepdims_random_expanded", - "test_reduce_log_sum_exp_negative_axes_keepdims_example", + "test_reduce_log_sum_exp_keepdims_random", "test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded", - "test_reduce_log_sum_exp_negative_axes_keepdims_random", + "test_reduce_log_sum_exp_negative_axes_keepdims_example", "test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded", - "test_reduce_log_sum_negative_axes", + "test_reduce_log_sum_exp_negative_axes_keepdims_random", "test_reduce_log_sum_negative_axes_expanded", + "test_reduce_log_sum_negative_axes", "test_reduce_max_bool_inputs", "test_reduce_max_do_not_keepdims_example", "test_reduce_max_do_not_keepdims_random", @@ -480,28 +603,31 @@ "test_reduce_prod_negative_axes_keepdims_random", "test_reduce_sum_do_not_keepdims_example", "test_reduce_sum_do_not_keepdims_random", - "test_reduce_sum_empty_set", "test_reduce_sum_empty_set_non_reduced_axis_zero", + "test_reduce_sum_empty_set", "test_reduce_sum_keepdims_example", "test_reduce_sum_keepdims_random", "test_reduce_sum_negative_axes_keepdims_example", "test_reduce_sum_square_default_axes_keepdims_example", "test_reduce_sum_square_default_axes_keepdims_random", - "test_reduce_sum_square_do_not_keepdims_example", "test_reduce_sum_square_do_not_keepdims_example_expanded", - "test_reduce_sum_square_do_not_keepdims_random", + "test_reduce_sum_square_do_not_keepdims_example", "test_reduce_sum_square_do_not_keepdims_random_expanded", - "test_reduce_sum_square_empty_set", + "test_reduce_sum_square_do_not_keepdims_random", "test_reduce_sum_square_empty_set_expanded", - "test_reduce_sum_square_keepdims_example", + "test_reduce_sum_square_empty_set", "test_reduce_sum_square_keepdims_example_expanded", - "test_reduce_sum_square_keepdims_random", + "test_reduce_sum_square_keepdims_example", "test_reduce_sum_square_keepdims_random_expanded", - "test_reduce_sum_square_negative_axes_keepdims_example", + "test_reduce_sum_square_keepdims_random", "test_reduce_sum_square_negative_axes_keepdims_example_expanded", - "test_reduce_sum_square_negative_axes_keepdims_random", + "test_reduce_sum_square_negative_axes_keepdims_example", "test_reduce_sum_square_negative_axes_keepdims_random_expanded", + "test_reduce_sum_square_negative_axes_keepdims_random", "test_reflect_pad", + "test_regex_full_match_basic", + "test_regex_full_match_email_domain", + "test_regex_full_match_empty", "test_reshape_allowzero_reordered", "test_reshape_extended_dims", "test_reshape_negative_dim", @@ -512,136 +638,178 @@ "test_reshape_reordered_last_dims", "test_reshape_zero_and_negative_dim", "test_reshape_zero_dim", + "test_resize_downsample_scales_cubic_A_n0p5_exclude_outside", + "test_resize_downsample_scales_cubic_align_corners", + "test_resize_downsample_scales_cubic_antialias", + "test_resize_downsample_scales_cubic", + "test_resize_downsample_scales_linear_align_corners", + "test_resize_downsample_scales_linear_antialias", + "test_resize_downsample_scales_linear_half_pixel_symmetric", + "test_resize_downsample_scales_linear", + "test_resize_downsample_scales_nearest", + "test_resize_downsample_sizes_cubic_antialias", + "test_resize_downsample_sizes_cubic", + "test_resize_downsample_sizes_linear_antialias", + "test_resize_downsample_sizes_linear_pytorch_half_pixel", + "test_resize_downsample_sizes_nearest_not_larger", + "test_resize_downsample_sizes_nearest_not_smaller", + "test_resize_downsample_sizes_nearest", + "test_resize_tf_crop_and_resize_axes_2_3", + "test_resize_tf_crop_and_resize_axes_3_2", + "test_resize_tf_crop_and_resize", + "test_resize_upsample_scales_cubic_A_n0p5_exclude_outside", + "test_resize_upsample_scales_cubic_align_corners", + "test_resize_upsample_scales_cubic_asymmetric", + "test_resize_upsample_scales_cubic", + "test_resize_upsample_scales_linear_align_corners", + "test_resize_upsample_scales_linear_half_pixel_symmetric", + "test_resize_upsample_scales_linear", + "test_resize_upsample_scales_nearest_axes_2_3", + "test_resize_upsample_scales_nearest_axes_3_2", + "test_resize_upsample_scales_nearest", + "test_resize_upsample_sizes_cubic", + "test_resize_upsample_sizes_nearest_axes_2_3", + "test_resize_upsample_sizes_nearest_axes_3_2", + "test_resize_upsample_sizes_nearest_ceil_half_pixel", + "test_resize_upsample_sizes_nearest_floor_align_corners", + "test_resize_upsample_sizes_nearest_not_larger", + "test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric", + "test_resize_upsample_sizes_nearest", "test_reversesequence_batch", "test_reversesequence_time", + "test_rnn_seq_length", "test_roialign_aligned_false", "test_roialign_aligned_true", "test_roialign_mode_max", + "test_scan_sum", + "test_scan9_sum", "test_scatter_elements_with_duplicate_indices", "test_scatter_elements_with_reduction_max", "test_scatter_elements_with_reduction_min", "test_scatter_with_axis", "test_scatter_without_axis", - "test_scatternd", "test_scatternd_add", "test_scatternd_max", "test_scatternd_min", "test_scatternd_multiply", - "test_sce_NCd1_mean_weight_negative_ii", - "test_sce_NCd1_mean_weight_negative_ii_expanded", - "test_sce_NCd1_mean_weight_negative_ii_log_prob", - "test_sce_NCd1_mean_weight_negative_ii_log_prob_expanded", - "test_sce_NCd1d2d3_none_no_weight_negative_ii", - "test_sce_NCd1d2d3_none_no_weight_negative_ii_expanded", - "test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob", - "test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob_expanded", - "test_sce_NCd1d2d3_sum_weight_high_ii", - "test_sce_NCd1d2d3_sum_weight_high_ii_expanded", - "test_sce_NCd1d2d3_sum_weight_high_ii_log_prob", - "test_sce_NCd1d2d3_sum_weight_high_ii_log_prob_expanded", - "test_sce_NCd1d2d3d4d5_mean_weight", - "test_sce_NCd1d2d3d4d5_mean_weight_expanded", - "test_sce_NCd1d2d3d4d5_mean_weight_log_prob", - "test_sce_NCd1d2d3d4d5_mean_weight_log_prob_expanded", - "test_sce_NCd1d2d3d4d5_none_no_weight", - "test_sce_NCd1d2d3d4d5_none_no_weight_expanded", - "test_sce_NCd1d2d3d4d5_none_no_weight_log_prob", - "test_sce_NCd1d2d3d4d5_none_no_weight_log_prob_expanded", - "test_sce_mean", - "test_sce_mean_3d", + "test_scatternd", "test_sce_mean_3d_expanded", - "test_sce_mean_3d_log_prob", "test_sce_mean_3d_log_prob_expanded", + "test_sce_mean_3d_log_prob", + "test_sce_mean_3d", "test_sce_mean_expanded", - "test_sce_mean_log_prob", "test_sce_mean_log_prob_expanded", - "test_sce_mean_no_weight_ii", - "test_sce_mean_no_weight_ii_3d", + "test_sce_mean_log_prob", "test_sce_mean_no_weight_ii_3d_expanded", - "test_sce_mean_no_weight_ii_3d_log_prob", "test_sce_mean_no_weight_ii_3d_log_prob_expanded", - "test_sce_mean_no_weight_ii_4d", + "test_sce_mean_no_weight_ii_3d_log_prob", + "test_sce_mean_no_weight_ii_3d", "test_sce_mean_no_weight_ii_4d_expanded", - "test_sce_mean_no_weight_ii_4d_log_prob", "test_sce_mean_no_weight_ii_4d_log_prob_expanded", + "test_sce_mean_no_weight_ii_4d_log_prob", + "test_sce_mean_no_weight_ii_4d", "test_sce_mean_no_weight_ii_expanded", - "test_sce_mean_no_weight_ii_log_prob", "test_sce_mean_no_weight_ii_log_prob_expanded", - "test_sce_mean_weight", + "test_sce_mean_no_weight_ii_log_prob", + "test_sce_mean_no_weight_ii", "test_sce_mean_weight_expanded", - "test_sce_mean_weight_ii", - "test_sce_mean_weight_ii_3d", "test_sce_mean_weight_ii_3d_expanded", - "test_sce_mean_weight_ii_3d_log_prob", "test_sce_mean_weight_ii_3d_log_prob_expanded", - "test_sce_mean_weight_ii_4d", + "test_sce_mean_weight_ii_3d_log_prob", + "test_sce_mean_weight_ii_3d", "test_sce_mean_weight_ii_4d_expanded", - "test_sce_mean_weight_ii_4d_log_prob", "test_sce_mean_weight_ii_4d_log_prob_expanded", + "test_sce_mean_weight_ii_4d_log_prob", + "test_sce_mean_weight_ii_4d", "test_sce_mean_weight_ii_expanded", - "test_sce_mean_weight_ii_log_prob", "test_sce_mean_weight_ii_log_prob_expanded", - "test_sce_mean_weight_log_prob", + "test_sce_mean_weight_ii_log_prob", + "test_sce_mean_weight_ii", "test_sce_mean_weight_log_prob_expanded", - "test_sce_none", + "test_sce_mean_weight_log_prob", + "test_sce_mean_weight", + "test_sce_mean", + "test_sce_NCd1_mean_weight_negative_ii_expanded", + "test_sce_NCd1_mean_weight_negative_ii_log_prob_expanded", + "test_sce_NCd1_mean_weight_negative_ii_log_prob", + "test_sce_NCd1_mean_weight_negative_ii", + "test_sce_NCd1d2d3_none_no_weight_negative_ii_expanded", + "test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob_expanded", + "test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob", + "test_sce_NCd1d2d3_none_no_weight_negative_ii", + "test_sce_NCd1d2d3_sum_weight_high_ii_expanded", + "test_sce_NCd1d2d3_sum_weight_high_ii_log_prob_expanded", + "test_sce_NCd1d2d3_sum_weight_high_ii_log_prob", + "test_sce_NCd1d2d3_sum_weight_high_ii", + "test_sce_NCd1d2d3d4d5_mean_weight_expanded", + "test_sce_NCd1d2d3d4d5_mean_weight_log_prob_expanded", + "test_sce_NCd1d2d3d4d5_mean_weight_log_prob", + "test_sce_NCd1d2d3d4d5_mean_weight", + "test_sce_NCd1d2d3d4d5_none_no_weight_expanded", + "test_sce_NCd1d2d3d4d5_none_no_weight_log_prob_expanded", + "test_sce_NCd1d2d3d4d5_none_no_weight_log_prob", + "test_sce_NCd1d2d3d4d5_none_no_weight", "test_sce_none_expanded", - "test_sce_none_log_prob", "test_sce_none_log_prob_expanded", - "test_sce_none_weights", + "test_sce_none_log_prob", "test_sce_none_weights_expanded", - "test_sce_none_weights_log_prob", "test_sce_none_weights_log_prob_expanded", - "test_sce_sum", + "test_sce_none_weights_log_prob", + "test_sce_none_weights", + "test_sce_none", "test_sce_sum_expanded", - "test_sce_sum_log_prob", "test_sce_sum_log_prob_expanded", + "test_sce_sum_log_prob", + "test_sce_sum", "test_shape_end_1", "test_shape_end_negative_1", - "test_shape_start_1", "test_shape_start_1_end_2", "test_shape_start_1_end_negative_1", + "test_shape_start_1", "test_shape_start_negative_1", "test_shrink_hard", "test_shrink_soft", "test_simple_rnn_batchwise", - "test_sinh", + "test_simple_rnn_defaults", + "test_simple_rnn_with_initial_bias", "test_sinh_example", - "test_size", + "test_sinh", "test_size_example", - "test_slice", + "test_size", "test_slice_default_axes", "test_slice_default_steps", "test_slice_end_out_of_bounds", - "test_slice_neg", "test_slice_neg_steps", + "test_slice_neg", "test_slice_negative_axes", "test_slice_start_out_of_bounds", - "test_softmax_axis_0_expanded", + "test_slice", "test_softmax_axis_0_expanded_ver18", - "test_softmax_axis_1_expanded", + "test_softmax_axis_0_expanded", "test_softmax_axis_1_expanded_ver18", - "test_softmax_axis_2_expanded", + "test_softmax_axis_1_expanded", "test_softmax_axis_2_expanded_ver18", - "test_softmax_default_axis_expanded", + "test_softmax_axis_2_expanded", "test_softmax_default_axis_expanded_ver18", - "test_softmax_example_expanded", + "test_softmax_default_axis_expanded", "test_softmax_example_expanded_ver18", - "test_softmax_large_number_expanded", + "test_softmax_example_expanded", "test_softmax_large_number_expanded_ver18", - "test_softmax_negative_axis_expanded", + "test_softmax_large_number_expanded", "test_softmax_negative_axis_expanded_ver18", - "test_softplus", + "test_softmax_negative_axis_expanded", "test_softplus_example", - "test_softsign", + "test_softplus", "test_softsign_example", - "test_spacetodepth", + "test_softsign", "test_spacetodepth_example", + "test_spacetodepth", "test_split_1d_uneven_split_opset18", "test_split_2d_uneven_split_opset18", "test_split_equal_parts_1d_opset13", "test_split_equal_parts_1d_opset18", - "test_split_equal_parts_2d", "test_split_equal_parts_2d_opset13", + "test_split_equal_parts_2d", "test_split_equal_parts_default_axis_opset13", "test_split_equal_parts_default_axis_opset18", "test_split_variable_parts_1d_opset13", @@ -652,9 +820,27 @@ "test_split_variable_parts_default_axis_opset18", "test_split_zero_size_splits_opset13", "test_split_zero_size_splits_opset18", - "test_squeeze", "test_squeeze_negative_axes", + "test_squeeze", "test_stft_with_window", + "test_stft", + "test_string_concat_broadcasting", + "test_string_concat_empty_string", + "test_string_concat_utf8", + "test_string_concat_zero_dimensional", + "test_string_concat", + "test_string_split_basic", + "test_string_split_consecutive_delimiters", + "test_string_split_empty_string_delimiter", + "test_string_split_empty_tensor", + "test_string_split_maxsplit", + "test_string_split_no_delimiter", + "test_strnormalizer_export_monday_casesensintive_lower", + "test_strnormalizer_export_monday_casesensintive_nochangecase", + "test_strnormalizer_export_monday_casesensintive_upper", + "test_strnormalizer_export_monday_empty_output", + "test_strnormalizer_export_monday_insensintive_upper_twodim", + "test_strnormalizer_nostopwords_nochangecase", "test_sub_uint8", "test_tfidfvectorizer_tf_batch_onlybigrams_skip0", "test_tfidfvectorizer_tf_batch_onlybigrams_skip5", @@ -663,41 +849,41 @@ "test_tfidfvectorizer_tf_onlybigrams_levelempty", "test_tfidfvectorizer_tf_onlybigrams_skip5", "test_tfidfvectorizer_tf_uniandbigrams_skip5", - "test_thresholdedrelu", "test_thresholdedrelu_default", "test_thresholdedrelu_example", - "test_tile", + "test_thresholdedrelu", "test_tile_precomputed", - "test_top_k", + "test_tile", "test_top_k_negative_axis", "test_top_k_smallest", - "test_training_dropout", - "test_training_dropout_default", + "test_top_k", "test_training_dropout_default_mask", + "test_training_dropout_default", "test_training_dropout_mask", - "test_training_dropout_zero_ratio", "test_training_dropout_zero_ratio_mask", - "test_tril", + "test_training_dropout_zero_ratio", + "test_training_dropout", "test_tril_neg", "test_tril_one_row_neg", "test_tril_out_neg", "test_tril_out_pos", "test_tril_pos", - "test_tril_square", "test_tril_square_neg", + "test_tril_square", "test_tril_zero", - "test_triu", + "test_tril", "test_triu_neg", "test_triu_one_row", "test_triu_out_neg_out", "test_triu_out_pos", "test_triu_pos", - "test_triu_square", "test_triu_square_neg", + "test_triu_square", "test_triu_zero", + "test_triu", "test_unique_not_sorted_without_axis", - "test_unique_sorted_with_axis", "test_unique_sorted_with_axis_3d", + "test_unique_sorted_with_axis", "test_unique_sorted_with_negative_axis", "test_unique_sorted_without_axis", "test_unsqueeze_axis_0", diff --git a/iree_tests/conftest.py b/iree_tests/conftest.py index db644e410..64772df22 100644 --- a/iree_tests/conftest.py +++ b/iree_tests/conftest.py @@ -249,7 +249,7 @@ def __init__( THIS_DIR = Path(__file__).parent REPO_ROOT = THIS_DIR.parent _iree_test_config_files = [ - REPO_ROOT / "iree_tests/configs/config_cpu.json", + REPO_ROOT / "iree_tests/configs/config_cpu_llvm_sync.json", # REPO_ROOT / "iree_tests/configs/config_gpu_vulkan.json", ] diff --git a/iree_tests/onnx/import_tests.py b/iree_tests/onnx/import_tests.py index 61d151f31..9f6b37e24 100644 --- a/iree_tests/onnx/import_tests.py +++ b/iree_tests/onnx/import_tests.py @@ -108,7 +108,7 @@ def import_onnx_files(test_dir_path, imported_dir_path): if t is None: return False input_path = (imported_dir_path / test_input.stem).with_suffix(".npy") - np.save(input_path, t, allow_pickle=False) + np.save(input_path, t) test_data_flagfile_lines.append(f"--input=@{input_path.name}\n") for i in range(len(test_outputs)): test_output = test_outputs[i] @@ -116,7 +116,7 @@ def import_onnx_files(test_dir_path, imported_dir_path): if t is None: return False output_path = (imported_dir_path / test_output.stem).with_suffix(".npy") - np.save(output_path, t, allow_pickle=False) + np.save(output_path, t) test_data_flagfile_lines.append(f"--expected_output=@{output_path.name}\n") with open(test_data_flagfile_path, "wt") as f: diff --git a/iree_tests/onnx/node/generated/test_abs/model.mlir b/iree_tests/onnx/node/generated/test_abs/model.mlir index 63840f11c..fa9c85ba3 100644 --- a/iree_tests/onnx/node/generated/test_abs/model.mlir +++ b/iree_tests/onnx/node/generated/test_abs/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_abs(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_acos/model.mlir b/iree_tests/onnx/node/generated/test_acos/model.mlir index c8fb999c1..d2f753394 100644 --- a/iree_tests/onnx/node/generated/test_acos/model.mlir +++ b/iree_tests/onnx/node/generated/test_acos/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_acos(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Acos"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Acos"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_acos_example/model.mlir b/iree_tests/onnx/node/generated/test_acos_example/model.mlir index f8d8fa778..7df5b8d0b 100644 --- a/iree_tests/onnx/node/generated/test_acos_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_acos_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_acos_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Acos"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Acos"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_acosh/model.mlir b/iree_tests/onnx/node/generated/test_acosh/model.mlir index 31e83aabe..178669ba6 100644 --- a/iree_tests/onnx/node/generated/test_acosh/model.mlir +++ b/iree_tests/onnx/node/generated/test_acosh/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_acosh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Acosh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Acosh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_acosh_example/model.mlir b/iree_tests/onnx/node/generated/test_acosh_example/model.mlir index 656a07705..36c324258 100644 --- a/iree_tests/onnx/node/generated/test_acosh_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_acosh_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_acosh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Acosh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Acosh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_adagrad/model.mlir b/iree_tests/onnx/node/generated/test_adagrad/model.mlir index 71df93f98..c338dada8 100644 --- a/iree_tests/onnx/node/generated/test_adagrad/model.mlir +++ b/iree_tests/onnx/node/generated/test_adagrad/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_adagrad(%arg0: !torch.vtensor<[],f32>, %arg1: !torch.vtensor<[],si64>, %arg2: !torch.vtensor<[1],f32>, %arg3: !torch.vtensor<[1],f32>, %arg4: !torch.vtensor<[1],f32>) -> (!torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_versions = {ai.onnx.preview.training = 1 : si64}, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.Adagrad"(%arg0, %arg1, %arg2, %arg3, %arg4) {torch.onnx.decay_factor = 1.000000e-01 : f32, torch.onnx.epsilon = 9.99999974E-6 : f32, torch.onnx.norm_coefficient = 1.000000e-03 : f32} : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> (!torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.Adagrad"(%arg0, %arg1, %arg2, %arg3, %arg4) {torch.onnx.decay_factor = 1.000000e-01 : f32, torch.onnx.epsilon = 9.99999974E-6 : f32, torch.onnx.norm_coefficient = 1.000000e-03 : f32} : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> (!torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) return %0#0, %0#1 : !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_adagrad_multiple/model.mlir b/iree_tests/onnx/node/generated/test_adagrad_multiple/model.mlir index 9aaa06d3b..8fa137c0e 100644 --- a/iree_tests/onnx/node/generated/test_adagrad_multiple/model.mlir +++ b/iree_tests/onnx/node/generated/test_adagrad_multiple/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_adagrad_multiple(%arg0: !torch.vtensor<[],f32>, %arg1: !torch.vtensor<[],si64>, %arg2: !torch.vtensor<[1],f32>, %arg3: !torch.vtensor<[2],f32>, %arg4: !torch.vtensor<[1],f32>, %arg5: !torch.vtensor<[2],f32>, %arg6: !torch.vtensor<[1],f32>, %arg7: !torch.vtensor<[2],f32>) -> (!torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_versions = {ai.onnx.preview.training = 1 : si64}, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:4 = torch.operator "onnx.Adagrad"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) {torch.onnx.decay_factor = 1.000000e-01 : f32, torch.onnx.epsilon = 9.99999974E-6 : f32, torch.onnx.norm_coefficient = 1.000000e-03 : f32} : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>) -> (!torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>) + %none = torch.constant.none + %0:4 = torch.operator "onnx.Adagrad"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) {torch.onnx.decay_factor = 1.000000e-01 : f32, torch.onnx.epsilon = 9.99999974E-6 : f32, torch.onnx.norm_coefficient = 1.000000e-03 : f32} : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>) -> (!torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>) return %0#0, %0#1, %0#2, %0#3 : !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_adam/model.mlir b/iree_tests/onnx/node/generated/test_adam/model.mlir index 97b3aabcd..1cf9dce17 100644 --- a/iree_tests/onnx/node/generated/test_adam/model.mlir +++ b/iree_tests/onnx/node/generated/test_adam/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_adam(%arg0: !torch.vtensor<[],f32>, %arg1: !torch.vtensor<[],si64>, %arg2: !torch.vtensor<[2],f32>, %arg3: !torch.vtensor<[2],f32>, %arg4: !torch.vtensor<[2],f32>, %arg5: !torch.vtensor<[2],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_versions = {ai.onnx.preview.training = 1 : si64}, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.Adam"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5) {torch.onnx.alpha = 0.949999988 : f32, torch.onnx.beta = 1.000000e-01 : f32, torch.onnx.epsilon = 1.000000e-07 : f32, torch.onnx.norm_coefficient = 1.000000e-03 : f32} : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.Adam"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5) {torch.onnx.alpha = 0.949999988 : f32, torch.onnx.beta = 1.000000e-01 : f32, torch.onnx.epsilon = 1.000000e-07 : f32, torch.onnx.norm_coefficient = 1.000000e-03 : f32} : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_adam_multiple/model.mlir b/iree_tests/onnx/node/generated/test_adam_multiple/model.mlir index 7918cd51b..87cc1e298 100644 --- a/iree_tests/onnx/node/generated/test_adam_multiple/model.mlir +++ b/iree_tests/onnx/node/generated/test_adam_multiple/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_adam_multiple(%arg0: !torch.vtensor<[],f32>, %arg1: !torch.vtensor<[],si64>, %arg2: !torch.vtensor<[1],f32>, %arg3: !torch.vtensor<[2],f32>, %arg4: !torch.vtensor<[1],f32>, %arg5: !torch.vtensor<[2],f32>, %arg6: !torch.vtensor<[1],f32>, %arg7: !torch.vtensor<[2],f32>, %arg8: !torch.vtensor<[1],f32>, %arg9: !torch.vtensor<[2],f32>) -> (!torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_versions = {ai.onnx.preview.training = 1 : si64}, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:6 = torch.operator "onnx.Adam"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7, %arg8, %arg9) {torch.onnx.alpha = 0.949999988 : f32, torch.onnx.beta = 8.500000e-01 : f32, torch.onnx.norm_coefficient = 1.000000e-03 : f32} : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>) -> (!torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>) + %none = torch.constant.none + %0:6 = torch.operator "onnx.Adam"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7, %arg8, %arg9) {torch.onnx.alpha = 0.949999988 : f32, torch.onnx.beta = 8.500000e-01 : f32, torch.onnx.norm_coefficient = 1.000000e-03 : f32} : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>) -> (!torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>) return %0#0, %0#1, %0#2, %0#3, %0#4, %0#5 : !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_add/model.mlir b/iree_tests/onnx/node/generated/test_add/model.mlir index 859a76fe2..582adb766 100644 --- a/iree_tests/onnx/node/generated/test_add/model.mlir +++ b/iree_tests/onnx/node/generated/test_add/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_add(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Add"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Add"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_add_bcast/model.mlir b/iree_tests/onnx/node/generated/test_add_bcast/model.mlir index a1c4b7f73..611c1d700 100644 --- a/iree_tests/onnx/node/generated/test_add_bcast/model.mlir +++ b/iree_tests/onnx/node/generated/test_add_bcast/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_add_bcast(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Add"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Add"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_add_uint8/model.mlir b/iree_tests/onnx/node/generated/test_add_uint8/model.mlir index 38a81e480..3b5a57fa7 100644 --- a/iree_tests/onnx/node/generated/test_add_uint8/model.mlir +++ b/iree_tests/onnx/node/generated/test_add_uint8/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_add_uint8(%arg0: !torch.vtensor<[3,4,5],ui8>, %arg1: !torch.vtensor<[3,4,5],ui8>) -> !torch.vtensor<[3,4,5],ui8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Add"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],ui8>, !torch.vtensor<[3,4,5],ui8>) -> !torch.vtensor<[3,4,5],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.Add"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],ui8>, !torch.vtensor<[3,4,5],ui8>) -> !torch.vtensor<[3,4,5],ui8> return %0 : !torch.vtensor<[3,4,5],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_affine_grid_2d/model.mlir b/iree_tests/onnx/node/generated/test_affine_grid_2d/model.mlir index 1edd3b57e..fb6739771 100644 --- a/iree_tests/onnx/node/generated/test_affine_grid_2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_affine_grid_2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_affine_grid_2d(%arg0: !torch.vtensor<[2,2,3],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,5,6,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AffineGrid"(%arg0, %arg1) {torch.onnx.align_corners = 0 : si64} : (!torch.vtensor<[2,2,3],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,5,6,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AffineGrid"(%arg0, %arg1) {torch.onnx.align_corners = 0 : si64} : (!torch.vtensor<[2,2,3],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,5,6,2],f32> return %0 : !torch.vtensor<[2,5,6,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners/model.mlir b/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners/model.mlir index 1f11ad6f1..805d642b7 100644 --- a/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners/model.mlir +++ b/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_affine_grid_2d_align_corners(%arg0: !torch.vtensor<[2,2,3],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,5,6,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AffineGrid"(%arg0, %arg1) {torch.onnx.align_corners = 1 : si64} : (!torch.vtensor<[2,2,3],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,5,6,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AffineGrid"(%arg0, %arg1) {torch.onnx.align_corners = 1 : si64} : (!torch.vtensor<[2,2,3],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,5,6,2],f32> return %0 : !torch.vtensor<[2,5,6,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/input_0.npy new file mode 100644 index 000000000..17dd7390b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/input_1.npy new file mode 100644 index 000000000..ba19e9218 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/model.mlir b/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/model.mlir new file mode 100644 index 000000000..f4cd1e546 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/model.mlir @@ -0,0 +1,140 @@ +module { + func.func @test_affine_grid_2d_align_corners_expanded(%arg0: !torch.vtensor<[2,2,3],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,5,6,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 1 : si64} : () -> !torch.vtensor<[],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 2 : si64} : () -> !torch.vtensor<[],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 0 : si64} : () -> !torch.vtensor<[],si64> + %3 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 4 : si64} : () -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [1 : si64]} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [0 : si64]} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Constant"() {torch.onnx.value_int = -1 : si64} : () -> !torch.vtensor<[],si64> + %7 = torch.operator "onnx.CastLike"(%6, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[2,2,3],f32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[2,2,3],f32>) -> !torch.vtensor<[],f32> + %9 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[2,2,3],f32>) -> !torch.vtensor<[],f32> + %10 = torch.operator "onnx.CastLike"(%1, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[2,2,3],f32>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 1 : si64} : () -> !torch.vtensor<[],si64> + %12 = torch.operator "onnx.Equal"(%11, %2) : (!torch.vtensor<[],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],i1> + %13 = torch.operator "onnx.Size"(%arg1) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %14 = torch.operator "onnx.Equal"(%13, %3) : (!torch.vtensor<[],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],i1> + %15:5 = torch.operator "onnx.If"(%14) : (!torch.vtensor<[],i1>) -> (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>) { + %63:5 = torch.operator "onnx.Split"(%arg1) {torch.onnx.num_outputs = 5 : si64} : (!torch.vtensor<[4],si64>) -> (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[0],si64>) + torch.operator_terminator %63#0, %63#1, %63#2, %63#3, %63#4 : !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[0],si64> + }, { + %63:4 = torch.operator "onnx.Split"(%arg1) {torch.onnx.num_outputs = 4 : si64} : (!torch.vtensor<[4],si64>) -> (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) + %64 = torch.operator "onnx.Identity"(%4) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + torch.operator_terminator %63#0, %63#1, %64, %63#2, %63#3 : !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64> + } + %16 = torch.operator "onnx.Concat"(%15#0, %15#1, %15#2, %15#3, %15#4) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %17 = torch.operator "onnx.If"(%14) : (!torch.vtensor<[],i1>) -> !torch.vtensor<[],f32> { + %63 = torch.operator "onnx.Identity"(%arg0) : (!torch.vtensor<[2,2,3],f32>) -> !torch.vtensor<[2,2,3],f32> + torch.operator_terminator %63 : !torch.vtensor<[2,2,3],f32> + }, { + %63 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [0 : si64, 1 : si64, 2 : si64, 0 : si64, 1 : si64, 2 : si64]} : () -> !torch.vtensor<[6],si64> + %64 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [2 : si64, 3 : si64]} : () -> !torch.vtensor<[2],si64> + %65 = torch.operator "onnx.Reshape"(%63, %64) : (!torch.vtensor<[6],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2,3],si64> + %66 = torch.operator "onnx.Concat"(%15#0, %64) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3],si64> + %67 = torch.operator "onnx.Expand"(%65, %66) : (!torch.vtensor<[2,3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[?,2,3],si64> + %68 = torch.operator "onnx.GatherElements"(%arg0, %67) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[2,2,3],f32>, !torch.vtensor<[?,2,3],si64>) -> !torch.vtensor<[?,2,3],f32> + %69:2 = torch.operator "onnx.Split"(%68) {torch.onnx.axis = 1 : si64, torch.onnx.num_outputs = 2 : si64} : (!torch.vtensor<[?,2,3],f32>) -> (!torch.vtensor<[?,1,3],f32>, !torch.vtensor<[?,1,3],f32>) + %70 = torch.operator "onnx.Squeeze"(%69#0) : (!torch.vtensor<[?,1,3],f32>) -> !torch.vtensor<[],f32> + %71 = torch.operator "onnx.Squeeze"(%69#1) : (!torch.vtensor<[?,1,3],f32>) -> !torch.vtensor<[],f32> + %72:3 = torch.operator "onnx.Split"(%70) {torch.onnx.axis = 1 : si64, torch.onnx.num_outputs = 3 : si64} : (!torch.vtensor<[],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) + %73:3 = torch.operator "onnx.Split"(%71) {torch.onnx.axis = 1 : si64, torch.onnx.num_outputs = 3 : si64} : (!torch.vtensor<[],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) + %74 = torch.operator "onnx.Shape"(%73#0) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[?],si64> + %75 = torch.operator "onnx.ConstantOfShape"(%74) : (!torch.vtensor<[?],si64>) -> !torch.vtensor<[],f32> + %76 = torch.operator "onnx.CastLike"(%75, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[2,2,3],f32>) -> !torch.vtensor<[],f32> + %77 = torch.operator "onnx.Add"(%76, %9) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %78 = torch.operator "onnx.Concat"(%72#0, %72#1, %76, %72#2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %79 = torch.operator "onnx.Concat"(%73#0, %73#1, %76, %73#2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %80 = torch.operator "onnx.Concat"(%76, %76, %77, %76) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %81 = torch.operator "onnx.Unsqueeze"(%78, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %82 = torch.operator "onnx.Unsqueeze"(%79, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %83 = torch.operator "onnx.Unsqueeze"(%80, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %84 = torch.operator "onnx.Concat"(%81, %82, %83) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %84 : !torch.vtensor<[],f32> + } + %18 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [2 : si64]} : () -> !torch.vtensor<[1],si64> + %19 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [3 : si64]} : () -> !torch.vtensor<[1],si64> + %20 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [5 : si64]} : () -> !torch.vtensor<[1],si64> + %21 = torch.operator "onnx.Slice"(%16, %18, %20) : (!torch.vtensor<[?],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %22 = torch.operator "onnx.ConstantOfShape"(%21) : (!torch.vtensor<[?],si64>) -> !torch.vtensor<[],f32> + %23 = torch.operator "onnx.CastLike"(%22, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[2,2,3],f32>) -> !torch.vtensor<[],f32> + %24 = torch.operator "onnx.Add"(%23, %9) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %25 = torch.operator "onnx.CastLike"(%15#2, %8) : (!torch.vtensor<[1],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %26 = torch.operator "onnx.CastLike"(%15#3, %8) : (!torch.vtensor<[1],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %27 = torch.operator "onnx.CastLike"(%15#4, %8) : (!torch.vtensor<[?],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %28:6 = torch.operator "onnx.If"(%12) : (!torch.vtensor<[],i1>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) { + %63 = torch.operator "onnx.Sub"(%25, %9) : (!torch.vtensor<[1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %64 = torch.operator "onnx.Sub"(%26, %9) : (!torch.vtensor<[1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %65 = torch.operator "onnx.Sub"(%27, %9) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %66 = torch.operator "onnx.Equal"(%15#2, %0) : (!torch.vtensor<[1],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[1],i1> + %67 = torch.operator "onnx.If"(%66) : (!torch.vtensor<[1],i1>) -> !torch.vtensor<[],f32> { + %73 = torch.operator "onnx.Div"(%10, %63) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + torch.operator_terminator %73 : !torch.vtensor<[1],f32> + }, { + %73 = torch.operator "onnx.Identity"(%8) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %73 : !torch.vtensor<[],f32> + } + %68 = torch.operator "onnx.Div"(%10, %64) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + %69 = torch.operator "onnx.Div"(%10, %65) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %70 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %71 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %72 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %70, %67, %71, %68, %72, %69 : !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[?],f32> + }, { + %63 = torch.operator "onnx.Div"(%10, %25) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + %64 = torch.operator "onnx.Div"(%10, %26) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + %65 = torch.operator "onnx.Div"(%10, %27) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %66 = torch.operator "onnx.Div"(%63, %10) : (!torch.vtensor<[1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %67 = torch.operator "onnx.Add"(%7, %66) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + %68 = torch.operator "onnx.Div"(%64, %10) : (!torch.vtensor<[1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %69 = torch.operator "onnx.Add"(%7, %68) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + %70 = torch.operator "onnx.Div"(%65, %10) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %71 = torch.operator "onnx.Add"(%7, %70) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + torch.operator_terminator %67, %63, %69, %64, %71, %65 : !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[?],f32>, !torch.vtensor<[?],f32> + } + %29 = torch.operator "onnx.Range"(%2, %15#4, %0) : (!torch.vtensor<[],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[?],si64> + %30 = torch.operator "onnx.CastLike"(%29, %28#5) : (!torch.vtensor<[?],si64>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %31 = torch.operator "onnx.Mul"(%30, %28#5) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %32 = torch.operator "onnx.Add"(%28#4, %31) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[],f32> + %33 = torch.operator "onnx.Range"(%2, %15#3, %0) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[?],si64> + %34 = torch.operator "onnx.CastLike"(%33, %28#3) : (!torch.vtensor<[?],si64>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[?],f32> + %35 = torch.operator "onnx.Mul"(%34, %28#3) : (!torch.vtensor<[?],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[?],f32> + %36 = torch.operator "onnx.Add"(%28#2, %35) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[],f32> + %37 = torch.operator "onnx.Range"(%2, %15#2, %0) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[?],si64> + %38 = torch.operator "onnx.CastLike"(%37, %28#1) : (!torch.vtensor<[?],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %39 = torch.operator "onnx.Mul"(%38, %28#1) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %40 = torch.operator "onnx.Add"(%28#0, %39) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %41 = torch.operator "onnx.Transpose"(%23) {torch.onnx.perm = [1 : si64, 2 : si64, 0 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %42 = torch.operator "onnx.Add"(%41, %40) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %43 = torch.operator "onnx.Transpose"(%42) {torch.onnx.perm = [2 : si64, 0 : si64, 1 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %44 = torch.operator "onnx.Transpose"(%23) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %45 = torch.operator "onnx.Add"(%44, %36) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %46 = torch.operator "onnx.Transpose"(%45) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %47 = torch.operator "onnx.Add"(%32, %23) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %48 = torch.operator "onnx.Unsqueeze"(%47, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %49 = torch.operator "onnx.Unsqueeze"(%46, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %50 = torch.operator "onnx.Unsqueeze"(%43, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %51 = torch.operator "onnx.Unsqueeze"(%24, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %52 = torch.operator "onnx.Concat"(%48, %49, %50, %51) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %53 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [-1 : si64, 4 : si64]} : () -> !torch.vtensor<[2],si64> + %54 = torch.operator "onnx.Reshape"(%52, %53) : (!torch.vtensor<[],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[?,4],f32> + %55 = torch.operator "onnx.Transpose"(%54) : (!torch.vtensor<[?,4],f32>) -> !torch.vtensor<[4,?],f32> + %56 = torch.operator "onnx.CastLike"(%55, %17) : (!torch.vtensor<[4,?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[4,?],f32> + %57 = torch.operator "onnx.MatMul"(%17, %56) : (!torch.vtensor<[],f32>, !torch.vtensor<[4,?],f32>) -> !torch.vtensor<[],f32> + %58 = torch.operator "onnx.Transpose"(%57) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %59 = torch.operator "onnx.Concat"(%15#0, %15#2, %15#3, %15#4, %19) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %60 = torch.operator "onnx.Reshape"(%58, %59) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[],f32> + %61 = torch.operator "onnx.CastLike"(%60, %17) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %62 = torch.operator "onnx.If"(%14) : (!torch.vtensor<[],i1>) -> !torch.vtensor<[2,5,6,2],f32> { + %63 = torch.operator "onnx.Identity"(%61) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %63 : !torch.vtensor<[],f32> + }, { + %63 = torch.operator "onnx.Squeeze"(%61, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %64 = torch.operator "onnx.Slice"(%63, %5, %18, %19) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + torch.operator_terminator %64 : !torch.vtensor<[],f32> + } + return %62 : !torch.vtensor<[2,5,6,2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/output_0.npy new file mode 100644 index 000000000..a0998ccb6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_affine_grid_2d_align_corners_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/input_0.npy new file mode 100644 index 000000000..17dd7390b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/input_1.npy new file mode 100644 index 000000000..ba19e9218 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/model.mlir b/iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/model.mlir new file mode 100644 index 000000000..d26ea4829 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/model.mlir @@ -0,0 +1,140 @@ +module { + func.func @test_affine_grid_2d_expanded(%arg0: !torch.vtensor<[2,2,3],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,5,6,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 1 : si64} : () -> !torch.vtensor<[],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 2 : si64} : () -> !torch.vtensor<[],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 0 : si64} : () -> !torch.vtensor<[],si64> + %3 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 4 : si64} : () -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [1 : si64]} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [0 : si64]} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Constant"() {torch.onnx.value_int = -1 : si64} : () -> !torch.vtensor<[],si64> + %7 = torch.operator "onnx.CastLike"(%6, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[2,2,3],f32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[2,2,3],f32>) -> !torch.vtensor<[],f32> + %9 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[2,2,3],f32>) -> !torch.vtensor<[],f32> + %10 = torch.operator "onnx.CastLike"(%1, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[2,2,3],f32>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 0 : si64} : () -> !torch.vtensor<[],si64> + %12 = torch.operator "onnx.Equal"(%11, %2) : (!torch.vtensor<[],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],i1> + %13 = torch.operator "onnx.Size"(%arg1) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %14 = torch.operator "onnx.Equal"(%13, %3) : (!torch.vtensor<[],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],i1> + %15:5 = torch.operator "onnx.If"(%14) : (!torch.vtensor<[],i1>) -> (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>) { + %63:5 = torch.operator "onnx.Split"(%arg1) {torch.onnx.num_outputs = 5 : si64} : (!torch.vtensor<[4],si64>) -> (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[0],si64>) + torch.operator_terminator %63#0, %63#1, %63#2, %63#3, %63#4 : !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[0],si64> + }, { + %63:4 = torch.operator "onnx.Split"(%arg1) {torch.onnx.num_outputs = 4 : si64} : (!torch.vtensor<[4],si64>) -> (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) + %64 = torch.operator "onnx.Identity"(%4) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + torch.operator_terminator %63#0, %63#1, %64, %63#2, %63#3 : !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64> + } + %16 = torch.operator "onnx.Concat"(%15#0, %15#1, %15#2, %15#3, %15#4) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %17 = torch.operator "onnx.If"(%14) : (!torch.vtensor<[],i1>) -> !torch.vtensor<[],f32> { + %63 = torch.operator "onnx.Identity"(%arg0) : (!torch.vtensor<[2,2,3],f32>) -> !torch.vtensor<[2,2,3],f32> + torch.operator_terminator %63 : !torch.vtensor<[2,2,3],f32> + }, { + %63 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [0 : si64, 1 : si64, 2 : si64, 0 : si64, 1 : si64, 2 : si64]} : () -> !torch.vtensor<[6],si64> + %64 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [2 : si64, 3 : si64]} : () -> !torch.vtensor<[2],si64> + %65 = torch.operator "onnx.Reshape"(%63, %64) : (!torch.vtensor<[6],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2,3],si64> + %66 = torch.operator "onnx.Concat"(%15#0, %64) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3],si64> + %67 = torch.operator "onnx.Expand"(%65, %66) : (!torch.vtensor<[2,3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[?,2,3],si64> + %68 = torch.operator "onnx.GatherElements"(%arg0, %67) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[2,2,3],f32>, !torch.vtensor<[?,2,3],si64>) -> !torch.vtensor<[?,2,3],f32> + %69:2 = torch.operator "onnx.Split"(%68) {torch.onnx.axis = 1 : si64, torch.onnx.num_outputs = 2 : si64} : (!torch.vtensor<[?,2,3],f32>) -> (!torch.vtensor<[?,1,3],f32>, !torch.vtensor<[?,1,3],f32>) + %70 = torch.operator "onnx.Squeeze"(%69#0) : (!torch.vtensor<[?,1,3],f32>) -> !torch.vtensor<[],f32> + %71 = torch.operator "onnx.Squeeze"(%69#1) : (!torch.vtensor<[?,1,3],f32>) -> !torch.vtensor<[],f32> + %72:3 = torch.operator "onnx.Split"(%70) {torch.onnx.axis = 1 : si64, torch.onnx.num_outputs = 3 : si64} : (!torch.vtensor<[],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) + %73:3 = torch.operator "onnx.Split"(%71) {torch.onnx.axis = 1 : si64, torch.onnx.num_outputs = 3 : si64} : (!torch.vtensor<[],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) + %74 = torch.operator "onnx.Shape"(%73#0) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[?],si64> + %75 = torch.operator "onnx.ConstantOfShape"(%74) : (!torch.vtensor<[?],si64>) -> !torch.vtensor<[],f32> + %76 = torch.operator "onnx.CastLike"(%75, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[2,2,3],f32>) -> !torch.vtensor<[],f32> + %77 = torch.operator "onnx.Add"(%76, %9) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %78 = torch.operator "onnx.Concat"(%72#0, %72#1, %76, %72#2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %79 = torch.operator "onnx.Concat"(%73#0, %73#1, %76, %73#2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %80 = torch.operator "onnx.Concat"(%76, %76, %77, %76) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %81 = torch.operator "onnx.Unsqueeze"(%78, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %82 = torch.operator "onnx.Unsqueeze"(%79, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %83 = torch.operator "onnx.Unsqueeze"(%80, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %84 = torch.operator "onnx.Concat"(%81, %82, %83) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %84 : !torch.vtensor<[],f32> + } + %18 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [2 : si64]} : () -> !torch.vtensor<[1],si64> + %19 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [3 : si64]} : () -> !torch.vtensor<[1],si64> + %20 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [5 : si64]} : () -> !torch.vtensor<[1],si64> + %21 = torch.operator "onnx.Slice"(%16, %18, %20) : (!torch.vtensor<[?],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %22 = torch.operator "onnx.ConstantOfShape"(%21) : (!torch.vtensor<[?],si64>) -> !torch.vtensor<[],f32> + %23 = torch.operator "onnx.CastLike"(%22, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[2,2,3],f32>) -> !torch.vtensor<[],f32> + %24 = torch.operator "onnx.Add"(%23, %9) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %25 = torch.operator "onnx.CastLike"(%15#2, %8) : (!torch.vtensor<[1],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %26 = torch.operator "onnx.CastLike"(%15#3, %8) : (!torch.vtensor<[1],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %27 = torch.operator "onnx.CastLike"(%15#4, %8) : (!torch.vtensor<[?],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %28:6 = torch.operator "onnx.If"(%12) : (!torch.vtensor<[],i1>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) { + %63 = torch.operator "onnx.Sub"(%25, %9) : (!torch.vtensor<[1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %64 = torch.operator "onnx.Sub"(%26, %9) : (!torch.vtensor<[1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %65 = torch.operator "onnx.Sub"(%27, %9) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %66 = torch.operator "onnx.Equal"(%15#2, %0) : (!torch.vtensor<[1],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[1],i1> + %67 = torch.operator "onnx.If"(%66) : (!torch.vtensor<[1],i1>) -> !torch.vtensor<[],f32> { + %73 = torch.operator "onnx.Div"(%10, %63) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + torch.operator_terminator %73 : !torch.vtensor<[1],f32> + }, { + %73 = torch.operator "onnx.Identity"(%8) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %73 : !torch.vtensor<[],f32> + } + %68 = torch.operator "onnx.Div"(%10, %64) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + %69 = torch.operator "onnx.Div"(%10, %65) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %70 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %71 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %72 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %70, %67, %71, %68, %72, %69 : !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[?],f32> + }, { + %63 = torch.operator "onnx.Div"(%10, %25) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + %64 = torch.operator "onnx.Div"(%10, %26) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + %65 = torch.operator "onnx.Div"(%10, %27) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %66 = torch.operator "onnx.Div"(%63, %10) : (!torch.vtensor<[1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %67 = torch.operator "onnx.Add"(%7, %66) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + %68 = torch.operator "onnx.Div"(%64, %10) : (!torch.vtensor<[1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %69 = torch.operator "onnx.Add"(%7, %68) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + %70 = torch.operator "onnx.Div"(%65, %10) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %71 = torch.operator "onnx.Add"(%7, %70) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + torch.operator_terminator %67, %63, %69, %64, %71, %65 : !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[?],f32>, !torch.vtensor<[?],f32> + } + %29 = torch.operator "onnx.Range"(%2, %15#4, %0) : (!torch.vtensor<[],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[?],si64> + %30 = torch.operator "onnx.CastLike"(%29, %28#5) : (!torch.vtensor<[?],si64>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %31 = torch.operator "onnx.Mul"(%30, %28#5) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %32 = torch.operator "onnx.Add"(%28#4, %31) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[],f32> + %33 = torch.operator "onnx.Range"(%2, %15#3, %0) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[?],si64> + %34 = torch.operator "onnx.CastLike"(%33, %28#3) : (!torch.vtensor<[?],si64>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[?],f32> + %35 = torch.operator "onnx.Mul"(%34, %28#3) : (!torch.vtensor<[?],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[?],f32> + %36 = torch.operator "onnx.Add"(%28#2, %35) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[],f32> + %37 = torch.operator "onnx.Range"(%2, %15#2, %0) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[?],si64> + %38 = torch.operator "onnx.CastLike"(%37, %28#1) : (!torch.vtensor<[?],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %39 = torch.operator "onnx.Mul"(%38, %28#1) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %40 = torch.operator "onnx.Add"(%28#0, %39) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %41 = torch.operator "onnx.Transpose"(%23) {torch.onnx.perm = [1 : si64, 2 : si64, 0 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %42 = torch.operator "onnx.Add"(%41, %40) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %43 = torch.operator "onnx.Transpose"(%42) {torch.onnx.perm = [2 : si64, 0 : si64, 1 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %44 = torch.operator "onnx.Transpose"(%23) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %45 = torch.operator "onnx.Add"(%44, %36) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %46 = torch.operator "onnx.Transpose"(%45) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %47 = torch.operator "onnx.Add"(%32, %23) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %48 = torch.operator "onnx.Unsqueeze"(%47, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %49 = torch.operator "onnx.Unsqueeze"(%46, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %50 = torch.operator "onnx.Unsqueeze"(%43, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %51 = torch.operator "onnx.Unsqueeze"(%24, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %52 = torch.operator "onnx.Concat"(%48, %49, %50, %51) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %53 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [-1 : si64, 4 : si64]} : () -> !torch.vtensor<[2],si64> + %54 = torch.operator "onnx.Reshape"(%52, %53) : (!torch.vtensor<[],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[?,4],f32> + %55 = torch.operator "onnx.Transpose"(%54) : (!torch.vtensor<[?,4],f32>) -> !torch.vtensor<[4,?],f32> + %56 = torch.operator "onnx.CastLike"(%55, %17) : (!torch.vtensor<[4,?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[4,?],f32> + %57 = torch.operator "onnx.MatMul"(%17, %56) : (!torch.vtensor<[],f32>, !torch.vtensor<[4,?],f32>) -> !torch.vtensor<[],f32> + %58 = torch.operator "onnx.Transpose"(%57) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %59 = torch.operator "onnx.Concat"(%15#0, %15#2, %15#3, %15#4, %19) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %60 = torch.operator "onnx.Reshape"(%58, %59) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[],f32> + %61 = torch.operator "onnx.CastLike"(%60, %17) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %62 = torch.operator "onnx.If"(%14) : (!torch.vtensor<[],i1>) -> !torch.vtensor<[2,5,6,2],f32> { + %63 = torch.operator "onnx.Identity"(%61) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %63 : !torch.vtensor<[],f32> + }, { + %63 = torch.operator "onnx.Squeeze"(%61, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %64 = torch.operator "onnx.Slice"(%63, %5, %18, %19) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + torch.operator_terminator %64 : !torch.vtensor<[],f32> + } + return %62 : !torch.vtensor<[2,5,6,2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/output_0.npy new file mode 100644 index 000000000..4f070f1ab Binary files /dev/null and b/iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_affine_grid_2d_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_affine_grid_3d/model.mlir b/iree_tests/onnx/node/generated/test_affine_grid_3d/model.mlir index 9a828bdd1..b338d9c09 100644 --- a/iree_tests/onnx/node/generated/test_affine_grid_3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_affine_grid_3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_affine_grid_3d(%arg0: !torch.vtensor<[2,3,4],f32>, %arg1: !torch.vtensor<[5],si64>) -> !torch.vtensor<[2,4,5,6,3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AffineGrid"(%arg0, %arg1) {torch.onnx.align_corners = 0 : si64} : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[5],si64>) -> !torch.vtensor<[2,4,5,6,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AffineGrid"(%arg0, %arg1) {torch.onnx.align_corners = 0 : si64} : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[5],si64>) -> !torch.vtensor<[2,4,5,6,3],f32> return %0 : !torch.vtensor<[2,4,5,6,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners/model.mlir b/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners/model.mlir index fb4c87ca2..9a54ccb99 100644 --- a/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners/model.mlir +++ b/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_affine_grid_3d_align_corners(%arg0: !torch.vtensor<[2,3,4],f32>, %arg1: !torch.vtensor<[5],si64>) -> !torch.vtensor<[2,4,5,6,3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AffineGrid"(%arg0, %arg1) {torch.onnx.align_corners = 1 : si64} : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[5],si64>) -> !torch.vtensor<[2,4,5,6,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AffineGrid"(%arg0, %arg1) {torch.onnx.align_corners = 1 : si64} : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[5],si64>) -> !torch.vtensor<[2,4,5,6,3],f32> return %0 : !torch.vtensor<[2,4,5,6,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/input_0.npy new file mode 100644 index 000000000..285919d9a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/input_1.npy new file mode 100644 index 000000000..7d2f170fb Binary files /dev/null and b/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/model.mlir b/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/model.mlir new file mode 100644 index 000000000..d9c2a31b1 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/model.mlir @@ -0,0 +1,140 @@ +module { + func.func @test_affine_grid_3d_align_corners_expanded(%arg0: !torch.vtensor<[2,3,4],f32>, %arg1: !torch.vtensor<[5],si64>) -> !torch.vtensor<[2,4,5,6,3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 1 : si64} : () -> !torch.vtensor<[],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 2 : si64} : () -> !torch.vtensor<[],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 0 : si64} : () -> !torch.vtensor<[],si64> + %3 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 4 : si64} : () -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [1 : si64]} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [0 : si64]} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Constant"() {torch.onnx.value_int = -1 : si64} : () -> !torch.vtensor<[],si64> + %7 = torch.operator "onnx.CastLike"(%6, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[],f32> + %9 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[],f32> + %10 = torch.operator "onnx.CastLike"(%1, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 1 : si64} : () -> !torch.vtensor<[],si64> + %12 = torch.operator "onnx.Equal"(%11, %2) : (!torch.vtensor<[],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],i1> + %13 = torch.operator "onnx.Size"(%arg1) : (!torch.vtensor<[5],si64>) -> !torch.vtensor<[],si64> + %14 = torch.operator "onnx.Equal"(%13, %3) : (!torch.vtensor<[],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],i1> + %15:5 = torch.operator "onnx.If"(%14) : (!torch.vtensor<[],i1>) -> (!torch.vtensor<[?],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[?],si64>) { + %63:5 = torch.operator "onnx.Split"(%arg1) {torch.onnx.num_outputs = 5 : si64} : (!torch.vtensor<[5],si64>) -> (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) + torch.operator_terminator %63#0, %63#1, %63#2, %63#3, %63#4 : !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64> + }, { + %63:4 = torch.operator "onnx.Split"(%arg1) {torch.onnx.num_outputs = 4 : si64} : (!torch.vtensor<[5],si64>) -> (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>, !torch.vtensor<[?],si64>) + %64 = torch.operator "onnx.Identity"(%4) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + torch.operator_terminator %63#0, %63#1, %64, %63#2, %63#3 : !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[2],si64>, !torch.vtensor<[?],si64> + } + %16 = torch.operator "onnx.Concat"(%15#0, %15#1, %15#2, %15#3, %15#4) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[?],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %17 = torch.operator "onnx.If"(%14) : (!torch.vtensor<[],i1>) -> !torch.vtensor<[],f32> { + %63 = torch.operator "onnx.Identity"(%arg0) : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,4],f32> + torch.operator_terminator %63 : !torch.vtensor<[2,3,4],f32> + }, { + %63 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [0 : si64, 1 : si64, 2 : si64, 0 : si64, 1 : si64, 2 : si64]} : () -> !torch.vtensor<[6],si64> + %64 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [2 : si64, 3 : si64]} : () -> !torch.vtensor<[2],si64> + %65 = torch.operator "onnx.Reshape"(%63, %64) : (!torch.vtensor<[6],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2,3],si64> + %66 = torch.operator "onnx.Concat"(%15#0, %64) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[?],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[?],si64> + %67 = torch.operator "onnx.Expand"(%65, %66) : (!torch.vtensor<[2,3],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[],si64> + %68 = torch.operator "onnx.GatherElements"(%arg0, %67) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %69:2 = torch.operator "onnx.Split"(%68) {torch.onnx.axis = 1 : si64, torch.onnx.num_outputs = 2 : si64} : (!torch.vtensor<[],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) + %70 = torch.operator "onnx.Squeeze"(%69#0) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %71 = torch.operator "onnx.Squeeze"(%69#1) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %72:3 = torch.operator "onnx.Split"(%70) {torch.onnx.axis = 1 : si64, torch.onnx.num_outputs = 3 : si64} : (!torch.vtensor<[],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) + %73:3 = torch.operator "onnx.Split"(%71) {torch.onnx.axis = 1 : si64, torch.onnx.num_outputs = 3 : si64} : (!torch.vtensor<[],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) + %74 = torch.operator "onnx.Shape"(%73#0) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[?],si64> + %75 = torch.operator "onnx.ConstantOfShape"(%74) : (!torch.vtensor<[?],si64>) -> !torch.vtensor<[],f32> + %76 = torch.operator "onnx.CastLike"(%75, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[],f32> + %77 = torch.operator "onnx.Add"(%76, %9) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %78 = torch.operator "onnx.Concat"(%72#0, %72#1, %76, %72#2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %79 = torch.operator "onnx.Concat"(%73#0, %73#1, %76, %73#2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %80 = torch.operator "onnx.Concat"(%76, %76, %77, %76) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %81 = torch.operator "onnx.Unsqueeze"(%78, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %82 = torch.operator "onnx.Unsqueeze"(%79, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %83 = torch.operator "onnx.Unsqueeze"(%80, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %84 = torch.operator "onnx.Concat"(%81, %82, %83) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %84 : !torch.vtensor<[],f32> + } + %18 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [2 : si64]} : () -> !torch.vtensor<[1],si64> + %19 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [3 : si64]} : () -> !torch.vtensor<[1],si64> + %20 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [5 : si64]} : () -> !torch.vtensor<[1],si64> + %21 = torch.operator "onnx.Slice"(%16, %18, %20) : (!torch.vtensor<[?],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %22 = torch.operator "onnx.ConstantOfShape"(%21) : (!torch.vtensor<[?],si64>) -> !torch.vtensor<[],f32> + %23 = torch.operator "onnx.CastLike"(%22, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[],f32> + %24 = torch.operator "onnx.Add"(%23, %9) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %25 = torch.operator "onnx.CastLike"(%15#2, %8) : (!torch.vtensor<[1],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %26 = torch.operator "onnx.CastLike"(%15#3, %8) : (!torch.vtensor<[?],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %27 = torch.operator "onnx.CastLike"(%15#4, %8) : (!torch.vtensor<[?],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %28:6 = torch.operator "onnx.If"(%12) : (!torch.vtensor<[],i1>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[?],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) { + %63 = torch.operator "onnx.Sub"(%25, %9) : (!torch.vtensor<[1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %64 = torch.operator "onnx.Sub"(%26, %9) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %65 = torch.operator "onnx.Sub"(%27, %9) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %66 = torch.operator "onnx.Equal"(%15#2, %0) : (!torch.vtensor<[1],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[1],i1> + %67 = torch.operator "onnx.If"(%66) : (!torch.vtensor<[1],i1>) -> !torch.vtensor<[],f32> { + %73 = torch.operator "onnx.Div"(%10, %63) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + torch.operator_terminator %73 : !torch.vtensor<[1],f32> + }, { + %73 = torch.operator "onnx.Identity"(%8) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %73 : !torch.vtensor<[],f32> + } + %68 = torch.operator "onnx.Div"(%10, %64) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %69 = torch.operator "onnx.Div"(%10, %65) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %70 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %71 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %72 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %70, %67, %71, %68, %72, %69 : !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[?],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[?],f32> + }, { + %63 = torch.operator "onnx.Div"(%10, %25) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + %64 = torch.operator "onnx.Div"(%10, %26) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %65 = torch.operator "onnx.Div"(%10, %27) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %66 = torch.operator "onnx.Div"(%63, %10) : (!torch.vtensor<[1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %67 = torch.operator "onnx.Add"(%7, %66) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + %68 = torch.operator "onnx.Div"(%64, %10) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %69 = torch.operator "onnx.Add"(%7, %68) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %70 = torch.operator "onnx.Div"(%65, %10) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %71 = torch.operator "onnx.Add"(%7, %70) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + torch.operator_terminator %67, %63, %69, %64, %71, %65 : !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>, !torch.vtensor<[?],f32> + } + %29 = torch.operator "onnx.Range"(%2, %15#4, %0) : (!torch.vtensor<[],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[?],si64> + %30 = torch.operator "onnx.CastLike"(%29, %28#5) : (!torch.vtensor<[?],si64>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %31 = torch.operator "onnx.Mul"(%30, %28#5) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %32 = torch.operator "onnx.Add"(%28#4, %31) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[],f32> + %33 = torch.operator "onnx.Range"(%2, %15#3, %0) : (!torch.vtensor<[],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[?],si64> + %34 = torch.operator "onnx.CastLike"(%33, %28#3) : (!torch.vtensor<[?],si64>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %35 = torch.operator "onnx.Mul"(%34, %28#3) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %36 = torch.operator "onnx.Add"(%28#2, %35) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[],f32> + %37 = torch.operator "onnx.Range"(%2, %15#2, %0) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[?],si64> + %38 = torch.operator "onnx.CastLike"(%37, %28#1) : (!torch.vtensor<[?],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %39 = torch.operator "onnx.Mul"(%38, %28#1) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %40 = torch.operator "onnx.Add"(%28#0, %39) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %41 = torch.operator "onnx.Transpose"(%23) {torch.onnx.perm = [1 : si64, 2 : si64, 0 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %42 = torch.operator "onnx.Add"(%41, %40) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %43 = torch.operator "onnx.Transpose"(%42) {torch.onnx.perm = [2 : si64, 0 : si64, 1 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %44 = torch.operator "onnx.Transpose"(%23) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %45 = torch.operator "onnx.Add"(%44, %36) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %46 = torch.operator "onnx.Transpose"(%45) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %47 = torch.operator "onnx.Add"(%32, %23) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %48 = torch.operator "onnx.Unsqueeze"(%47, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %49 = torch.operator "onnx.Unsqueeze"(%46, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %50 = torch.operator "onnx.Unsqueeze"(%43, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %51 = torch.operator "onnx.Unsqueeze"(%24, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %52 = torch.operator "onnx.Concat"(%48, %49, %50, %51) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %53 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [-1 : si64, 4 : si64]} : () -> !torch.vtensor<[2],si64> + %54 = torch.operator "onnx.Reshape"(%52, %53) : (!torch.vtensor<[],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[?,4],f32> + %55 = torch.operator "onnx.Transpose"(%54) : (!torch.vtensor<[?,4],f32>) -> !torch.vtensor<[4,?],f32> + %56 = torch.operator "onnx.CastLike"(%55, %17) : (!torch.vtensor<[4,?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[4,?],f32> + %57 = torch.operator "onnx.MatMul"(%17, %56) : (!torch.vtensor<[],f32>, !torch.vtensor<[4,?],f32>) -> !torch.vtensor<[],f32> + %58 = torch.operator "onnx.Transpose"(%57) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %59 = torch.operator "onnx.Concat"(%15#0, %15#2, %15#3, %15#4, %19) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[?],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %60 = torch.operator "onnx.Reshape"(%58, %59) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[],f32> + %61 = torch.operator "onnx.CastLike"(%60, %17) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %62 = torch.operator "onnx.If"(%14) : (!torch.vtensor<[],i1>) -> !torch.vtensor<[2,4,5,6,3],f32> { + %63 = torch.operator "onnx.Identity"(%61) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %63 : !torch.vtensor<[],f32> + }, { + %63 = torch.operator "onnx.Squeeze"(%61, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %64 = torch.operator "onnx.Slice"(%63, %5, %18, %19) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + torch.operator_terminator %64 : !torch.vtensor<[],f32> + } + return %62 : !torch.vtensor<[2,4,5,6,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/output_0.npy new file mode 100644 index 000000000..a167f5cf2 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_affine_grid_3d_align_corners_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/input_0.npy new file mode 100644 index 000000000..285919d9a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/input_1.npy new file mode 100644 index 000000000..7d2f170fb Binary files /dev/null and b/iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/model.mlir b/iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/model.mlir new file mode 100644 index 000000000..d896e40fc --- /dev/null +++ b/iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/model.mlir @@ -0,0 +1,140 @@ +module { + func.func @test_affine_grid_3d_expanded(%arg0: !torch.vtensor<[2,3,4],f32>, %arg1: !torch.vtensor<[5],si64>) -> !torch.vtensor<[2,4,5,6,3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 1 : si64} : () -> !torch.vtensor<[],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 2 : si64} : () -> !torch.vtensor<[],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 0 : si64} : () -> !torch.vtensor<[],si64> + %3 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 4 : si64} : () -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [1 : si64]} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [0 : si64]} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Constant"() {torch.onnx.value_int = -1 : si64} : () -> !torch.vtensor<[],si64> + %7 = torch.operator "onnx.CastLike"(%6, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[],f32> + %9 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[],f32> + %10 = torch.operator "onnx.CastLike"(%1, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 0 : si64} : () -> !torch.vtensor<[],si64> + %12 = torch.operator "onnx.Equal"(%11, %2) : (!torch.vtensor<[],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],i1> + %13 = torch.operator "onnx.Size"(%arg1) : (!torch.vtensor<[5],si64>) -> !torch.vtensor<[],si64> + %14 = torch.operator "onnx.Equal"(%13, %3) : (!torch.vtensor<[],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],i1> + %15:5 = torch.operator "onnx.If"(%14) : (!torch.vtensor<[],i1>) -> (!torch.vtensor<[?],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[?],si64>) { + %63:5 = torch.operator "onnx.Split"(%arg1) {torch.onnx.num_outputs = 5 : si64} : (!torch.vtensor<[5],si64>) -> (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) + torch.operator_terminator %63#0, %63#1, %63#2, %63#3, %63#4 : !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64> + }, { + %63:4 = torch.operator "onnx.Split"(%arg1) {torch.onnx.num_outputs = 4 : si64} : (!torch.vtensor<[5],si64>) -> (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>, !torch.vtensor<[?],si64>) + %64 = torch.operator "onnx.Identity"(%4) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + torch.operator_terminator %63#0, %63#1, %64, %63#2, %63#3 : !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[2],si64>, !torch.vtensor<[?],si64> + } + %16 = torch.operator "onnx.Concat"(%15#0, %15#1, %15#2, %15#3, %15#4) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[?],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %17 = torch.operator "onnx.If"(%14) : (!torch.vtensor<[],i1>) -> !torch.vtensor<[],f32> { + %63 = torch.operator "onnx.Identity"(%arg0) : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,4],f32> + torch.operator_terminator %63 : !torch.vtensor<[2,3,4],f32> + }, { + %63 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [0 : si64, 1 : si64, 2 : si64, 0 : si64, 1 : si64, 2 : si64]} : () -> !torch.vtensor<[6],si64> + %64 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [2 : si64, 3 : si64]} : () -> !torch.vtensor<[2],si64> + %65 = torch.operator "onnx.Reshape"(%63, %64) : (!torch.vtensor<[6],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2,3],si64> + %66 = torch.operator "onnx.Concat"(%15#0, %64) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[?],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[?],si64> + %67 = torch.operator "onnx.Expand"(%65, %66) : (!torch.vtensor<[2,3],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[],si64> + %68 = torch.operator "onnx.GatherElements"(%arg0, %67) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %69:2 = torch.operator "onnx.Split"(%68) {torch.onnx.axis = 1 : si64, torch.onnx.num_outputs = 2 : si64} : (!torch.vtensor<[],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) + %70 = torch.operator "onnx.Squeeze"(%69#0) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %71 = torch.operator "onnx.Squeeze"(%69#1) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %72:3 = torch.operator "onnx.Split"(%70) {torch.onnx.axis = 1 : si64, torch.onnx.num_outputs = 3 : si64} : (!torch.vtensor<[],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) + %73:3 = torch.operator "onnx.Split"(%71) {torch.onnx.axis = 1 : si64, torch.onnx.num_outputs = 3 : si64} : (!torch.vtensor<[],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) + %74 = torch.operator "onnx.Shape"(%73#0) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[?],si64> + %75 = torch.operator "onnx.ConstantOfShape"(%74) : (!torch.vtensor<[?],si64>) -> !torch.vtensor<[],f32> + %76 = torch.operator "onnx.CastLike"(%75, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[],f32> + %77 = torch.operator "onnx.Add"(%76, %9) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %78 = torch.operator "onnx.Concat"(%72#0, %72#1, %76, %72#2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %79 = torch.operator "onnx.Concat"(%73#0, %73#1, %76, %73#2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %80 = torch.operator "onnx.Concat"(%76, %76, %77, %76) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %81 = torch.operator "onnx.Unsqueeze"(%78, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %82 = torch.operator "onnx.Unsqueeze"(%79, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %83 = torch.operator "onnx.Unsqueeze"(%80, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %84 = torch.operator "onnx.Concat"(%81, %82, %83) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %84 : !torch.vtensor<[],f32> + } + %18 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [2 : si64]} : () -> !torch.vtensor<[1],si64> + %19 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [3 : si64]} : () -> !torch.vtensor<[1],si64> + %20 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [5 : si64]} : () -> !torch.vtensor<[1],si64> + %21 = torch.operator "onnx.Slice"(%16, %18, %20) : (!torch.vtensor<[?],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %22 = torch.operator "onnx.ConstantOfShape"(%21) : (!torch.vtensor<[?],si64>) -> !torch.vtensor<[],f32> + %23 = torch.operator "onnx.CastLike"(%22, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[],f32> + %24 = torch.operator "onnx.Add"(%23, %9) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %25 = torch.operator "onnx.CastLike"(%15#2, %8) : (!torch.vtensor<[1],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %26 = torch.operator "onnx.CastLike"(%15#3, %8) : (!torch.vtensor<[?],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %27 = torch.operator "onnx.CastLike"(%15#4, %8) : (!torch.vtensor<[?],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %28:6 = torch.operator "onnx.If"(%12) : (!torch.vtensor<[],i1>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[?],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) { + %63 = torch.operator "onnx.Sub"(%25, %9) : (!torch.vtensor<[1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %64 = torch.operator "onnx.Sub"(%26, %9) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %65 = torch.operator "onnx.Sub"(%27, %9) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %66 = torch.operator "onnx.Equal"(%15#2, %0) : (!torch.vtensor<[1],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[1],i1> + %67 = torch.operator "onnx.If"(%66) : (!torch.vtensor<[1],i1>) -> !torch.vtensor<[],f32> { + %73 = torch.operator "onnx.Div"(%10, %63) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + torch.operator_terminator %73 : !torch.vtensor<[1],f32> + }, { + %73 = torch.operator "onnx.Identity"(%8) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %73 : !torch.vtensor<[],f32> + } + %68 = torch.operator "onnx.Div"(%10, %64) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %69 = torch.operator "onnx.Div"(%10, %65) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %70 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %71 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %72 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %70, %67, %71, %68, %72, %69 : !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[?],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[?],f32> + }, { + %63 = torch.operator "onnx.Div"(%10, %25) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + %64 = torch.operator "onnx.Div"(%10, %26) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %65 = torch.operator "onnx.Div"(%10, %27) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %66 = torch.operator "onnx.Div"(%63, %10) : (!torch.vtensor<[1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> + %67 = torch.operator "onnx.Add"(%7, %66) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + %68 = torch.operator "onnx.Div"(%64, %10) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %69 = torch.operator "onnx.Add"(%7, %68) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %70 = torch.operator "onnx.Div"(%65, %10) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %71 = torch.operator "onnx.Add"(%7, %70) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + torch.operator_terminator %67, %63, %69, %64, %71, %65 : !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>, !torch.vtensor<[?],f32> + } + %29 = torch.operator "onnx.Range"(%2, %15#4, %0) : (!torch.vtensor<[],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[?],si64> + %30 = torch.operator "onnx.CastLike"(%29, %28#5) : (!torch.vtensor<[?],si64>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %31 = torch.operator "onnx.Mul"(%30, %28#5) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %32 = torch.operator "onnx.Add"(%28#4, %31) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[],f32> + %33 = torch.operator "onnx.Range"(%2, %15#3, %0) : (!torch.vtensor<[],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[?],si64> + %34 = torch.operator "onnx.CastLike"(%33, %28#3) : (!torch.vtensor<[?],si64>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %35 = torch.operator "onnx.Mul"(%34, %28#3) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %36 = torch.operator "onnx.Add"(%28#2, %35) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[],f32> + %37 = torch.operator "onnx.Range"(%2, %15#2, %0) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[?],si64> + %38 = torch.operator "onnx.CastLike"(%37, %28#1) : (!torch.vtensor<[?],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %39 = torch.operator "onnx.Mul"(%38, %28#1) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %40 = torch.operator "onnx.Add"(%28#0, %39) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %41 = torch.operator "onnx.Transpose"(%23) {torch.onnx.perm = [1 : si64, 2 : si64, 0 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %42 = torch.operator "onnx.Add"(%41, %40) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %43 = torch.operator "onnx.Transpose"(%42) {torch.onnx.perm = [2 : si64, 0 : si64, 1 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %44 = torch.operator "onnx.Transpose"(%23) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %45 = torch.operator "onnx.Add"(%44, %36) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %46 = torch.operator "onnx.Transpose"(%45) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %47 = torch.operator "onnx.Add"(%32, %23) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %48 = torch.operator "onnx.Unsqueeze"(%47, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %49 = torch.operator "onnx.Unsqueeze"(%46, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %50 = torch.operator "onnx.Unsqueeze"(%43, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %51 = torch.operator "onnx.Unsqueeze"(%24, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %52 = torch.operator "onnx.Concat"(%48, %49, %50, %51) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %53 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [-1 : si64, 4 : si64]} : () -> !torch.vtensor<[2],si64> + %54 = torch.operator "onnx.Reshape"(%52, %53) : (!torch.vtensor<[],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[?,4],f32> + %55 = torch.operator "onnx.Transpose"(%54) : (!torch.vtensor<[?,4],f32>) -> !torch.vtensor<[4,?],f32> + %56 = torch.operator "onnx.CastLike"(%55, %17) : (!torch.vtensor<[4,?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[4,?],f32> + %57 = torch.operator "onnx.MatMul"(%17, %56) : (!torch.vtensor<[],f32>, !torch.vtensor<[4,?],f32>) -> !torch.vtensor<[],f32> + %58 = torch.operator "onnx.Transpose"(%57) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %59 = torch.operator "onnx.Concat"(%15#0, %15#2, %15#3, %15#4, %19) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[?],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[?],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %60 = torch.operator "onnx.Reshape"(%58, %59) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[],f32> + %61 = torch.operator "onnx.CastLike"(%60, %17) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %62 = torch.operator "onnx.If"(%14) : (!torch.vtensor<[],i1>) -> !torch.vtensor<[2,4,5,6,3],f32> { + %63 = torch.operator "onnx.Identity"(%61) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %63 : !torch.vtensor<[],f32> + }, { + %63 = torch.operator "onnx.Squeeze"(%61, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %64 = torch.operator "onnx.Slice"(%63, %5, %18, %19) : (!torch.vtensor<[],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + torch.operator_terminator %64 : !torch.vtensor<[],f32> + } + return %62 : !torch.vtensor<[2,4,5,6,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/output_0.npy new file mode 100644 index 000000000..5af8e5432 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_affine_grid_3d_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_ai_onnx_ml_array_feature_extractor/model.mlir b/iree_tests/onnx/node/generated/test_ai_onnx_ml_array_feature_extractor/model.mlir index cb219c783..f706694c3 100644 --- a/iree_tests/onnx/node/generated/test_ai_onnx_ml_array_feature_extractor/model.mlir +++ b/iree_tests/onnx/node/generated/test_ai_onnx_ml_array_feature_extractor/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_ai_onnx_ml_array_feature_extractor(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_versions = {ai.onnx.ml = 1 : si64}, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArrayFeatureExtractor"(%arg0, %arg1) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ArrayFeatureExtractor"(%arg0, %arg1) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_ai_onnx_ml_binarizer/model.mlir b/iree_tests/onnx/node/generated/test_ai_onnx_ml_binarizer/model.mlir index 0bf69ad71..ec08da80b 100644 --- a/iree_tests/onnx/node/generated/test_ai_onnx_ml_binarizer/model.mlir +++ b/iree_tests/onnx/node/generated/test_ai_onnx_ml_binarizer/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_ai_onnx_ml_binarizer(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_versions = {ai.onnx.ml = 1 : si64}, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Binarizer"(%arg0) {torch.onnx.threshold = 1.000000e+00 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Binarizer"(%arg0) {torch.onnx.threshold = 1.000000e+00 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int/input_0.npy b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int/input_0.npy new file mode 100644 index 000000000..09f70f8ee Binary files /dev/null and b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int/model.mlir b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int/model.mlir new file mode 100644 index 000000000..d753b1f29 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_ai_onnx_ml_label_encoder_string_int(%arg0: !torch.vtensor<[5],!torch.str>) -> !torch.vtensor<[5],si64> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_versions = {ai.onnx.ml = 4 : si64}, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.LabelEncoder"(%arg0) {torch.onnx.default_int64 = 42 : si64, torch.onnx.keys_strings = ["a", "b", "c"], torch.onnx.values_int64s = [0 : si64, 1 : si64, 2 : si64]} : (!torch.vtensor<[5],!torch.str>) -> !torch.vtensor<[5],si64> + return %0 : !torch.vtensor<[5],si64> + } +} + diff --git a/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int/output_0.npy b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int/output_0.npy new file mode 100644 index 000000000..4e42cf6d0 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int/test_data_flags.txt b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int_no_default/input_0.npy b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int_no_default/input_0.npy new file mode 100644 index 000000000..09f70f8ee Binary files /dev/null and b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int_no_default/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int_no_default/model.mlir b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int_no_default/model.mlir new file mode 100644 index 000000000..28da12a81 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int_no_default/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_ai_onnx_ml_label_encoder_string_int_no_default(%arg0: !torch.vtensor<[5],!torch.str>) -> !torch.vtensor<[5],si64> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_versions = {ai.onnx.ml = 4 : si64}, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.LabelEncoder"(%arg0) {torch.onnx.keys_strings = ["a", "b", "c"], torch.onnx.values_int64s = [0 : si64, 1 : si64, 2 : si64]} : (!torch.vtensor<[5],!torch.str>) -> !torch.vtensor<[5],si64> + return %0 : !torch.vtensor<[5],si64> + } +} + diff --git a/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int_no_default/output_0.npy b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int_no_default/output_0.npy new file mode 100644 index 000000000..9e30e4db5 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int_no_default/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int_no_default/test_data_flags.txt b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int_no_default/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_string_int_no_default/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_tensor_value_only_mapping/input_0.npy b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_tensor_value_only_mapping/input_0.npy new file mode 100644 index 000000000..09f70f8ee Binary files /dev/null and b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_tensor_value_only_mapping/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_tensor_value_only_mapping/model.mlir b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_tensor_value_only_mapping/model.mlir new file mode 100644 index 000000000..118372391 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_tensor_value_only_mapping/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_ai_onnx_ml_label_encoder_tensor_value_only_mapping(%arg0: !torch.vtensor<[5],!torch.str>) -> !torch.vtensor<[5],si16> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_versions = {ai.onnx.ml = 4 : si64}, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.LabelEncoder"(%arg0) {torch.onnx.default_tensor = dense<42> : tensor<1xsi16>, torch.onnx.keys_strings = ["a", "b", "c"], torch.onnx.values_tensor = dense<[0, 1, 2]> : tensor<3xsi16>} : (!torch.vtensor<[5],!torch.str>) -> !torch.vtensor<[5],si16> + return %0 : !torch.vtensor<[5],si16> + } +} + diff --git a/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_tensor_value_only_mapping/output_0.npy b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_tensor_value_only_mapping/output_0.npy new file mode 100644 index 000000000..8706b7a5a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_tensor_value_only_mapping/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_tensor_value_only_mapping/test_data_flags.txt b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_tensor_value_only_mapping/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_ai_onnx_ml_label_encoder_tensor_value_only_mapping/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_and2d/model.mlir b/iree_tests/onnx/node/generated/test_and2d/model.mlir index d04c935f3..9327923db 100644 --- a/iree_tests/onnx/node/generated/test_and2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_and2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_and2d(%arg0: !torch.vtensor<[3,4],i1>, %arg1: !torch.vtensor<[3,4],i1>) -> !torch.vtensor<[3,4],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4],i1>, !torch.vtensor<[3,4],i1>) -> !torch.vtensor<[3,4],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4],i1>, !torch.vtensor<[3,4],i1>) -> !torch.vtensor<[3,4],i1> return %0 : !torch.vtensor<[3,4],i1> } } diff --git a/iree_tests/onnx/node/generated/test_and3d/model.mlir b/iree_tests/onnx/node/generated/test_and3d/model.mlir index 217c2a36f..3706d003d 100644 --- a/iree_tests/onnx/node/generated/test_and3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_and3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_and3d(%arg0: !torch.vtensor<[3,4,5],i1>, %arg1: !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_and4d/model.mlir b/iree_tests/onnx/node/generated/test_and4d/model.mlir index 386a4159f..b5b31b9e3 100644 --- a/iree_tests/onnx/node/generated/test_and4d/model.mlir +++ b/iree_tests/onnx/node/generated/test_and4d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_and4d(%arg0: !torch.vtensor<[3,4,5,6],i1>, %arg1: !torch.vtensor<[3,4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[3,4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[3,4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> return %0 : !torch.vtensor<[3,4,5,6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_and_bcast3v1d/model.mlir b/iree_tests/onnx/node/generated/test_and_bcast3v1d/model.mlir index 171f40b2f..cedb0256a 100644 --- a/iree_tests/onnx/node/generated/test_and_bcast3v1d/model.mlir +++ b/iree_tests/onnx/node/generated/test_and_bcast3v1d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_and_bcast3v1d(%arg0: !torch.vtensor<[3,4,5],i1>, %arg1: !torch.vtensor<[5],i1>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[5],i1>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[5],i1>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_and_bcast3v2d/model.mlir b/iree_tests/onnx/node/generated/test_and_bcast3v2d/model.mlir index f86929051..4d67a5700 100644 --- a/iree_tests/onnx/node/generated/test_and_bcast3v2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_and_bcast3v2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_and_bcast3v2d(%arg0: !torch.vtensor<[3,4,5],i1>, %arg1: !torch.vtensor<[4,5],i1>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[4,5],i1>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[4,5],i1>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_and_bcast4v2d/model.mlir b/iree_tests/onnx/node/generated/test_and_bcast4v2d/model.mlir index 36f8e8132..be4c6736c 100644 --- a/iree_tests/onnx/node/generated/test_and_bcast4v2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_and_bcast4v2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_and_bcast4v2d(%arg0: !torch.vtensor<[3,4,5,6],i1>, %arg1: !torch.vtensor<[5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> return %0 : !torch.vtensor<[3,4,5,6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_and_bcast4v3d/model.mlir b/iree_tests/onnx/node/generated/test_and_bcast4v3d/model.mlir index 8bbba7a0e..b4d6bc00b 100644 --- a/iree_tests/onnx/node/generated/test_and_bcast4v3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_and_bcast4v3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_and_bcast4v3d(%arg0: !torch.vtensor<[3,4,5,6],i1>, %arg1: !torch.vtensor<[4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> return %0 : !torch.vtensor<[3,4,5,6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_and_bcast4v4d/model.mlir b/iree_tests/onnx/node/generated/test_and_bcast4v4d/model.mlir index fe3f09ed3..b292e2b51 100644 --- a/iree_tests/onnx/node/generated/test_and_bcast4v4d/model.mlir +++ b/iree_tests/onnx/node/generated/test_and_bcast4v4d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_and_bcast4v4d(%arg0: !torch.vtensor<[1,4,1,6],i1>, %arg1: !torch.vtensor<[3,1,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[1,4,1,6],i1>, !torch.vtensor<[3,1,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.And"(%arg0, %arg1) : (!torch.vtensor<[1,4,1,6],i1>, !torch.vtensor<[3,1,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> return %0 : !torch.vtensor<[3,4,5,6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_argmax_default_axis_example/model.mlir b/iree_tests/onnx/node/generated/test_argmax_default_axis_example/model.mlir index fd51f9e7f..61a56f925 100644 --- a/iree_tests/onnx/node/generated/test_argmax_default_axis_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmax_default_axis_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmax_default_axis_example(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[1,2],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[1,2],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[1,2],si64> return %0 : !torch.vtensor<[1,2],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmax_default_axis_example_select_last_index/model.mlir b/iree_tests/onnx/node/generated/test_argmax_default_axis_example_select_last_index/model.mlir index 41d1b5835..e372f9768 100644 --- a/iree_tests/onnx/node/generated/test_argmax_default_axis_example_select_last_index/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmax_default_axis_example_select_last_index/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmax_default_axis_example_select_last_index(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[1,2],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[1,2],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[1,2],si64> return %0 : !torch.vtensor<[1,2],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmax_default_axis_random/model.mlir b/iree_tests/onnx/node/generated/test_argmax_default_axis_random/model.mlir index 663325017..39fa5f4ab 100644 --- a/iree_tests/onnx/node/generated/test_argmax_default_axis_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmax_default_axis_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmax_default_axis_random(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[1,3,4],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[1,3,4],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[1,3,4],si64> return %0 : !torch.vtensor<[1,3,4],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmax_default_axis_random_select_last_index/model.mlir b/iree_tests/onnx/node/generated/test_argmax_default_axis_random_select_last_index/model.mlir index 47e5c4e66..4181c8146 100644 --- a/iree_tests/onnx/node/generated/test_argmax_default_axis_random_select_last_index/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmax_default_axis_random_select_last_index/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmax_default_axis_random_select_last_index(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[1,3,4],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[1,3,4],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[1,3,4],si64> return %0 : !torch.vtensor<[1,3,4],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmax_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_argmax_keepdims_example/model.mlir index 9703d9f96..4c9d15c3a 100644 --- a/iree_tests/onnx/node/generated/test_argmax_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmax_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmax_keepdims_example(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> return %0 : !torch.vtensor<[2,1],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmax_keepdims_example_select_last_index/model.mlir b/iree_tests/onnx/node/generated/test_argmax_keepdims_example_select_last_index/model.mlir index d157d9f5a..22fad46b9 100644 --- a/iree_tests/onnx/node/generated/test_argmax_keepdims_example_select_last_index/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmax_keepdims_example_select_last_index/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmax_keepdims_example_select_last_index(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> return %0 : !torch.vtensor<[2,1],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmax_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_argmax_keepdims_random/model.mlir index 91b3d95c5..695870bfa 100644 --- a/iree_tests/onnx/node/generated/test_argmax_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmax_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmax_keepdims_random(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,1,4],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,1,4],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,1,4],si64> return %0 : !torch.vtensor<[2,1,4],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmax_keepdims_random_select_last_index/model.mlir b/iree_tests/onnx/node/generated/test_argmax_keepdims_random_select_last_index/model.mlir index 09d8b6ca5..3127da817 100644 --- a/iree_tests/onnx/node/generated/test_argmax_keepdims_random_select_last_index/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmax_keepdims_random_select_last_index/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmax_keepdims_random_select_last_index(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,1,4],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,1,4],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,1,4],si64> return %0 : !torch.vtensor<[2,1,4],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmax_negative_axis_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_argmax_negative_axis_keepdims_example/model.mlir index 51bb16fe1..ea5bf3679 100644 --- a/iree_tests/onnx/node/generated/test_argmax_negative_axis_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmax_negative_axis_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmax_negative_axis_keepdims_example(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> return %0 : !torch.vtensor<[2,1],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmax_negative_axis_keepdims_example_select_last_index/model.mlir b/iree_tests/onnx/node/generated/test_argmax_negative_axis_keepdims_example_select_last_index/model.mlir index 2814e48cd..5e2298ec9 100644 --- a/iree_tests/onnx/node/generated/test_argmax_negative_axis_keepdims_example_select_last_index/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmax_negative_axis_keepdims_example_select_last_index/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmax_negative_axis_keepdims_example_select_last_index(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> return %0 : !torch.vtensor<[2,1],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmax_negative_axis_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_argmax_negative_axis_keepdims_random/model.mlir index d07891bb2..6d25c8105 100644 --- a/iree_tests/onnx/node/generated/test_argmax_negative_axis_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmax_negative_axis_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmax_negative_axis_keepdims_random(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,1],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,1],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,1],si64> return %0 : !torch.vtensor<[2,3,1],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmax_negative_axis_keepdims_random_select_last_index/model.mlir b/iree_tests/onnx/node/generated/test_argmax_negative_axis_keepdims_random_select_last_index/model.mlir index d1b6359f2..90ba8a91b 100644 --- a/iree_tests/onnx/node/generated/test_argmax_negative_axis_keepdims_random_select_last_index/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmax_negative_axis_keepdims_random_select_last_index/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmax_negative_axis_keepdims_random_select_last_index(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,1],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,1],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,1],si64> return %0 : !torch.vtensor<[2,3,1],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmax_no_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_argmax_no_keepdims_example/model.mlir index 7b6596c88..eb6178273 100644 --- a/iree_tests/onnx/node/generated/test_argmax_no_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmax_no_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmax_no_keepdims_example(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2],si64> return %0 : !torch.vtensor<[2],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmax_no_keepdims_example_select_last_index/model.mlir b/iree_tests/onnx/node/generated/test_argmax_no_keepdims_example_select_last_index/model.mlir index e460df116..c4b7cebdd 100644 --- a/iree_tests/onnx/node/generated/test_argmax_no_keepdims_example_select_last_index/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmax_no_keepdims_example_select_last_index/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmax_no_keepdims_example_select_last_index(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 0 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 0 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2],si64> return %0 : !torch.vtensor<[2],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmax_no_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_argmax_no_keepdims_random/model.mlir index 8ae9aa679..696f7a0d8 100644 --- a/iree_tests/onnx/node/generated/test_argmax_no_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmax_no_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmax_no_keepdims_random(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,4],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,4],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,4],si64> return %0 : !torch.vtensor<[2,4],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmax_no_keepdims_random_select_last_index/model.mlir b/iree_tests/onnx/node/generated/test_argmax_no_keepdims_random_select_last_index/model.mlir index 2db7f2e15..47690039f 100644 --- a/iree_tests/onnx/node/generated/test_argmax_no_keepdims_random_select_last_index/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmax_no_keepdims_random_select_last_index/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmax_no_keepdims_random_select_last_index(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,4],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 0 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,4],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMax"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 0 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,4],si64> return %0 : !torch.vtensor<[2,4],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmin_default_axis_example/model.mlir b/iree_tests/onnx/node/generated/test_argmin_default_axis_example/model.mlir index 52afe48b8..a7fd6a385 100644 --- a/iree_tests/onnx/node/generated/test_argmin_default_axis_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmin_default_axis_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmin_default_axis_example(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[1,2],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[1,2],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[1,2],si64> return %0 : !torch.vtensor<[1,2],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmin_default_axis_example_select_last_index/model.mlir b/iree_tests/onnx/node/generated/test_argmin_default_axis_example_select_last_index/model.mlir index e34664916..7dac179b4 100644 --- a/iree_tests/onnx/node/generated/test_argmin_default_axis_example_select_last_index/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmin_default_axis_example_select_last_index/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmin_default_axis_example_select_last_index(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[1,2],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[1,2],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[1,2],si64> return %0 : !torch.vtensor<[1,2],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmin_default_axis_random/model.mlir b/iree_tests/onnx/node/generated/test_argmin_default_axis_random/model.mlir index c3d19ce96..406d9b310 100644 --- a/iree_tests/onnx/node/generated/test_argmin_default_axis_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmin_default_axis_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmin_default_axis_random(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[1,3,4],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[1,3,4],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[1,3,4],si64> return %0 : !torch.vtensor<[1,3,4],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmin_default_axis_random_select_last_index/model.mlir b/iree_tests/onnx/node/generated/test_argmin_default_axis_random_select_last_index/model.mlir index 97f14e45f..d9486a1ca 100644 --- a/iree_tests/onnx/node/generated/test_argmin_default_axis_random_select_last_index/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmin_default_axis_random_select_last_index/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmin_default_axis_random_select_last_index(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[1,3,4],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[1,3,4],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[1,3,4],si64> return %0 : !torch.vtensor<[1,3,4],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmin_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_argmin_keepdims_example/model.mlir index 90341e4b5..0c47095c1 100644 --- a/iree_tests/onnx/node/generated/test_argmin_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmin_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmin_keepdims_example(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> return %0 : !torch.vtensor<[2,1],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmin_keepdims_example_select_last_index/model.mlir b/iree_tests/onnx/node/generated/test_argmin_keepdims_example_select_last_index/model.mlir index 288d36414..36513ab58 100644 --- a/iree_tests/onnx/node/generated/test_argmin_keepdims_example_select_last_index/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmin_keepdims_example_select_last_index/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmin_keepdims_example_select_last_index(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> return %0 : !torch.vtensor<[2,1],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmin_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_argmin_keepdims_random/model.mlir index 358e98452..993b1806c 100644 --- a/iree_tests/onnx/node/generated/test_argmin_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmin_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmin_keepdims_random(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,1,4],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,1,4],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,1,4],si64> return %0 : !torch.vtensor<[2,1,4],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmin_keepdims_random_select_last_index/model.mlir b/iree_tests/onnx/node/generated/test_argmin_keepdims_random_select_last_index/model.mlir index ab91b0a31..4f3304e10 100644 --- a/iree_tests/onnx/node/generated/test_argmin_keepdims_random_select_last_index/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmin_keepdims_random_select_last_index/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmin_keepdims_random_select_last_index(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,1,4],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,1,4],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,1,4],si64> return %0 : !torch.vtensor<[2,1,4],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmin_negative_axis_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_argmin_negative_axis_keepdims_example/model.mlir index 5db58f0ed..b578ec9af 100644 --- a/iree_tests/onnx/node/generated/test_argmin_negative_axis_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmin_negative_axis_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmin_negative_axis_keepdims_example(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> return %0 : !torch.vtensor<[2,1],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmin_negative_axis_keepdims_example_select_last_index/model.mlir b/iree_tests/onnx/node/generated/test_argmin_negative_axis_keepdims_example_select_last_index/model.mlir index b3f567d80..3a90c53e5 100644 --- a/iree_tests/onnx/node/generated/test_argmin_negative_axis_keepdims_example_select_last_index/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmin_negative_axis_keepdims_example_select_last_index/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmin_negative_axis_keepdims_example_select_last_index(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,1],si64> return %0 : !torch.vtensor<[2,1],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmin_negative_axis_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_argmin_negative_axis_keepdims_random/model.mlir index 271861a5e..908eb2730 100644 --- a/iree_tests/onnx/node/generated/test_argmin_negative_axis_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmin_negative_axis_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmin_negative_axis_keepdims_random(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,1],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,1],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,1],si64> return %0 : !torch.vtensor<[2,3,1],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmin_negative_axis_keepdims_random_select_last_index/model.mlir b/iree_tests/onnx/node/generated/test_argmin_negative_axis_keepdims_random_select_last_index/model.mlir index 805fc1c2b..71b0f7a56 100644 --- a/iree_tests/onnx/node/generated/test_argmin_negative_axis_keepdims_random_select_last_index/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmin_negative_axis_keepdims_random_select_last_index/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmin_negative_axis_keepdims_random_select_last_index(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,1],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,1],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.keepdims = 1 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,1],si64> return %0 : !torch.vtensor<[2,3,1],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmin_no_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_argmin_no_keepdims_example/model.mlir index dc4e29d98..c567beb48 100644 --- a/iree_tests/onnx/node/generated/test_argmin_no_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmin_no_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmin_no_keepdims_example(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2],si64> return %0 : !torch.vtensor<[2],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmin_no_keepdims_example_select_last_index/model.mlir b/iree_tests/onnx/node/generated/test_argmin_no_keepdims_example_select_last_index/model.mlir index 89cb42f48..8b0b31104 100644 --- a/iree_tests/onnx/node/generated/test_argmin_no_keepdims_example_select_last_index/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmin_no_keepdims_example_select_last_index/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmin_no_keepdims_example_select_last_index(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 0 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 0 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2],si64> return %0 : !torch.vtensor<[2],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmin_no_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_argmin_no_keepdims_random/model.mlir index fd66e78f2..88ee5c191 100644 --- a/iree_tests/onnx/node/generated/test_argmin_no_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmin_no_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmin_no_keepdims_random(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,4],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,4],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,4],si64> return %0 : !torch.vtensor<[2,4],si64> } } diff --git a/iree_tests/onnx/node/generated/test_argmin_no_keepdims_random_select_last_index/model.mlir b/iree_tests/onnx/node/generated/test_argmin_no_keepdims_random_select_last_index/model.mlir index ae7a28f4b..ae2e43cc4 100644 --- a/iree_tests/onnx/node/generated/test_argmin_no_keepdims_random_select_last_index/model.mlir +++ b/iree_tests/onnx/node/generated/test_argmin_no_keepdims_random_select_last_index/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_argmin_no_keepdims_random_select_last_index(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,4],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 0 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,4],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.ArgMin"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.keepdims = 0 : si64, torch.onnx.select_last_index = 1 : si64} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,4],si64> return %0 : !torch.vtensor<[2,4],si64> } } diff --git a/iree_tests/onnx/node/generated/test_asin/model.mlir b/iree_tests/onnx/node/generated/test_asin/model.mlir index 41e42e0b1..b7fb6a5dd 100644 --- a/iree_tests/onnx/node/generated/test_asin/model.mlir +++ b/iree_tests/onnx/node/generated/test_asin/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_asin(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Asin"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Asin"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_asin_example/model.mlir b/iree_tests/onnx/node/generated/test_asin_example/model.mlir index dfac4baac..47896f291 100644 --- a/iree_tests/onnx/node/generated/test_asin_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_asin_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_asin_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Asin"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Asin"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_asinh/model.mlir b/iree_tests/onnx/node/generated/test_asinh/model.mlir index 64d234466..153672353 100644 --- a/iree_tests/onnx/node/generated/test_asinh/model.mlir +++ b/iree_tests/onnx/node/generated/test_asinh/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_asinh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Asinh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Asinh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_asinh_example/model.mlir b/iree_tests/onnx/node/generated/test_asinh_example/model.mlir index 57921ba84..f28c55714 100644 --- a/iree_tests/onnx/node/generated/test_asinh_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_asinh_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_asinh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Asinh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Asinh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_atan/model.mlir b/iree_tests/onnx/node/generated/test_atan/model.mlir index 463ffb0de..ea8937a1d 100644 --- a/iree_tests/onnx/node/generated/test_atan/model.mlir +++ b/iree_tests/onnx/node/generated/test_atan/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_atan(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Atan"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Atan"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_atan_example/model.mlir b/iree_tests/onnx/node/generated/test_atan_example/model.mlir index 85e820175..6efe5425e 100644 --- a/iree_tests/onnx/node/generated/test_atan_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_atan_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_atan_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Atan"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Atan"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_atanh/model.mlir b/iree_tests/onnx/node/generated/test_atanh/model.mlir index b52cfdbea..7ae12f84a 100644 --- a/iree_tests/onnx/node/generated/test_atanh/model.mlir +++ b/iree_tests/onnx/node/generated/test_atanh/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_atanh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Atanh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Atanh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_atanh_example/model.mlir b/iree_tests/onnx/node/generated/test_atanh_example/model.mlir index a1453233a..8da789a93 100644 --- a/iree_tests/onnx/node/generated/test_atanh_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_atanh_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_atanh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Atanh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Atanh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_1d_default/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_1d_default/model.mlir index 6b6711b69..fd2e1fa74 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_1d_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_1d_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_1d_default(%arg0: !torch.vtensor<[1,3,32],f32>) -> !torch.vtensor<[1,3,31],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.kernel_shape = [2 : si64]} : (!torch.vtensor<[1,3,32],f32>) -> !torch.vtensor<[1,3,31],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.kernel_shape = [2 : si64]} : (!torch.vtensor<[1,3,32],f32>) -> !torch.vtensor<[1,3,31],f32> return %0 : !torch.vtensor<[1,3,31],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_2d_ceil/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_2d_ceil/model.mlir index 06883e867..635046d22 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_2d_ceil/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_2d_ceil/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_2d_ceil(%arg0: !torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.ceil_mode = 1 : si64, torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.ceil_mode = 1 : si64, torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> return %0 : !torch.vtensor<[1,1,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_2d_default/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_2d_default/model.mlir index c5e0b9f77..a83f7383a 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_2d_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_2d_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_2d_default(%arg0: !torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,31,31],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,31,31],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,31,31],f32> return %0 : !torch.vtensor<[1,3,31,31],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_2d_dilations/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_2d_dilations/model.mlir index 05182a9eb..a9b0082b6 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_2d_dilations/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_2d_dilations/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_2d_dilations(%arg0: !torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.ceil_mode = 1 : si64, torch.onnx.dilations = [2 : si64, 2 : si64], torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.strides = [1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.ceil_mode = 1 : si64, torch.onnx.dilations = [2 : si64, 2 : si64], torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.strides = [1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> return %0 : !torch.vtensor<[1,1,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_2d_pads/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_2d_pads/model.mlir index cc36afba4..d9a7847ed 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_2d_pads/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_2d_pads/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_2d_pads(%arg0: !torch.vtensor<[1,3,28,28],f32>) -> !torch.vtensor<[1,3,30,30],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,28,28],f32>) -> !torch.vtensor<[1,3,30,30],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,28,28],f32>) -> !torch.vtensor<[1,3,30,30],f32> return %0 : !torch.vtensor<[1,3,30,30],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_2d_pads_count_include_pad/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_2d_pads_count_include_pad/model.mlir index 195cb715b..42a2c9974 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_2d_pads_count_include_pad/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_2d_pads_count_include_pad/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_2d_pads_count_include_pad(%arg0: !torch.vtensor<[1,3,28,28],f32>) -> !torch.vtensor<[1,3,30,30],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.count_include_pad = 1 : si64, torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,28,28],f32>) -> !torch.vtensor<[1,3,30,30],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.count_include_pad = 1 : si64, torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,28,28],f32>) -> !torch.vtensor<[1,3,30,30],f32> return %0 : !torch.vtensor<[1,3,30,30],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_2d_precomputed_pads/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_2d_precomputed_pads/model.mlir index 45616684a..0e1fc6a06 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_2d_precomputed_pads/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_2d_precomputed_pads/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_2d_precomputed_pads(%arg0: !torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,5,5],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,5,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,5,5],f32> return %0 : !torch.vtensor<[1,1,5,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_2d_precomputed_pads_count_include_pad/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_2d_precomputed_pads_count_include_pad/model.mlir index 6769f4f53..2abff06f6 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_2d_precomputed_pads_count_include_pad/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_2d_precomputed_pads_count_include_pad/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_2d_precomputed_pads_count_include_pad(%arg0: !torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,5,5],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.count_include_pad = 1 : si64, torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,5,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.count_include_pad = 1 : si64, torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,5,5],f32> return %0 : !torch.vtensor<[1,1,5,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_2d_precomputed_same_upper/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_2d_precomputed_same_upper/model.mlir index 76002951c..66068799d 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_2d_precomputed_same_upper/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_2d_precomputed_same_upper/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_2d_precomputed_same_upper(%arg0: !torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,3,3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.auto_pad = "SAME_UPPER", torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,3,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.auto_pad = "SAME_UPPER", torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,3,3],f32> return %0 : !torch.vtensor<[1,1,3,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_2d_precomputed_strides/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_2d_precomputed_strides/model.mlir index 24612e595..e129ad42a 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_2d_precomputed_strides/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_2d_precomputed_strides/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_2d_precomputed_strides(%arg0: !torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,2,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,2,2],f32> return %0 : !torch.vtensor<[1,1,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_2d_same_lower/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_2d_same_lower/model.mlir index 86a7646a5..2e1541bd3 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_2d_same_lower/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_2d_same_lower/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_2d_same_lower(%arg0: !torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.auto_pad = "SAME_LOWER", torch.onnx.kernel_shape = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.auto_pad = "SAME_LOWER", torch.onnx.kernel_shape = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> return %0 : !torch.vtensor<[1,3,32,32],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_2d_same_upper/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_2d_same_upper/model.mlir index 3717a411d..c9d06d65e 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_2d_same_upper/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_2d_same_upper/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_2d_same_upper(%arg0: !torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.auto_pad = "SAME_UPPER", torch.onnx.kernel_shape = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.auto_pad = "SAME_UPPER", torch.onnx.kernel_shape = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> return %0 : !torch.vtensor<[1,3,32,32],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_2d_strides/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_2d_strides/model.mlir index 44d859b00..a44d75058 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_2d_strides/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_2d_strides/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_2d_strides(%arg0: !torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,10,10],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.strides = [3 : si64, 3 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,10,10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.strides = [3 : si64, 3 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,10,10],f32> return %0 : !torch.vtensor<[1,3,10,10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_3d_default/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_3d_default/model.mlir index efad9c533..8ce55227f 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_3d_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_3d_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_3d_default(%arg0: !torch.vtensor<[1,3,32,32,32],f32>) -> !torch.vtensor<[1,3,31,31,31],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32,32],f32>) -> !torch.vtensor<[1,3,31,31,31],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32,32],f32>) -> !torch.vtensor<[1,3,31,31,31],f32> return %0 : !torch.vtensor<[1,3,31,31,31],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_large_count_include_pad_is_0_ceil_mode_is_False/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_large_count_include_pad_is_0_ceil_mode_is_False/model.mlir index a5141357e..49ec1f9b5 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_large_count_include_pad_is_0_ceil_mode_is_False/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_large_count_include_pad_is_0_ceil_mode_is_False/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_3d_dilations_large_count_include_pad_is_0_ceil_mode_is_False(%arg0: !torch.vtensor<[1,1,32,32,32],f32>) -> !torch.vtensor<[1,1,8,8,8],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.ceil_mode = 0 : si64, torch.onnx.count_include_pad = 0 : si64, torch.onnx.dilations = [2 : si64, 2 : si64, 2 : si64], torch.onnx.kernel_shape = [5 : si64, 5 : si64, 5 : si64], torch.onnx.strides = [3 : si64, 3 : si64, 3 : si64]} : (!torch.vtensor<[1,1,32,32,32],f32>) -> !torch.vtensor<[1,1,8,8,8],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.ceil_mode = 0 : si64, torch.onnx.count_include_pad = 0 : si64, torch.onnx.dilations = [2 : si64, 2 : si64, 2 : si64], torch.onnx.kernel_shape = [5 : si64, 5 : si64, 5 : si64], torch.onnx.strides = [3 : si64, 3 : si64, 3 : si64]} : (!torch.vtensor<[1,1,32,32,32],f32>) -> !torch.vtensor<[1,1,8,8,8],f32> return %0 : !torch.vtensor<[1,1,8,8,8],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_large_count_include_pad_is_0_ceil_mode_is_True/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_large_count_include_pad_is_0_ceil_mode_is_True/model.mlir index 070f0dec4..b6dd70408 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_large_count_include_pad_is_0_ceil_mode_is_True/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_large_count_include_pad_is_0_ceil_mode_is_True/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_3d_dilations_large_count_include_pad_is_0_ceil_mode_is_True(%arg0: !torch.vtensor<[1,1,32,32,32],f32>) -> !torch.vtensor<[1,1,9,9,9],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.ceil_mode = 1 : si64, torch.onnx.count_include_pad = 0 : si64, torch.onnx.dilations = [2 : si64, 2 : si64, 2 : si64], torch.onnx.kernel_shape = [5 : si64, 5 : si64, 5 : si64], torch.onnx.strides = [3 : si64, 3 : si64, 3 : si64]} : (!torch.vtensor<[1,1,32,32,32],f32>) -> !torch.vtensor<[1,1,9,9,9],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.ceil_mode = 1 : si64, torch.onnx.count_include_pad = 0 : si64, torch.onnx.dilations = [2 : si64, 2 : si64, 2 : si64], torch.onnx.kernel_shape = [5 : si64, 5 : si64, 5 : si64], torch.onnx.strides = [3 : si64, 3 : si64, 3 : si64]} : (!torch.vtensor<[1,1,32,32,32],f32>) -> !torch.vtensor<[1,1,9,9,9],f32> return %0 : !torch.vtensor<[1,1,9,9,9],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_large_count_include_pad_is_1_ceil_mode_is_False/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_large_count_include_pad_is_1_ceil_mode_is_False/model.mlir index af7ef8853..ea312821f 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_large_count_include_pad_is_1_ceil_mode_is_False/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_large_count_include_pad_is_1_ceil_mode_is_False/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_3d_dilations_large_count_include_pad_is_1_ceil_mode_is_False(%arg0: !torch.vtensor<[1,1,32,32,32],f32>) -> !torch.vtensor<[1,1,8,8,8],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.ceil_mode = 0 : si64, torch.onnx.count_include_pad = 1 : si64, torch.onnx.dilations = [2 : si64, 2 : si64, 2 : si64], torch.onnx.kernel_shape = [5 : si64, 5 : si64, 5 : si64], torch.onnx.strides = [3 : si64, 3 : si64, 3 : si64]} : (!torch.vtensor<[1,1,32,32,32],f32>) -> !torch.vtensor<[1,1,8,8,8],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.ceil_mode = 0 : si64, torch.onnx.count_include_pad = 1 : si64, torch.onnx.dilations = [2 : si64, 2 : si64, 2 : si64], torch.onnx.kernel_shape = [5 : si64, 5 : si64, 5 : si64], torch.onnx.strides = [3 : si64, 3 : si64, 3 : si64]} : (!torch.vtensor<[1,1,32,32,32],f32>) -> !torch.vtensor<[1,1,8,8,8],f32> return %0 : !torch.vtensor<[1,1,8,8,8],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_large_count_include_pad_is_1_ceil_mode_is_True/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_large_count_include_pad_is_1_ceil_mode_is_True/model.mlir index e41f3c5e6..3ecc22fdf 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_large_count_include_pad_is_1_ceil_mode_is_True/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_large_count_include_pad_is_1_ceil_mode_is_True/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_3d_dilations_large_count_include_pad_is_1_ceil_mode_is_True(%arg0: !torch.vtensor<[1,1,32,32,32],f32>) -> !torch.vtensor<[1,1,9,9,9],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.ceil_mode = 1 : si64, torch.onnx.count_include_pad = 1 : si64, torch.onnx.dilations = [2 : si64, 2 : si64, 2 : si64], torch.onnx.kernel_shape = [5 : si64, 5 : si64, 5 : si64], torch.onnx.strides = [3 : si64, 3 : si64, 3 : si64]} : (!torch.vtensor<[1,1,32,32,32],f32>) -> !torch.vtensor<[1,1,9,9,9],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.ceil_mode = 1 : si64, torch.onnx.count_include_pad = 1 : si64, torch.onnx.dilations = [2 : si64, 2 : si64, 2 : si64], torch.onnx.kernel_shape = [5 : si64, 5 : si64, 5 : si64], torch.onnx.strides = [3 : si64, 3 : si64, 3 : si64]} : (!torch.vtensor<[1,1,32,32,32],f32>) -> !torch.vtensor<[1,1,9,9,9],f32> return %0 : !torch.vtensor<[1,1,9,9,9],f32> } } diff --git a/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_small/model.mlir b/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_small/model.mlir index 31b9e3749..4b403c33a 100644 --- a/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_small/model.mlir +++ b/iree_tests/onnx/node/generated/test_averagepool_3d_dilations_small/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_averagepool_3d_dilations_small(%arg0: !torch.vtensor<[1,1,4,4,4],f32>) -> !torch.vtensor<[1,1,2,2,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.ceil_mode = 1 : si64, torch.onnx.dilations = [2 : si64, 2 : si64, 2 : si64], torch.onnx.kernel_shape = [2 : si64, 2 : si64, 2 : si64], torch.onnx.strides = [1 : si64, 1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,4,4,4],f32>) -> !torch.vtensor<[1,1,2,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.AveragePool"(%arg0) {torch.onnx.ceil_mode = 1 : si64, torch.onnx.dilations = [2 : si64, 2 : si64, 2 : si64], torch.onnx.kernel_shape = [2 : si64, 2 : si64, 2 : si64], torch.onnx.strides = [1 : si64, 1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,4,4,4],f32>) -> !torch.vtensor<[1,1,2,2,2],f32> return %0 : !torch.vtensor<[1,1,2,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_basic_conv_with_padding/model.mlir b/iree_tests/onnx/node/generated/test_basic_conv_with_padding/model.mlir index 1e0e1c51f..29e904ae0 100644 --- a/iree_tests/onnx/node/generated/test_basic_conv_with_padding/model.mlir +++ b/iree_tests/onnx/node/generated/test_basic_conv_with_padding/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_basic_conv_with_padding(%arg0: !torch.vtensor<[1,1,5,5],f32>, %arg1: !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,5,5],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Conv"(%arg0, %arg1) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.pads = [1 : si64, 1 : si64, 1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,5,5],f32>, !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,5,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Conv"(%arg0, %arg1) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.pads = [1 : si64, 1 : si64, 1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,5,5],f32>, !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,5,5],f32> return %0 : !torch.vtensor<[1,1,5,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_basic_conv_without_padding/model.mlir b/iree_tests/onnx/node/generated/test_basic_conv_without_padding/model.mlir index 66997062e..bbb7f1f46 100644 --- a/iree_tests/onnx/node/generated/test_basic_conv_without_padding/model.mlir +++ b/iree_tests/onnx/node/generated/test_basic_conv_without_padding/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_basic_conv_without_padding(%arg0: !torch.vtensor<[1,1,5,5],f32>, %arg1: !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,3,3],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Conv"(%arg0, %arg1) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.pads = [0 : si64, 0 : si64, 0 : si64, 0 : si64]} : (!torch.vtensor<[1,1,5,5],f32>, !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,3,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Conv"(%arg0, %arg1) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.pads = [0 : si64, 0 : si64, 0 : si64, 0 : si64]} : (!torch.vtensor<[1,1,5,5],f32>, !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,3,3],f32> return %0 : !torch.vtensor<[1,1,3,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_basic_deform_conv_with_padding/model.mlir b/iree_tests/onnx/node/generated/test_basic_deform_conv_with_padding/model.mlir index 70ab84f06..c173e5370 100644 --- a/iree_tests/onnx/node/generated/test_basic_deform_conv_with_padding/model.mlir +++ b/iree_tests/onnx/node/generated/test_basic_deform_conv_with_padding/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_basic_deform_conv_with_padding(%arg0: !torch.vtensor<[1,1,3,3],f32>, %arg1: !torch.vtensor<[1,1,2,2],f32>, %arg2: !torch.vtensor<[1,8,4,4],f32>) -> !torch.vtensor<[1,1,4,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.DeformConv"(%arg0, %arg1, %arg2) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.pads = [1 : si64, 1 : si64, 1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,1,2,2],f32>, !torch.vtensor<[1,8,4,4],f32>) -> !torch.vtensor<[1,1,4,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.DeformConv"(%arg0, %arg1, %arg2) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.pads = [1 : si64, 1 : si64, 1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,1,2,2],f32>, !torch.vtensor<[1,8,4,4],f32>) -> !torch.vtensor<[1,1,4,4],f32> return %0 : !torch.vtensor<[1,1,4,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_basic_deform_conv_without_padding/model.mlir b/iree_tests/onnx/node/generated/test_basic_deform_conv_without_padding/model.mlir index 6fbb6a1b0..d3398655f 100644 --- a/iree_tests/onnx/node/generated/test_basic_deform_conv_without_padding/model.mlir +++ b/iree_tests/onnx/node/generated/test_basic_deform_conv_without_padding/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_basic_deform_conv_without_padding(%arg0: !torch.vtensor<[1,1,3,3],f32>, %arg1: !torch.vtensor<[1,1,2,2],f32>, %arg2: !torch.vtensor<[1,8,2,2],f32>) -> !torch.vtensor<[1,1,2,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.DeformConv"(%arg0, %arg1, %arg2) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.pads = [0 : si64, 0 : si64, 0 : si64, 0 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,1,2,2],f32>, !torch.vtensor<[1,8,2,2],f32>) -> !torch.vtensor<[1,1,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.DeformConv"(%arg0, %arg1, %arg2) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.pads = [0 : si64, 0 : si64, 0 : si64, 0 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,1,2,2],f32>, !torch.vtensor<[1,8,2,2],f32>) -> !torch.vtensor<[1,1,2,2],f32> return %0 : !torch.vtensor<[1,1,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_batchnorm_epsilon/model.mlir b/iree_tests/onnx/node/generated/test_batchnorm_epsilon/model.mlir index 74f47b8bf..11e125564 100644 --- a/iree_tests/onnx/node/generated/test_batchnorm_epsilon/model.mlir +++ b/iree_tests/onnx/node/generated/test_batchnorm_epsilon/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_batchnorm_epsilon(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[3],f32>, %arg2: !torch.vtensor<[3],f32>, %arg3: !torch.vtensor<[3],f32>, %arg4: !torch.vtensor<[3],f32>) -> !torch.vtensor<[2,3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BatchNormalization"(%arg0, %arg1, %arg2, %arg3, %arg4) {torch.onnx.epsilon = 0.00999999977 : f32} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[2,3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.BatchNormalization"(%arg0, %arg1, %arg2, %arg3, %arg4) {torch.onnx.epsilon = 0.00999999977 : f32} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[2,3,4,5],f32> return %0 : !torch.vtensor<[2,3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_batchnorm_epsilon_training_mode/model.mlir b/iree_tests/onnx/node/generated/test_batchnorm_epsilon_training_mode/model.mlir index 75f6430c5..d9cb010af 100644 --- a/iree_tests/onnx/node/generated/test_batchnorm_epsilon_training_mode/model.mlir +++ b/iree_tests/onnx/node/generated/test_batchnorm_epsilon_training_mode/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_batchnorm_epsilon_training_mode(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[3],f32>, %arg2: !torch.vtensor<[3],f32>, %arg3: !torch.vtensor<[3],f32>, %arg4: !torch.vtensor<[3],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.BatchNormalization"(%arg0, %arg1, %arg2, %arg3, %arg4) {torch.onnx.epsilon = 0.00999999977 : f32, torch.onnx.training_mode = 1 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.BatchNormalization"(%arg0, %arg1, %arg2, %arg3, %arg4) {torch.onnx.epsilon = 0.00999999977 : f32, torch.onnx.training_mode = 1 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_batchnorm_example/model.mlir b/iree_tests/onnx/node/generated/test_batchnorm_example/model.mlir index 124c62e91..9029d2e73 100644 --- a/iree_tests/onnx/node/generated/test_batchnorm_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_batchnorm_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_batchnorm_example(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[3],f32>, %arg2: !torch.vtensor<[3],f32>, %arg3: !torch.vtensor<[3],f32>, %arg4: !torch.vtensor<[3],f32>) -> !torch.vtensor<[2,3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BatchNormalization"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[2,3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.BatchNormalization"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[2,3,4,5],f32> return %0 : !torch.vtensor<[2,3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_batchnorm_example_training_mode/model.mlir b/iree_tests/onnx/node/generated/test_batchnorm_example_training_mode/model.mlir index a126ed4a3..ecfc04464 100644 --- a/iree_tests/onnx/node/generated/test_batchnorm_example_training_mode/model.mlir +++ b/iree_tests/onnx/node/generated/test_batchnorm_example_training_mode/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_batchnorm_example_training_mode(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[3],f32>, %arg2: !torch.vtensor<[3],f32>, %arg3: !torch.vtensor<[3],f32>, %arg4: !torch.vtensor<[3],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.BatchNormalization"(%arg0, %arg1, %arg2, %arg3, %arg4) {torch.onnx.training_mode = 1 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.BatchNormalization"(%arg0, %arg1, %arg2, %arg3, %arg4) {torch.onnx.training_mode = 1 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_bernoulli/model.mlir b/iree_tests/onnx/node/generated/test_bernoulli/model.mlir index 9bca55c25..232b9b1ef 100644 --- a/iree_tests/onnx/node/generated/test_bernoulli/model.mlir +++ b/iree_tests/onnx/node/generated/test_bernoulli/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bernoulli(%arg0: !torch.vtensor<[10],f64>) -> !torch.vtensor<[10],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Bernoulli"(%arg0) : (!torch.vtensor<[10],f64>) -> !torch.vtensor<[10],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Bernoulli"(%arg0) : (!torch.vtensor<[10],f64>) -> !torch.vtensor<[10],f64> return %0 : !torch.vtensor<[10],f64> } } diff --git a/iree_tests/onnx/node/generated/test_bernoulli_double/model.mlir b/iree_tests/onnx/node/generated/test_bernoulli_double/model.mlir index edb0ed121..77cd97e33 100644 --- a/iree_tests/onnx/node/generated/test_bernoulli_double/model.mlir +++ b/iree_tests/onnx/node/generated/test_bernoulli_double/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bernoulli_double(%arg0: !torch.vtensor<[10],f32>) -> !torch.vtensor<[10],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Bernoulli"(%arg0) {torch.onnx.dtype = 11 : si64} : (!torch.vtensor<[10],f32>) -> !torch.vtensor<[10],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Bernoulli"(%arg0) {torch.onnx.dtype = 11 : si64} : (!torch.vtensor<[10],f32>) -> !torch.vtensor<[10],f64> return %0 : !torch.vtensor<[10],f64> } } diff --git a/iree_tests/onnx/node/generated/test_bernoulli_double_expanded/model.mlir b/iree_tests/onnx/node/generated/test_bernoulli_double_expanded/model.mlir index 330ad2b9b..6eef43678 100644 --- a/iree_tests/onnx/node/generated/test_bernoulli_double_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_bernoulli_double_expanded/model.mlir @@ -1,8 +1,9 @@ module { func.func @test_bernoulli_double_expanded(%arg0: !torch.vtensor<[10],f32>) -> !torch.vtensor<[10],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.RandomUniformLike"(%arg0) {torch.onnx.dtype = 1 : si64, torch.onnx.high = 1.000000e+00 : f32, torch.onnx.low = 0.000000e+00 : f32} : (!torch.vtensor<[10],f32>) -> !torch.vtensor<[10],f32> - %1 = torch.operator "onnx.Greater"(%0, %arg0) : (!torch.vtensor<[10],f32>, !torch.vtensor<[10],f32>) -> !torch.vtensor<[10],i1> - %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[10],i1>) -> !torch.vtensor<[10],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.RandomUniformLike"(%arg0) {torch.onnx.dtype = 1 : si64, torch.onnx.high = 1.000000e+00 : f32, torch.onnx.low = 0.000000e+00 : f32} : (!torch.vtensor<[10],f32>) -> !torch.vtensor<[10],f32> + %1 = torch.operator "onnx.Greater"(%0, %arg0) : (!torch.vtensor<[10],f32>, !torch.vtensor<[10],f32>) -> !torch.vtensor<[10],i1> + %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[10],i1>) -> !torch.vtensor<[10],f64> return %2 : !torch.vtensor<[10],f64> } } diff --git a/iree_tests/onnx/node/generated/test_bernoulli_expanded/model.mlir b/iree_tests/onnx/node/generated/test_bernoulli_expanded/model.mlir index 28ddae483..6190e9731 100644 --- a/iree_tests/onnx/node/generated/test_bernoulli_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_bernoulli_expanded/model.mlir @@ -1,8 +1,9 @@ module { func.func @test_bernoulli_expanded(%arg0: !torch.vtensor<[10],f64>) -> !torch.vtensor<[10],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.RandomUniformLike"(%arg0) {torch.onnx.dtype = 11 : si64, torch.onnx.high = 1.000000e+00 : f32, torch.onnx.low = 0.000000e+00 : f32} : (!torch.vtensor<[10],f64>) -> !torch.vtensor<[10],f64> - %1 = torch.operator "onnx.Greater"(%0, %arg0) : (!torch.vtensor<[10],f64>, !torch.vtensor<[10],f64>) -> !torch.vtensor<[10],i1> - %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[10],i1>) -> !torch.vtensor<[10],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.RandomUniformLike"(%arg0) {torch.onnx.dtype = 11 : si64, torch.onnx.high = 1.000000e+00 : f32, torch.onnx.low = 0.000000e+00 : f32} : (!torch.vtensor<[10],f64>) -> !torch.vtensor<[10],f64> + %1 = torch.operator "onnx.Greater"(%0, %arg0) : (!torch.vtensor<[10],f64>, !torch.vtensor<[10],f64>) -> !torch.vtensor<[10],i1> + %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[10],i1>) -> !torch.vtensor<[10],f64> return %2 : !torch.vtensor<[10],f64> } } diff --git a/iree_tests/onnx/node/generated/test_bernoulli_seed/model.mlir b/iree_tests/onnx/node/generated/test_bernoulli_seed/model.mlir index 8349b1f0b..187fdd97e 100644 --- a/iree_tests/onnx/node/generated/test_bernoulli_seed/model.mlir +++ b/iree_tests/onnx/node/generated/test_bernoulli_seed/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bernoulli_seed(%arg0: !torch.vtensor<[10],f32>) -> !torch.vtensor<[10],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Bernoulli"(%arg0) {torch.onnx.seed = 0.000000e+00 : f32} : (!torch.vtensor<[10],f32>) -> !torch.vtensor<[10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Bernoulli"(%arg0) {torch.onnx.seed = 0.000000e+00 : f32} : (!torch.vtensor<[10],f32>) -> !torch.vtensor<[10],f32> return %0 : !torch.vtensor<[10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_bernoulli_seed_expanded/model.mlir b/iree_tests/onnx/node/generated/test_bernoulli_seed_expanded/model.mlir index f168abeb6..3ca8fd712 100644 --- a/iree_tests/onnx/node/generated/test_bernoulli_seed_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_bernoulli_seed_expanded/model.mlir @@ -1,8 +1,9 @@ module { func.func @test_bernoulli_seed_expanded(%arg0: !torch.vtensor<[10],f32>) -> !torch.vtensor<[10],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.RandomUniformLike"(%arg0) {torch.onnx.dtype = 1 : si64, torch.onnx.high = 1.000000e+00 : f32, torch.onnx.low = 0.000000e+00 : f32, torch.onnx.seed = 0.000000e+00 : f32} : (!torch.vtensor<[10],f32>) -> !torch.vtensor<[10],f32> - %1 = torch.operator "onnx.Greater"(%0, %arg0) : (!torch.vtensor<[10],f32>, !torch.vtensor<[10],f32>) -> !torch.vtensor<[10],i1> - %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[10],i1>) -> !torch.vtensor<[10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.RandomUniformLike"(%arg0) {torch.onnx.dtype = 1 : si64, torch.onnx.high = 1.000000e+00 : f32, torch.onnx.low = 0.000000e+00 : f32, torch.onnx.seed = 0.000000e+00 : f32} : (!torch.vtensor<[10],f32>) -> !torch.vtensor<[10],f32> + %1 = torch.operator "onnx.Greater"(%0, %arg0) : (!torch.vtensor<[10],f32>, !torch.vtensor<[10],f32>) -> !torch.vtensor<[10],i1> + %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[10],i1>) -> !torch.vtensor<[10],f32> return %2 : !torch.vtensor<[10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_bitshift_left_uint16/model.mlir b/iree_tests/onnx/node/generated/test_bitshift_left_uint16/model.mlir index df7dcaafc..35fdef21e 100644 --- a/iree_tests/onnx/node/generated/test_bitshift_left_uint16/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitshift_left_uint16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitshift_left_uint16(%arg0: !torch.vtensor<[3],ui16>, %arg1: !torch.vtensor<[3],ui16>) -> !torch.vtensor<[3],ui16> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitShift"(%arg0, %arg1) {torch.onnx.direction = "LEFT"} : (!torch.vtensor<[3],ui16>, !torch.vtensor<[3],ui16>) -> !torch.vtensor<[3],ui16> + %none = torch.constant.none + %0 = torch.operator "onnx.BitShift"(%arg0, %arg1) {torch.onnx.direction = "LEFT"} : (!torch.vtensor<[3],ui16>, !torch.vtensor<[3],ui16>) -> !torch.vtensor<[3],ui16> return %0 : !torch.vtensor<[3],ui16> } } diff --git a/iree_tests/onnx/node/generated/test_bitshift_left_uint32/model.mlir b/iree_tests/onnx/node/generated/test_bitshift_left_uint32/model.mlir index 60fa38482..77b097596 100644 --- a/iree_tests/onnx/node/generated/test_bitshift_left_uint32/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitshift_left_uint32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitshift_left_uint32(%arg0: !torch.vtensor<[3],ui32>, %arg1: !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],ui32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitShift"(%arg0, %arg1) {torch.onnx.direction = "LEFT"} : (!torch.vtensor<[3],ui32>, !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],ui32> + %none = torch.constant.none + %0 = torch.operator "onnx.BitShift"(%arg0, %arg1) {torch.onnx.direction = "LEFT"} : (!torch.vtensor<[3],ui32>, !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],ui32> return %0 : !torch.vtensor<[3],ui32> } } diff --git a/iree_tests/onnx/node/generated/test_bitshift_left_uint64/model.mlir b/iree_tests/onnx/node/generated/test_bitshift_left_uint64/model.mlir index 8ba0bc7c9..9f5653086 100644 --- a/iree_tests/onnx/node/generated/test_bitshift_left_uint64/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitshift_left_uint64/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitshift_left_uint64(%arg0: !torch.vtensor<[3],ui64>, %arg1: !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],ui64> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitShift"(%arg0, %arg1) {torch.onnx.direction = "LEFT"} : (!torch.vtensor<[3],ui64>, !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],ui64> + %none = torch.constant.none + %0 = torch.operator "onnx.BitShift"(%arg0, %arg1) {torch.onnx.direction = "LEFT"} : (!torch.vtensor<[3],ui64>, !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],ui64> return %0 : !torch.vtensor<[3],ui64> } } diff --git a/iree_tests/onnx/node/generated/test_bitshift_left_uint8/model.mlir b/iree_tests/onnx/node/generated/test_bitshift_left_uint8/model.mlir index 0a63c19bb..0f01b7f72 100644 --- a/iree_tests/onnx/node/generated/test_bitshift_left_uint8/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitshift_left_uint8/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitshift_left_uint8(%arg0: !torch.vtensor<[3],ui8>, %arg1: !torch.vtensor<[3],ui8>) -> !torch.vtensor<[3],ui8> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitShift"(%arg0, %arg1) {torch.onnx.direction = "LEFT"} : (!torch.vtensor<[3],ui8>, !torch.vtensor<[3],ui8>) -> !torch.vtensor<[3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.BitShift"(%arg0, %arg1) {torch.onnx.direction = "LEFT"} : (!torch.vtensor<[3],ui8>, !torch.vtensor<[3],ui8>) -> !torch.vtensor<[3],ui8> return %0 : !torch.vtensor<[3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_bitshift_right_uint16/model.mlir b/iree_tests/onnx/node/generated/test_bitshift_right_uint16/model.mlir index e9db1b052..0c2744e14 100644 --- a/iree_tests/onnx/node/generated/test_bitshift_right_uint16/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitshift_right_uint16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitshift_right_uint16(%arg0: !torch.vtensor<[3],ui16>, %arg1: !torch.vtensor<[3],ui16>) -> !torch.vtensor<[3],ui16> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitShift"(%arg0, %arg1) {torch.onnx.direction = "RIGHT"} : (!torch.vtensor<[3],ui16>, !torch.vtensor<[3],ui16>) -> !torch.vtensor<[3],ui16> + %none = torch.constant.none + %0 = torch.operator "onnx.BitShift"(%arg0, %arg1) {torch.onnx.direction = "RIGHT"} : (!torch.vtensor<[3],ui16>, !torch.vtensor<[3],ui16>) -> !torch.vtensor<[3],ui16> return %0 : !torch.vtensor<[3],ui16> } } diff --git a/iree_tests/onnx/node/generated/test_bitshift_right_uint32/model.mlir b/iree_tests/onnx/node/generated/test_bitshift_right_uint32/model.mlir index 4720c030f..e05db104c 100644 --- a/iree_tests/onnx/node/generated/test_bitshift_right_uint32/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitshift_right_uint32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitshift_right_uint32(%arg0: !torch.vtensor<[3],ui32>, %arg1: !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],ui32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitShift"(%arg0, %arg1) {torch.onnx.direction = "RIGHT"} : (!torch.vtensor<[3],ui32>, !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],ui32> + %none = torch.constant.none + %0 = torch.operator "onnx.BitShift"(%arg0, %arg1) {torch.onnx.direction = "RIGHT"} : (!torch.vtensor<[3],ui32>, !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],ui32> return %0 : !torch.vtensor<[3],ui32> } } diff --git a/iree_tests/onnx/node/generated/test_bitshift_right_uint64/model.mlir b/iree_tests/onnx/node/generated/test_bitshift_right_uint64/model.mlir index 1247a5d66..89e124e52 100644 --- a/iree_tests/onnx/node/generated/test_bitshift_right_uint64/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitshift_right_uint64/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitshift_right_uint64(%arg0: !torch.vtensor<[3],ui64>, %arg1: !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],ui64> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitShift"(%arg0, %arg1) {torch.onnx.direction = "RIGHT"} : (!torch.vtensor<[3],ui64>, !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],ui64> + %none = torch.constant.none + %0 = torch.operator "onnx.BitShift"(%arg0, %arg1) {torch.onnx.direction = "RIGHT"} : (!torch.vtensor<[3],ui64>, !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],ui64> return %0 : !torch.vtensor<[3],ui64> } } diff --git a/iree_tests/onnx/node/generated/test_bitshift_right_uint8/model.mlir b/iree_tests/onnx/node/generated/test_bitshift_right_uint8/model.mlir index 5eb41b6c2..f6fe1edab 100644 --- a/iree_tests/onnx/node/generated/test_bitshift_right_uint8/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitshift_right_uint8/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitshift_right_uint8(%arg0: !torch.vtensor<[3],ui8>, %arg1: !torch.vtensor<[3],ui8>) -> !torch.vtensor<[3],ui8> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitShift"(%arg0, %arg1) {torch.onnx.direction = "RIGHT"} : (!torch.vtensor<[3],ui8>, !torch.vtensor<[3],ui8>) -> !torch.vtensor<[3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.BitShift"(%arg0, %arg1) {torch.onnx.direction = "RIGHT"} : (!torch.vtensor<[3],ui8>, !torch.vtensor<[3],ui8>) -> !torch.vtensor<[3],ui8> return %0 : !torch.vtensor<[3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_bitwise_and_i16_3d/model.mlir b/iree_tests/onnx/node/generated/test_bitwise_and_i16_3d/model.mlir index d48c03d22..c95796fce 100644 --- a/iree_tests/onnx/node/generated/test_bitwise_and_i16_3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitwise_and_i16_3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitwise_and_i16_3d(%arg0: !torch.vtensor<[3,4,5],si16>, %arg1: !torch.vtensor<[3,4,5],si16>) -> !torch.vtensor<[3,4,5],si16> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitwiseAnd"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],si16>, !torch.vtensor<[3,4,5],si16>) -> !torch.vtensor<[3,4,5],si16> + %none = torch.constant.none + %0 = torch.operator "onnx.BitwiseAnd"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],si16>, !torch.vtensor<[3,4,5],si16>) -> !torch.vtensor<[3,4,5],si16> return %0 : !torch.vtensor<[3,4,5],si16> } } diff --git a/iree_tests/onnx/node/generated/test_bitwise_and_i32_2d/model.mlir b/iree_tests/onnx/node/generated/test_bitwise_and_i32_2d/model.mlir index 82b964a25..4826f6d76 100644 --- a/iree_tests/onnx/node/generated/test_bitwise_and_i32_2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitwise_and_i32_2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitwise_and_i32_2d(%arg0: !torch.vtensor<[3,4],si32>, %arg1: !torch.vtensor<[3,4],si32>) -> !torch.vtensor<[3,4],si32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitwiseAnd"(%arg0, %arg1) : (!torch.vtensor<[3,4],si32>, !torch.vtensor<[3,4],si32>) -> !torch.vtensor<[3,4],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.BitwiseAnd"(%arg0, %arg1) : (!torch.vtensor<[3,4],si32>, !torch.vtensor<[3,4],si32>) -> !torch.vtensor<[3,4],si32> return %0 : !torch.vtensor<[3,4],si32> } } diff --git a/iree_tests/onnx/node/generated/test_bitwise_and_ui64_bcast_3v1d/model.mlir b/iree_tests/onnx/node/generated/test_bitwise_and_ui64_bcast_3v1d/model.mlir index 70f02396e..2cc9d3297 100644 --- a/iree_tests/onnx/node/generated/test_bitwise_and_ui64_bcast_3v1d/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitwise_and_ui64_bcast_3v1d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitwise_and_ui64_bcast_3v1d(%arg0: !torch.vtensor<[3,4,5],ui64>, %arg1: !torch.vtensor<[5],ui64>) -> !torch.vtensor<[3,4,5],ui64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitwiseAnd"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],ui64>, !torch.vtensor<[5],ui64>) -> !torch.vtensor<[3,4,5],ui64> + %none = torch.constant.none + %0 = torch.operator "onnx.BitwiseAnd"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],ui64>, !torch.vtensor<[5],ui64>) -> !torch.vtensor<[3,4,5],ui64> return %0 : !torch.vtensor<[3,4,5],ui64> } } diff --git a/iree_tests/onnx/node/generated/test_bitwise_and_ui8_bcast_4v3d/model.mlir b/iree_tests/onnx/node/generated/test_bitwise_and_ui8_bcast_4v3d/model.mlir index 6861b1ea3..8314bafe0 100644 --- a/iree_tests/onnx/node/generated/test_bitwise_and_ui8_bcast_4v3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitwise_and_ui8_bcast_4v3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitwise_and_ui8_bcast_4v3d(%arg0: !torch.vtensor<[3,4,5,6],ui8>, %arg1: !torch.vtensor<[4,5,6],ui8>) -> !torch.vtensor<[3,4,5,6],ui8> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitwiseAnd"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],ui8>, !torch.vtensor<[4,5,6],ui8>) -> !torch.vtensor<[3,4,5,6],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.BitwiseAnd"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],ui8>, !torch.vtensor<[4,5,6],ui8>) -> !torch.vtensor<[3,4,5,6],ui8> return %0 : !torch.vtensor<[3,4,5,6],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_bitwise_not_2d/model.mlir b/iree_tests/onnx/node/generated/test_bitwise_not_2d/model.mlir index 807b0137b..7e9b6516f 100644 --- a/iree_tests/onnx/node/generated/test_bitwise_not_2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitwise_not_2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitwise_not_2d(%arg0: !torch.vtensor<[3,4],si32>) -> !torch.vtensor<[3,4],si32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitwiseNot"(%arg0) : (!torch.vtensor<[3,4],si32>) -> !torch.vtensor<[3,4],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.BitwiseNot"(%arg0) : (!torch.vtensor<[3,4],si32>) -> !torch.vtensor<[3,4],si32> return %0 : !torch.vtensor<[3,4],si32> } } diff --git a/iree_tests/onnx/node/generated/test_bitwise_not_3d/model.mlir b/iree_tests/onnx/node/generated/test_bitwise_not_3d/model.mlir index a914601e9..cb3fe537d 100644 --- a/iree_tests/onnx/node/generated/test_bitwise_not_3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitwise_not_3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitwise_not_3d(%arg0: !torch.vtensor<[3,4,5],ui16>) -> !torch.vtensor<[3,4,5],ui16> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitwiseNot"(%arg0) : (!torch.vtensor<[3,4,5],ui16>) -> !torch.vtensor<[3,4,5],ui16> + %none = torch.constant.none + %0 = torch.operator "onnx.BitwiseNot"(%arg0) : (!torch.vtensor<[3,4,5],ui16>) -> !torch.vtensor<[3,4,5],ui16> return %0 : !torch.vtensor<[3,4,5],ui16> } } diff --git a/iree_tests/onnx/node/generated/test_bitwise_not_4d/model.mlir b/iree_tests/onnx/node/generated/test_bitwise_not_4d/model.mlir index ce9ec6cd0..4ff104301 100644 --- a/iree_tests/onnx/node/generated/test_bitwise_not_4d/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitwise_not_4d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitwise_not_4d(%arg0: !torch.vtensor<[3,4,5,6],ui8>) -> !torch.vtensor<[3,4,5,6],ui8> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitwiseNot"(%arg0) : (!torch.vtensor<[3,4,5,6],ui8>) -> !torch.vtensor<[3,4,5,6],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.BitwiseNot"(%arg0) : (!torch.vtensor<[3,4,5,6],ui8>) -> !torch.vtensor<[3,4,5,6],ui8> return %0 : !torch.vtensor<[3,4,5,6],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_bitwise_or_i16_4d/model.mlir b/iree_tests/onnx/node/generated/test_bitwise_or_i16_4d/model.mlir index e819ced91..b094d93de 100644 --- a/iree_tests/onnx/node/generated/test_bitwise_or_i16_4d/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitwise_or_i16_4d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitwise_or_i16_4d(%arg0: !torch.vtensor<[3,4,5,6],si8>, %arg1: !torch.vtensor<[3,4,5,6],si8>) -> !torch.vtensor<[3,4,5,6],si8> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitwiseOr"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],si8>, !torch.vtensor<[3,4,5,6],si8>) -> !torch.vtensor<[3,4,5,6],si8> + %none = torch.constant.none + %0 = torch.operator "onnx.BitwiseOr"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],si8>, !torch.vtensor<[3,4,5,6],si8>) -> !torch.vtensor<[3,4,5,6],si8> return %0 : !torch.vtensor<[3,4,5,6],si8> } } diff --git a/iree_tests/onnx/node/generated/test_bitwise_or_i32_2d/model.mlir b/iree_tests/onnx/node/generated/test_bitwise_or_i32_2d/model.mlir index cbaebca84..5ab65488a 100644 --- a/iree_tests/onnx/node/generated/test_bitwise_or_i32_2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitwise_or_i32_2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitwise_or_i32_2d(%arg0: !torch.vtensor<[3,4],si32>, %arg1: !torch.vtensor<[3,4],si32>) -> !torch.vtensor<[3,4],si32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitwiseOr"(%arg0, %arg1) : (!torch.vtensor<[3,4],si32>, !torch.vtensor<[3,4],si32>) -> !torch.vtensor<[3,4],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.BitwiseOr"(%arg0, %arg1) : (!torch.vtensor<[3,4],si32>, !torch.vtensor<[3,4],si32>) -> !torch.vtensor<[3,4],si32> return %0 : !torch.vtensor<[3,4],si32> } } diff --git a/iree_tests/onnx/node/generated/test_bitwise_or_ui64_bcast_3v1d/model.mlir b/iree_tests/onnx/node/generated/test_bitwise_or_ui64_bcast_3v1d/model.mlir index 4d18d485f..0967cafd8 100644 --- a/iree_tests/onnx/node/generated/test_bitwise_or_ui64_bcast_3v1d/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitwise_or_ui64_bcast_3v1d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitwise_or_ui64_bcast_3v1d(%arg0: !torch.vtensor<[3,4,5],ui64>, %arg1: !torch.vtensor<[5],ui64>) -> !torch.vtensor<[3,4,5],ui64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitwiseOr"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],ui64>, !torch.vtensor<[5],ui64>) -> !torch.vtensor<[3,4,5],ui64> + %none = torch.constant.none + %0 = torch.operator "onnx.BitwiseOr"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],ui64>, !torch.vtensor<[5],ui64>) -> !torch.vtensor<[3,4,5],ui64> return %0 : !torch.vtensor<[3,4,5],ui64> } } diff --git a/iree_tests/onnx/node/generated/test_bitwise_or_ui8_bcast_4v3d/model.mlir b/iree_tests/onnx/node/generated/test_bitwise_or_ui8_bcast_4v3d/model.mlir index fb1957642..435c8e22d 100644 --- a/iree_tests/onnx/node/generated/test_bitwise_or_ui8_bcast_4v3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitwise_or_ui8_bcast_4v3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitwise_or_ui8_bcast_4v3d(%arg0: !torch.vtensor<[3,4,5,6],ui8>, %arg1: !torch.vtensor<[4,5,6],ui8>) -> !torch.vtensor<[3,4,5,6],ui8> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitwiseOr"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],ui8>, !torch.vtensor<[4,5,6],ui8>) -> !torch.vtensor<[3,4,5,6],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.BitwiseOr"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],ui8>, !torch.vtensor<[4,5,6],ui8>) -> !torch.vtensor<[3,4,5,6],ui8> return %0 : !torch.vtensor<[3,4,5,6],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_bitwise_xor_i16_3d/model.mlir b/iree_tests/onnx/node/generated/test_bitwise_xor_i16_3d/model.mlir index d23b0a6f3..f87428358 100644 --- a/iree_tests/onnx/node/generated/test_bitwise_xor_i16_3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitwise_xor_i16_3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitwise_xor_i16_3d(%arg0: !torch.vtensor<[3,4,5],si16>, %arg1: !torch.vtensor<[3,4,5],si16>) -> !torch.vtensor<[3,4,5],si16> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitwiseXor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],si16>, !torch.vtensor<[3,4,5],si16>) -> !torch.vtensor<[3,4,5],si16> + %none = torch.constant.none + %0 = torch.operator "onnx.BitwiseXor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],si16>, !torch.vtensor<[3,4,5],si16>) -> !torch.vtensor<[3,4,5],si16> return %0 : !torch.vtensor<[3,4,5],si16> } } diff --git a/iree_tests/onnx/node/generated/test_bitwise_xor_i32_2d/model.mlir b/iree_tests/onnx/node/generated/test_bitwise_xor_i32_2d/model.mlir index 0416840db..f7f9ee4f1 100644 --- a/iree_tests/onnx/node/generated/test_bitwise_xor_i32_2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitwise_xor_i32_2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitwise_xor_i32_2d(%arg0: !torch.vtensor<[3,4],si32>, %arg1: !torch.vtensor<[3,4],si32>) -> !torch.vtensor<[3,4],si32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitwiseXor"(%arg0, %arg1) : (!torch.vtensor<[3,4],si32>, !torch.vtensor<[3,4],si32>) -> !torch.vtensor<[3,4],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.BitwiseXor"(%arg0, %arg1) : (!torch.vtensor<[3,4],si32>, !torch.vtensor<[3,4],si32>) -> !torch.vtensor<[3,4],si32> return %0 : !torch.vtensor<[3,4],si32> } } diff --git a/iree_tests/onnx/node/generated/test_bitwise_xor_ui64_bcast_3v1d/model.mlir b/iree_tests/onnx/node/generated/test_bitwise_xor_ui64_bcast_3v1d/model.mlir index 01180615d..f831d0a1d 100644 --- a/iree_tests/onnx/node/generated/test_bitwise_xor_ui64_bcast_3v1d/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitwise_xor_ui64_bcast_3v1d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitwise_xor_ui64_bcast_3v1d(%arg0: !torch.vtensor<[3,4,5],ui64>, %arg1: !torch.vtensor<[5],ui64>) -> !torch.vtensor<[3,4,5],ui64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitwiseXor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],ui64>, !torch.vtensor<[5],ui64>) -> !torch.vtensor<[3,4,5],ui64> + %none = torch.constant.none + %0 = torch.operator "onnx.BitwiseXor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],ui64>, !torch.vtensor<[5],ui64>) -> !torch.vtensor<[3,4,5],ui64> return %0 : !torch.vtensor<[3,4,5],ui64> } } diff --git a/iree_tests/onnx/node/generated/test_bitwise_xor_ui8_bcast_4v3d/model.mlir b/iree_tests/onnx/node/generated/test_bitwise_xor_ui8_bcast_4v3d/model.mlir index 797c11a0c..26e2e65ce 100644 --- a/iree_tests/onnx/node/generated/test_bitwise_xor_ui8_bcast_4v3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_bitwise_xor_ui8_bcast_4v3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_bitwise_xor_ui8_bcast_4v3d(%arg0: !torch.vtensor<[3,4,5,6],ui8>, %arg1: !torch.vtensor<[4,5,6],ui8>) -> !torch.vtensor<[3,4,5,6],ui8> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BitwiseXor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],ui8>, !torch.vtensor<[4,5,6],ui8>) -> !torch.vtensor<[3,4,5,6],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.BitwiseXor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],ui8>, !torch.vtensor<[4,5,6],ui8>) -> !torch.vtensor<[3,4,5,6],ui8> return %0 : !torch.vtensor<[3,4,5,6],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_blackmanwindow/model.mlir b/iree_tests/onnx/node/generated/test_blackmanwindow/model.mlir index 3299fe08c..74b051521 100644 --- a/iree_tests/onnx/node/generated/test_blackmanwindow/model.mlir +++ b/iree_tests/onnx/node/generated/test_blackmanwindow/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_blackmanwindow(%arg0: !torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BlackmanWindow"(%arg0) : (!torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.BlackmanWindow"(%arg0) : (!torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> return %0 : !torch.vtensor<[10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_blackmanwindow_expanded/model.mlir b/iree_tests/onnx/node/generated/test_blackmanwindow_expanded/model.mlir index e461248ba..616cbb904 100644 --- a/iree_tests/onnx/node/generated/test_blackmanwindow_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_blackmanwindow_expanded/model.mlir @@ -1,31 +1,32 @@ module { func.func @test_blackmanwindow_expanded(%arg0: !torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<4.200000e-01> : tensor) : !torch.vtensor<[],f32> - %1 = torch.vtensor.literal(dense<5.000000e-01> : tensor) : !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<8.000000e-02> : tensor) : !torch.vtensor<[],f32> - %3 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.vtensor.literal(dense<2.000000e+00> : tensor) : !torch.vtensor<[],f32> - %6 = torch.vtensor.literal(dense<6.28318548> : tensor) : !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[],f32> - %8 = torch.operator "onnx.Sub"(%7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %9 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 1 : si64} : () -> !torch.vtensor<[],si64> - %10 = torch.operator "onnx.Cast"(%9) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> - %11 = torch.operator "onnx.Sub"(%4, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %12 = torch.operator "onnx.Mul"(%7, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %13 = torch.operator "onnx.Mul"(%8, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %14 = torch.operator "onnx.Add"(%12, %13) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %15 = torch.operator "onnx.Div"(%6, %14) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %16 = torch.operator "onnx.Range"(%3, %7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %17 = torch.operator "onnx.Mul"(%16, %15) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %18 = torch.operator "onnx.Mul"(%17, %5) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %19 = torch.operator "onnx.Cos"(%18) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %20 = torch.operator "onnx.Mul"(%2, %19) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %21 = torch.operator "onnx.Cos"(%17) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %22 = torch.operator "onnx.Mul"(%1, %21) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %23 = torch.operator "onnx.Sub"(%0, %22) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %24 = torch.operator "onnx.Add"(%23, %20) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %25 = torch.operator "onnx.Cast"(%24) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<4.200000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<5.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<8.000000e-02> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<6.28318548> : tensor} : () -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.Sub"(%7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %9 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 1 : si64} : () -> !torch.vtensor<[],si64> + %10 = torch.operator "onnx.Cast"(%9) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.Sub"(%4, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %12 = torch.operator "onnx.Mul"(%7, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %13 = torch.operator "onnx.Mul"(%8, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %14 = torch.operator "onnx.Add"(%12, %13) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %15 = torch.operator "onnx.Div"(%6, %14) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %16 = torch.operator "onnx.Range"(%3, %7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %17 = torch.operator "onnx.Mul"(%16, %15) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %18 = torch.operator "onnx.Mul"(%17, %5) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %19 = torch.operator "onnx.Cos"(%18) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %20 = torch.operator "onnx.Mul"(%2, %19) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %21 = torch.operator "onnx.Cos"(%17) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %22 = torch.operator "onnx.Mul"(%1, %21) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %23 = torch.operator "onnx.Sub"(%0, %22) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %24 = torch.operator "onnx.Add"(%23, %20) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %25 = torch.operator "onnx.Cast"(%24) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[10],f32> return %25 : !torch.vtensor<[10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_blackmanwindow_symmetric/model.mlir b/iree_tests/onnx/node/generated/test_blackmanwindow_symmetric/model.mlir index 12d246430..9f69cdf21 100644 --- a/iree_tests/onnx/node/generated/test_blackmanwindow_symmetric/model.mlir +++ b/iree_tests/onnx/node/generated/test_blackmanwindow_symmetric/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_blackmanwindow_symmetric(%arg0: !torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.BlackmanWindow"(%arg0) {torch.onnx.periodic = 0 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.BlackmanWindow"(%arg0) {torch.onnx.periodic = 0 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> return %0 : !torch.vtensor<[10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_blackmanwindow_symmetric_expanded/model.mlir b/iree_tests/onnx/node/generated/test_blackmanwindow_symmetric_expanded/model.mlir index f70875bbf..91f5170f7 100644 --- a/iree_tests/onnx/node/generated/test_blackmanwindow_symmetric_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_blackmanwindow_symmetric_expanded/model.mlir @@ -1,31 +1,32 @@ module { func.func @test_blackmanwindow_symmetric_expanded(%arg0: !torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<4.200000e-01> : tensor) : !torch.vtensor<[],f32> - %1 = torch.vtensor.literal(dense<5.000000e-01> : tensor) : !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<8.000000e-02> : tensor) : !torch.vtensor<[],f32> - %3 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.vtensor.literal(dense<2.000000e+00> : tensor) : !torch.vtensor<[],f32> - %6 = torch.vtensor.literal(dense<6.28318548> : tensor) : !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[],f32> - %8 = torch.operator "onnx.Sub"(%7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %9 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 0 : si64} : () -> !torch.vtensor<[],si64> - %10 = torch.operator "onnx.Cast"(%9) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> - %11 = torch.operator "onnx.Sub"(%4, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %12 = torch.operator "onnx.Mul"(%7, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %13 = torch.operator "onnx.Mul"(%8, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %14 = torch.operator "onnx.Add"(%12, %13) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %15 = torch.operator "onnx.Div"(%6, %14) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %16 = torch.operator "onnx.Range"(%3, %7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %17 = torch.operator "onnx.Mul"(%16, %15) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %18 = torch.operator "onnx.Mul"(%17, %5) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %19 = torch.operator "onnx.Cos"(%18) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %20 = torch.operator "onnx.Mul"(%2, %19) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %21 = torch.operator "onnx.Cos"(%17) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %22 = torch.operator "onnx.Mul"(%1, %21) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %23 = torch.operator "onnx.Sub"(%0, %22) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %24 = torch.operator "onnx.Add"(%23, %20) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %25 = torch.operator "onnx.Cast"(%24) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<4.200000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<5.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<8.000000e-02> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<6.28318548> : tensor} : () -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.Sub"(%7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %9 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 0 : si64} : () -> !torch.vtensor<[],si64> + %10 = torch.operator "onnx.Cast"(%9) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.Sub"(%4, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %12 = torch.operator "onnx.Mul"(%7, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %13 = torch.operator "onnx.Mul"(%8, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %14 = torch.operator "onnx.Add"(%12, %13) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %15 = torch.operator "onnx.Div"(%6, %14) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %16 = torch.operator "onnx.Range"(%3, %7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %17 = torch.operator "onnx.Mul"(%16, %15) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %18 = torch.operator "onnx.Mul"(%17, %5) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %19 = torch.operator "onnx.Cos"(%18) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %20 = torch.operator "onnx.Mul"(%2, %19) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %21 = torch.operator "onnx.Cos"(%17) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %22 = torch.operator "onnx.Mul"(%1, %21) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %23 = torch.operator "onnx.Sub"(%0, %22) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %24 = torch.operator "onnx.Add"(%23, %20) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %25 = torch.operator "onnx.Cast"(%24) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[10],f32> return %25 : !torch.vtensor<[10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_cast_BFLOAT16_to_FLOAT/model.mlir b/iree_tests/onnx/node/generated/test_cast_BFLOAT16_to_FLOAT/model.mlir index e4f6ee0a8..8294bb235 100644 --- a/iree_tests/onnx/node/generated/test_cast_BFLOAT16_to_FLOAT/model.mlir +++ b/iree_tests/onnx/node/generated/test_cast_BFLOAT16_to_FLOAT/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cast_BFLOAT16_to_FLOAT(%arg0: !torch.vtensor<[3,4],bf16>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],bf16>) -> !torch.vtensor<[3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],bf16>) -> !torch.vtensor<[3,4],f32> return %0 : !torch.vtensor<[3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_cast_DOUBLE_to_FLOAT/model.mlir b/iree_tests/onnx/node/generated/test_cast_DOUBLE_to_FLOAT/model.mlir index 9744060bc..a339a132a 100644 --- a/iree_tests/onnx/node/generated/test_cast_DOUBLE_to_FLOAT/model.mlir +++ b/iree_tests/onnx/node/generated/test_cast_DOUBLE_to_FLOAT/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cast_DOUBLE_to_FLOAT(%arg0: !torch.vtensor<[3,4],f64>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f64>) -> !torch.vtensor<[3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f64>) -> !torch.vtensor<[3,4],f32> return %0 : !torch.vtensor<[3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_cast_DOUBLE_to_FLOAT16/model.mlir b/iree_tests/onnx/node/generated/test_cast_DOUBLE_to_FLOAT16/model.mlir index b6ae12f8c..c06cd1597 100644 --- a/iree_tests/onnx/node/generated/test_cast_DOUBLE_to_FLOAT16/model.mlir +++ b/iree_tests/onnx/node/generated/test_cast_DOUBLE_to_FLOAT16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cast_DOUBLE_to_FLOAT16(%arg0: !torch.vtensor<[3,4],f64>) -> !torch.vtensor<[3,4],f16> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 10 : si64} : (!torch.vtensor<[3,4],f64>) -> !torch.vtensor<[3,4],f16> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 10 : si64} : (!torch.vtensor<[3,4],f64>) -> !torch.vtensor<[3,4],f16> return %0 : !torch.vtensor<[3,4],f16> } } diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_DOUBLE/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_DOUBLE/model.mlir index 2722fccda..133698195 100644 --- a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_DOUBLE/model.mlir +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_DOUBLE/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cast_FLOAT16_to_DOUBLE(%arg0: !torch.vtensor<[3,4],f16>) -> !torch.vtensor<[3,4],f64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,4],f16>) -> !torch.vtensor<[3,4],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,4],f16>) -> !torch.vtensor<[3,4],f64> return %0 : !torch.vtensor<[3,4],f64> } } diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT/model.mlir index cc47d19b3..66b836409 100644 --- a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT/model.mlir +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cast_FLOAT16_to_FLOAT(%arg0: !torch.vtensor<[3,4],f16>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f16>) -> !torch.vtensor<[3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f16>) -> !torch.vtensor<[3,4],f32> return %0 : !torch.vtensor<[3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FN/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FN/input_0.npy new file mode 100644 index 000000000..f15b1a310 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FN/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FN/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FN/model.mlir new file mode 100644 index 000000000..b6970d6a4 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FN/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT16_to_FLOAT8E4M3FN(%arg0: !torch.vtensor<[3,5],f16>) -> !torch.vtensor<[3,5],f8E4M3FN> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 17 : si64} : (!torch.vtensor<[3,5],f16>) -> !torch.vtensor<[3,5],f8E4M3FN> + return %0 : !torch.vtensor<[3,5],f8E4M3FN> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FN/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FN/output_0.npy new file mode 100644 index 000000000..936e4ef4f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FN/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FN/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FN/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FN/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FNUZ/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FNUZ/input_0.npy new file mode 100644 index 000000000..f15b1a310 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FNUZ/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FNUZ/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FNUZ/model.mlir new file mode 100644 index 000000000..56e87b1fe --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FNUZ/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT16_to_FLOAT8E4M3FNUZ(%arg0: !torch.vtensor<[3,5],f16>) -> !torch.vtensor<[3,5],f8E5M2FNUZ> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 18 : si64} : (!torch.vtensor<[3,5],f16>) -> !torch.vtensor<[3,5],f8E5M2FNUZ> + return %0 : !torch.vtensor<[3,5],f8E5M2FNUZ> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FNUZ/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FNUZ/output_0.npy new file mode 100644 index 000000000..368edfd1d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FNUZ/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FNUZ/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FNUZ/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E4M3FNUZ/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2/input_0.npy new file mode 100644 index 000000000..f15b1a310 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2/model.mlir new file mode 100644 index 000000000..52317053b --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT16_to_FLOAT8E5M2(%arg0: !torch.vtensor<[3,5],f16>) -> !torch.vtensor<[3,5],f8E5M2> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 19 : si64} : (!torch.vtensor<[3,5],f16>) -> !torch.vtensor<[3,5],f8E5M2> + return %0 : !torch.vtensor<[3,5],f8E5M2> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2/output_0.npy new file mode 100644 index 000000000..daa2b6b01 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2FNUZ/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2FNUZ/input_0.npy new file mode 100644 index 000000000..f15b1a310 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2FNUZ/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2FNUZ/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2FNUZ/model.mlir new file mode 100644 index 000000000..e3762b7b4 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2FNUZ/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT16_to_FLOAT8E5M2FNUZ(%arg0: !torch.vtensor<[3,5],f16>) -> !torch.vtensor<[3,5],f8E5M2FNUZ> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 20 : si64} : (!torch.vtensor<[3,5],f16>) -> !torch.vtensor<[3,5],f8E5M2FNUZ> + return %0 : !torch.vtensor<[3,5],f8E5M2FNUZ> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2FNUZ/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2FNUZ/output_0.npy new file mode 100644 index 000000000..f411813ab Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2FNUZ/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2FNUZ/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2FNUZ/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT16_to_FLOAT8E5M2FNUZ/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT/input_0.npy new file mode 100644 index 000000000..368edfd1d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT/model.mlir new file mode 100644 index 000000000..339152fc3 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT8E4M3FNUZ_to_FLOAT(%arg0: !torch.vtensor<[3,5],f8E5M2FNUZ>) -> !torch.vtensor<[3,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,5],f8E5M2FNUZ>) -> !torch.vtensor<[3,5],f32> + return %0 : !torch.vtensor<[3,5],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT/output_0.npy new file mode 100644 index 000000000..368edfd1d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT16/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT16/input_0.npy new file mode 100644 index 000000000..368edfd1d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT16/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT16/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT16/model.mlir new file mode 100644 index 000000000..3cdd40c27 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT16/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT8E4M3FNUZ_to_FLOAT16(%arg0: !torch.vtensor<[3,5],f8E5M2FNUZ>) -> !torch.vtensor<[3,5],f16> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 10 : si64} : (!torch.vtensor<[3,5],f8E5M2FNUZ>) -> !torch.vtensor<[3,5],f16> + return %0 : !torch.vtensor<[3,5],f16> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT16/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT16/output_0.npy new file mode 100644 index 000000000..d8be7d794 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT16/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT16/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT16/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FNUZ_to_FLOAT16/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT/input_0.npy new file mode 100644 index 000000000..936e4ef4f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT/model.mlir new file mode 100644 index 000000000..d5b3f06b3 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT8E4M3FN_to_FLOAT(%arg0: !torch.vtensor<[3,5],f8E4M3FN>) -> !torch.vtensor<[3,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,5],f8E4M3FN>) -> !torch.vtensor<[3,5],f32> + return %0 : !torch.vtensor<[3,5],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT/output_0.npy new file mode 100644 index 000000000..936e4ef4f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT16/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT16/input_0.npy new file mode 100644 index 000000000..936e4ef4f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT16/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT16/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT16/model.mlir new file mode 100644 index 000000000..c68540cd1 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT16/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT8E4M3FN_to_FLOAT16(%arg0: !torch.vtensor<[3,5],f8E4M3FN>) -> !torch.vtensor<[3,5],f16> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 10 : si64} : (!torch.vtensor<[3,5],f8E4M3FN>) -> !torch.vtensor<[3,5],f16> + return %0 : !torch.vtensor<[3,5],f16> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT16/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT16/output_0.npy new file mode 100644 index 000000000..905df53de Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT16/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT16/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT16/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT8E4M3FN_to_FLOAT16/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT/input_0.npy new file mode 100644 index 000000000..f411813ab Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT/model.mlir new file mode 100644 index 000000000..6054b0f9c --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT8E5M2FNUZ_to_FLOAT(%arg0: !torch.vtensor<[3,5],f8E5M2FNUZ>) -> !torch.vtensor<[3,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,5],f8E5M2FNUZ>) -> !torch.vtensor<[3,5],f32> + return %0 : !torch.vtensor<[3,5],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT/output_0.npy new file mode 100644 index 000000000..f411813ab Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT16/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT16/input_0.npy new file mode 100644 index 000000000..f411813ab Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT16/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT16/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT16/model.mlir new file mode 100644 index 000000000..a05b9df7e --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT16/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT8E5M2FNUZ_to_FLOAT16(%arg0: !torch.vtensor<[3,5],f8E5M2FNUZ>) -> !torch.vtensor<[3,5],f16> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 10 : si64} : (!torch.vtensor<[3,5],f8E5M2FNUZ>) -> !torch.vtensor<[3,5],f16> + return %0 : !torch.vtensor<[3,5],f16> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT16/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT16/output_0.npy new file mode 100644 index 000000000..5d548abb4 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT16/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT16/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT16/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2FNUZ_to_FLOAT16/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT/input_0.npy new file mode 100644 index 000000000..daa2b6b01 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT/model.mlir new file mode 100644 index 000000000..0c4f2fd94 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT8E5M2_to_FLOAT(%arg0: !torch.vtensor<[3,5],f8E5M2>) -> !torch.vtensor<[3,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,5],f8E5M2>) -> !torch.vtensor<[3,5],f32> + return %0 : !torch.vtensor<[3,5],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT/output_0.npy new file mode 100644 index 000000000..daa2b6b01 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT16/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT16/input_0.npy new file mode 100644 index 000000000..daa2b6b01 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT16/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT16/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT16/model.mlir new file mode 100644 index 000000000..ddfe6a0aa --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT16/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT8E5M2_to_FLOAT16(%arg0: !torch.vtensor<[3,5],f8E5M2>) -> !torch.vtensor<[3,5],f16> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 10 : si64} : (!torch.vtensor<[3,5],f8E5M2>) -> !torch.vtensor<[3,5],f16> + return %0 : !torch.vtensor<[3,5],f16> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT16/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT16/output_0.npy new file mode 100644 index 000000000..918ea6f87 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT16/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT16/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT16/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT8E5M2_to_FLOAT16/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_BFLOAT16/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_BFLOAT16/model.mlir index c39c5f12f..3c0a9bdc5 100644 --- a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_BFLOAT16/model.mlir +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_BFLOAT16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cast_FLOAT_to_BFLOAT16(%arg0: !torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],bf16> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 16 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],bf16> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 16 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],bf16> return %0 : !torch.vtensor<[3,4],bf16> } } diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_DOUBLE/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_DOUBLE/model.mlir index 3e6a21681..1e49b4a34 100644 --- a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_DOUBLE/model.mlir +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_DOUBLE/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cast_FLOAT_to_DOUBLE(%arg0: !torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f64> return %0 : !torch.vtensor<[3,4],f64> } } diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT16/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT16/model.mlir index a15094686..7e459fa0c 100644 --- a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT16/model.mlir +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cast_FLOAT_to_FLOAT16(%arg0: !torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f16> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 10 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f16> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 10 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f16> return %0 : !torch.vtensor<[3,4],f16> } } diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FN/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FN/input_0.npy new file mode 100644 index 000000000..67c5d9d85 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FN/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FN/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FN/model.mlir new file mode 100644 index 000000000..07d62fcf6 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FN/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT_to_FLOAT8E4M3FN(%arg0: !torch.vtensor<[3,5],f32>) -> !torch.vtensor<[3,5],f8E4M3FN> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 17 : si64} : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[3,5],f8E4M3FN> + return %0 : !torch.vtensor<[3,5],f8E4M3FN> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FN/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FN/output_0.npy new file mode 100644 index 000000000..936e4ef4f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FN/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FN/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FN/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FN/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FNUZ/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FNUZ/input_0.npy new file mode 100644 index 000000000..67c5d9d85 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FNUZ/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FNUZ/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FNUZ/model.mlir new file mode 100644 index 000000000..0e54159fb --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FNUZ/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT_to_FLOAT8E4M3FNUZ(%arg0: !torch.vtensor<[3,5],f32>) -> !torch.vtensor<[3,5],f8E5M2FNUZ> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 18 : si64} : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[3,5],f8E5M2FNUZ> + return %0 : !torch.vtensor<[3,5],f8E5M2FNUZ> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FNUZ/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FNUZ/output_0.npy new file mode 100644 index 000000000..368edfd1d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FNUZ/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FNUZ/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FNUZ/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E4M3FNUZ/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2/input_0.npy new file mode 100644 index 000000000..67c5d9d85 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2/model.mlir new file mode 100644 index 000000000..860fe543b --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT_to_FLOAT8E5M2(%arg0: !torch.vtensor<[3,5],f32>) -> !torch.vtensor<[3,5],f8E5M2> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 19 : si64} : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[3,5],f8E5M2> + return %0 : !torch.vtensor<[3,5],f8E5M2> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2/output_0.npy new file mode 100644 index 000000000..daa2b6b01 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2FNUZ/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2FNUZ/input_0.npy new file mode 100644 index 000000000..67c5d9d85 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2FNUZ/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2FNUZ/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2FNUZ/model.mlir new file mode 100644 index 000000000..a0a91eab3 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2FNUZ/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT_to_FLOAT8E5M2FNUZ(%arg0: !torch.vtensor<[3,5],f32>) -> !torch.vtensor<[3,5],f8E5M2FNUZ> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 20 : si64} : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[3,5],f8E5M2FNUZ> + return %0 : !torch.vtensor<[3,5],f8E5M2FNUZ> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2FNUZ/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2FNUZ/output_0.npy new file mode 100644 index 000000000..f411813ab Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2FNUZ/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2FNUZ/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2FNUZ/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_FLOAT8E5M2FNUZ/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_STRING/input_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_STRING/input_0.npy new file mode 100644 index 000000000..a1ea94a5a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_STRING/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_STRING/model.mlir b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_STRING/model.mlir new file mode 100644 index 000000000..cd08a8508 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_STRING/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_FLOAT_to_STRING(%arg0: !torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],!torch.str> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 8 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],!torch.str> + return %0 : !torch.vtensor<[3,4],!torch.str> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_STRING/output_0.npy b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_STRING/output_0.npy new file mode 100644 index 000000000..9c4779909 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_STRING/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_FLOAT_to_STRING/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_STRING/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_FLOAT_to_STRING/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_STRING_to_FLOAT/input_0.npy b/iree_tests/onnx/node/generated/test_cast_STRING_to_FLOAT/input_0.npy new file mode 100644 index 000000000..b52101d9c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_STRING_to_FLOAT/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_STRING_to_FLOAT/model.mlir b/iree_tests/onnx/node/generated/test_cast_STRING_to_FLOAT/model.mlir new file mode 100644 index 000000000..aa45bce99 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_STRING_to_FLOAT/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_STRING_to_FLOAT(%arg0: !torch.vtensor<[3,4],!torch.str>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],!torch.str>) -> !torch.vtensor<[3,4],f32> + return %0 : !torch.vtensor<[3,4],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_STRING_to_FLOAT/output_0.npy b/iree_tests/onnx/node/generated/test_cast_STRING_to_FLOAT/output_0.npy new file mode 100644 index 000000000..cf5f4645d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_STRING_to_FLOAT/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_STRING_to_FLOAT/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_STRING_to_FLOAT/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_STRING_to_FLOAT/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN/input_0.npy b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN/input_0.npy new file mode 100644 index 000000000..f15b1a310 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN/model.mlir b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN/model.mlir new file mode 100644 index 000000000..6bbcb4c8f --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN(%arg0: !torch.vtensor<[3,5],f16>) -> !torch.vtensor<[3,5],f8E4M3FN> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 0 : si64, torch.onnx.to = 17 : si64} : (!torch.vtensor<[3,5],f16>) -> !torch.vtensor<[3,5],f8E4M3FN> + return %0 : !torch.vtensor<[3,5],f8E4M3FN> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN/output_0.npy b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN/output_0.npy new file mode 100644 index 000000000..30b0e2bc1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ/input_0.npy b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ/input_0.npy new file mode 100644 index 000000000..f15b1a310 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ/model.mlir b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ/model.mlir new file mode 100644 index 000000000..844009631 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ(%arg0: !torch.vtensor<[3,5],f16>) -> !torch.vtensor<[3,5],f8E5M2FNUZ> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 0 : si64, torch.onnx.to = 18 : si64} : (!torch.vtensor<[3,5],f16>) -> !torch.vtensor<[3,5],f8E5M2FNUZ> + return %0 : !torch.vtensor<[3,5],f8E5M2FNUZ> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ/output_0.npy b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ/output_0.npy new file mode 100644 index 000000000..e3d8b014f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2/input_0.npy b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2/input_0.npy new file mode 100644 index 000000000..f15b1a310 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2/model.mlir b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2/model.mlir new file mode 100644 index 000000000..15f045681 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2(%arg0: !torch.vtensor<[3,5],f16>) -> !torch.vtensor<[3,5],f8E5M2> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 0 : si64, torch.onnx.to = 19 : si64} : (!torch.vtensor<[3,5],f16>) -> !torch.vtensor<[3,5],f8E5M2> + return %0 : !torch.vtensor<[3,5],f8E5M2> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2/output_0.npy b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2/output_0.npy new file mode 100644 index 000000000..dd3506bde Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ/input_0.npy b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ/input_0.npy new file mode 100644 index 000000000..f15b1a310 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ/model.mlir b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ/model.mlir new file mode 100644 index 000000000..293c50c3b --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ(%arg0: !torch.vtensor<[3,5],f16>) -> !torch.vtensor<[3,5],f8E5M2FNUZ> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 0 : si64, torch.onnx.to = 20 : si64} : (!torch.vtensor<[3,5],f16>) -> !torch.vtensor<[3,5],f8E5M2FNUZ> + return %0 : !torch.vtensor<[3,5],f8E5M2FNUZ> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ/output_0.npy b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ/output_0.npy new file mode 100644 index 000000000..b9efcf480 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN/input_0.npy b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN/input_0.npy new file mode 100644 index 000000000..67c5d9d85 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN/model.mlir b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN/model.mlir new file mode 100644 index 000000000..65144caa9 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN(%arg0: !torch.vtensor<[3,5],f32>) -> !torch.vtensor<[3,5],f8E4M3FN> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 0 : si64, torch.onnx.to = 17 : si64} : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[3,5],f8E4M3FN> + return %0 : !torch.vtensor<[3,5],f8E4M3FN> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN/output_0.npy b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN/output_0.npy new file mode 100644 index 000000000..30b0e2bc1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ/input_0.npy b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ/input_0.npy new file mode 100644 index 000000000..67c5d9d85 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ/model.mlir b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ/model.mlir new file mode 100644 index 000000000..cd3a5fb91 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ(%arg0: !torch.vtensor<[3,5],f32>) -> !torch.vtensor<[3,5],f8E5M2FNUZ> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 0 : si64, torch.onnx.to = 18 : si64} : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[3,5],f8E5M2FNUZ> + return %0 : !torch.vtensor<[3,5],f8E5M2FNUZ> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ/output_0.npy b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ/output_0.npy new file mode 100644 index 000000000..e3d8b014f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2/input_0.npy b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2/input_0.npy new file mode 100644 index 000000000..67c5d9d85 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2/model.mlir b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2/model.mlir new file mode 100644 index 000000000..1f4ae1e09 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_no_saturate_FLOAT_to_FLOAT8E5M2(%arg0: !torch.vtensor<[3,5],f32>) -> !torch.vtensor<[3,5],f8E5M2> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 0 : si64, torch.onnx.to = 19 : si64} : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[3,5],f8E5M2> + return %0 : !torch.vtensor<[3,5],f8E5M2> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2/output_0.npy b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2/output_0.npy new file mode 100644 index 000000000..dd3506bde Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ/input_0.npy b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ/input_0.npy new file mode 100644 index 000000000..67c5d9d85 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ/model.mlir b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ/model.mlir new file mode 100644 index 000000000..baeed11dc --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ(%arg0: !torch.vtensor<[3,5],f32>) -> !torch.vtensor<[3,5],f8E5M2FNUZ> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 0 : si64, torch.onnx.to = 20 : si64} : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[3,5],f8E5M2FNUZ> + return %0 : !torch.vtensor<[3,5],f8E5M2FNUZ> + } +} + diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ/output_0.npy b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ/output_0.npy new file mode 100644 index 000000000..b9efcf480 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ/test_data_flags.txt b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_BFLOAT16_to_FLOAT/model.mlir b/iree_tests/onnx/node/generated/test_castlike_BFLOAT16_to_FLOAT/model.mlir index 42d252ad3..05fff5bde 100644 --- a/iree_tests/onnx/node/generated/test_castlike_BFLOAT16_to_FLOAT/model.mlir +++ b/iree_tests/onnx/node/generated/test_castlike_BFLOAT16_to_FLOAT/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_castlike_BFLOAT16_to_FLOAT(%arg0: !torch.vtensor<[3,4],bf16>, %arg1: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],bf16>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],bf16>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> return %0 : !torch.vtensor<[3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_castlike_BFLOAT16_to_FLOAT_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_BFLOAT16_to_FLOAT_expanded/model.mlir index c4bfbbf96..1de409a93 100644 --- a/iree_tests/onnx/node/generated/test_castlike_BFLOAT16_to_FLOAT_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_castlike_BFLOAT16_to_FLOAT_expanded/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_castlike_BFLOAT16_to_FLOAT_expanded(%arg0: !torch.vtensor<[3,4],bf16>, %arg1: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],bf16>) -> !torch.vtensor<[3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],bf16>) -> !torch.vtensor<[3,4],f32> return %0 : !torch.vtensor<[3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_castlike_DOUBLE_to_FLOAT/model.mlir b/iree_tests/onnx/node/generated/test_castlike_DOUBLE_to_FLOAT/model.mlir index dabb94222..13f550ca3 100644 --- a/iree_tests/onnx/node/generated/test_castlike_DOUBLE_to_FLOAT/model.mlir +++ b/iree_tests/onnx/node/generated/test_castlike_DOUBLE_to_FLOAT/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_castlike_DOUBLE_to_FLOAT(%arg0: !torch.vtensor<[3,4],f64>, %arg1: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f64>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f64>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> return %0 : !torch.vtensor<[3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_castlike_DOUBLE_to_FLOAT16/model.mlir b/iree_tests/onnx/node/generated/test_castlike_DOUBLE_to_FLOAT16/model.mlir index 433d231f1..c43cbd623 100644 --- a/iree_tests/onnx/node/generated/test_castlike_DOUBLE_to_FLOAT16/model.mlir +++ b/iree_tests/onnx/node/generated/test_castlike_DOUBLE_to_FLOAT16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_castlike_DOUBLE_to_FLOAT16(%arg0: !torch.vtensor<[3,4],f64>, %arg1: !torch.vtensor<[1],f16>) -> !torch.vtensor<[3,4],f16> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f64>, !torch.vtensor<[1],f16>) -> !torch.vtensor<[3,4],f16> + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f64>, !torch.vtensor<[1],f16>) -> !torch.vtensor<[3,4],f16> return %0 : !torch.vtensor<[3,4],f16> } } diff --git a/iree_tests/onnx/node/generated/test_castlike_DOUBLE_to_FLOAT16_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_DOUBLE_to_FLOAT16_expanded/model.mlir index 269a0e306..6bfe59ea0 100644 --- a/iree_tests/onnx/node/generated/test_castlike_DOUBLE_to_FLOAT16_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_castlike_DOUBLE_to_FLOAT16_expanded/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_castlike_DOUBLE_to_FLOAT16_expanded(%arg0: !torch.vtensor<[3,4],f64>, %arg1: !torch.vtensor<[1],f16>) -> !torch.vtensor<[3,4],f16> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 10 : si64} : (!torch.vtensor<[3,4],f64>) -> !torch.vtensor<[3,4],f16> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 10 : si64} : (!torch.vtensor<[3,4],f64>) -> !torch.vtensor<[3,4],f16> return %0 : !torch.vtensor<[3,4],f16> } } diff --git a/iree_tests/onnx/node/generated/test_castlike_DOUBLE_to_FLOAT_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_DOUBLE_to_FLOAT_expanded/model.mlir index 576f504de..0969ae59b 100644 --- a/iree_tests/onnx/node/generated/test_castlike_DOUBLE_to_FLOAT_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_castlike_DOUBLE_to_FLOAT_expanded/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_castlike_DOUBLE_to_FLOAT_expanded(%arg0: !torch.vtensor<[3,4],f64>, %arg1: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f64>) -> !torch.vtensor<[3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f64>) -> !torch.vtensor<[3,4],f32> return %0 : !torch.vtensor<[3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT16_to_DOUBLE/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT16_to_DOUBLE/model.mlir index cc6bca0ef..869a0ded3 100644 --- a/iree_tests/onnx/node/generated/test_castlike_FLOAT16_to_DOUBLE/model.mlir +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT16_to_DOUBLE/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_castlike_FLOAT16_to_DOUBLE(%arg0: !torch.vtensor<[3,4],f16>, %arg1: !torch.vtensor<[1],f64>) -> !torch.vtensor<[3,4],f64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f16>, !torch.vtensor<[1],f64>) -> !torch.vtensor<[3,4],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f16>, !torch.vtensor<[1],f64>) -> !torch.vtensor<[3,4],f64> return %0 : !torch.vtensor<[3,4],f64> } } diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT16_to_DOUBLE_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT16_to_DOUBLE_expanded/model.mlir index ad697d42d..a5339cb9a 100644 --- a/iree_tests/onnx/node/generated/test_castlike_FLOAT16_to_DOUBLE_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT16_to_DOUBLE_expanded/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_castlike_FLOAT16_to_DOUBLE_expanded(%arg0: !torch.vtensor<[3,4],f16>, %arg1: !torch.vtensor<[1],f64>) -> !torch.vtensor<[3,4],f64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,4],f16>) -> !torch.vtensor<[3,4],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,4],f16>) -> !torch.vtensor<[3,4],f64> return %0 : !torch.vtensor<[3,4],f64> } } diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT16_to_FLOAT/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT16_to_FLOAT/model.mlir index e9a22ca17..af7ed1c37 100644 --- a/iree_tests/onnx/node/generated/test_castlike_FLOAT16_to_FLOAT/model.mlir +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT16_to_FLOAT/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_castlike_FLOAT16_to_FLOAT(%arg0: !torch.vtensor<[3,4],f16>, %arg1: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f16>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f16>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> return %0 : !torch.vtensor<[3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT16_to_FLOAT_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT16_to_FLOAT_expanded/model.mlir index e7e759677..17421b200 100644 --- a/iree_tests/onnx/node/generated/test_castlike_FLOAT16_to_FLOAT_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT16_to_FLOAT_expanded/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_castlike_FLOAT16_to_FLOAT_expanded(%arg0: !torch.vtensor<[3,4],f16>, %arg1: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f16>) -> !torch.vtensor<[3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f16>) -> !torch.vtensor<[3,4],f32> return %0 : !torch.vtensor<[3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT/input_0.npy new file mode 100644 index 000000000..a2ee45a4e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT/input_1.npy new file mode 100644 index 000000000..ce0222503 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT/model.mlir new file mode 100644 index 000000000..28880b636 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT8E4M3FNUZ_to_FLOAT(%arg0: !torch.vtensor<[3,4],f8E5M2FNUZ>, %arg1: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f8E5M2FNUZ>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> + return %0 : !torch.vtensor<[3,4],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT/output_0.npy new file mode 100644 index 000000000..a2ee45a4e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded/input_0.npy new file mode 100644 index 000000000..a2ee45a4e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded/input_1.npy new file mode 100644 index 000000000..ce0222503 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded/model.mlir new file mode 100644 index 000000000..6a00f87d4 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded(%arg0: !torch.vtensor<[3,4],f8E5M2FNUZ>, %arg1: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f8E5M2FNUZ>) -> !torch.vtensor<[3,4],f32> + return %0 : !torch.vtensor<[3,4],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded/output_0.npy new file mode 100644 index 000000000..a2ee45a4e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT/input_0.npy new file mode 100644 index 000000000..a2ee45a4e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT/input_1.npy new file mode 100644 index 000000000..ce0222503 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT/model.mlir new file mode 100644 index 000000000..7c8c5d9e7 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT8E4M3FN_to_FLOAT(%arg0: !torch.vtensor<[3,4],f8E5M2FNUZ>, %arg1: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f8E5M2FNUZ>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> + return %0 : !torch.vtensor<[3,4],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT/output_0.npy new file mode 100644 index 000000000..a2ee45a4e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded/input_0.npy new file mode 100644 index 000000000..a2ee45a4e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded/input_1.npy new file mode 100644 index 000000000..ce0222503 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded/model.mlir new file mode 100644 index 000000000..7c1eafe83 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded(%arg0: !torch.vtensor<[3,4],f8E5M2FNUZ>, %arg1: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f8E5M2FNUZ>) -> !torch.vtensor<[3,4],f32> + return %0 : !torch.vtensor<[3,4],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded/output_0.npy new file mode 100644 index 000000000..a2ee45a4e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT/input_0.npy new file mode 100644 index 000000000..761e13d3f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT/input_1.npy new file mode 100644 index 000000000..af8a234e1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT/model.mlir new file mode 100644 index 000000000..252dc536c --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT8E5M2FNUZ_to_FLOAT(%arg0: !torch.vtensor<[3,4],f8E5M2FNUZ>, %arg1: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f8E5M2FNUZ>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> + return %0 : !torch.vtensor<[3,4],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT/output_0.npy new file mode 100644 index 000000000..761e13d3f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded/input_0.npy new file mode 100644 index 000000000..761e13d3f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded/input_1.npy new file mode 100644 index 000000000..af8a234e1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded/model.mlir new file mode 100644 index 000000000..96b78a328 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded(%arg0: !torch.vtensor<[3,4],f8E5M2FNUZ>, %arg1: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f8E5M2FNUZ>) -> !torch.vtensor<[3,4],f32> + return %0 : !torch.vtensor<[3,4],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded/output_0.npy new file mode 100644 index 000000000..761e13d3f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT/input_0.npy new file mode 100644 index 000000000..761e13d3f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT/input_1.npy new file mode 100644 index 000000000..af8a234e1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT/model.mlir new file mode 100644 index 000000000..a9ccee0fe --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT8E5M2_to_FLOAT(%arg0: !torch.vtensor<[3,4],f8E5M2FNUZ>, %arg1: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f8E5M2FNUZ>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> + return %0 : !torch.vtensor<[3,4],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT/output_0.npy new file mode 100644 index 000000000..761e13d3f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT_expanded/input_0.npy new file mode 100644 index 000000000..761e13d3f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT_expanded/input_1.npy new file mode 100644 index 000000000..af8a234e1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT_expanded/model.mlir new file mode 100644 index 000000000..8048fec0b --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT_expanded/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT8E5M2_to_FLOAT_expanded(%arg0: !torch.vtensor<[3,4],f8E5M2FNUZ>, %arg1: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f8E5M2FNUZ>) -> !torch.vtensor<[3,4],f32> + return %0 : !torch.vtensor<[3,4],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT_expanded/output_0.npy new file mode 100644 index 000000000..761e13d3f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT8E5M2_to_FLOAT_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_BFLOAT16/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_BFLOAT16/model.mlir index 40a040116..b03e36039 100644 --- a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_BFLOAT16/model.mlir +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_BFLOAT16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_castlike_FLOAT_to_BFLOAT16(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],bf16>) -> !torch.vtensor<[3,4],bf16> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],bf16>) -> !torch.vtensor<[3,4],bf16> + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],bf16>) -> !torch.vtensor<[3,4],bf16> return %0 : !torch.vtensor<[3,4],bf16> } } diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_BFLOAT16_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_BFLOAT16_expanded/model.mlir index 282ae8133..fef6da7bc 100644 --- a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_BFLOAT16_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_BFLOAT16_expanded/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_castlike_FLOAT_to_BFLOAT16_expanded(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],bf16>) -> !torch.vtensor<[3,4],bf16> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 16 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],bf16> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 16 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],bf16> return %0 : !torch.vtensor<[3,4],bf16> } } diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_DOUBLE/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_DOUBLE/model.mlir index b3100f862..5c03e6676 100644 --- a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_DOUBLE/model.mlir +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_DOUBLE/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_castlike_FLOAT_to_DOUBLE(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],f64>) -> !torch.vtensor<[3,4],f64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],f64>) -> !torch.vtensor<[3,4],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],f64>) -> !torch.vtensor<[3,4],f64> return %0 : !torch.vtensor<[3,4],f64> } } diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_DOUBLE_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_DOUBLE_expanded/model.mlir index 134ac2a6f..a361ebb72 100644 --- a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_DOUBLE_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_DOUBLE_expanded/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_castlike_FLOAT_to_DOUBLE_expanded(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],f64>) -> !torch.vtensor<[3,4],f64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f64> return %0 : !torch.vtensor<[3,4],f64> } } diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT16/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT16/model.mlir index f680283e0..b5b419086 100644 --- a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT16/model.mlir +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_castlike_FLOAT_to_FLOAT16(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],f16>) -> !torch.vtensor<[3,4],f16> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],f16>) -> !torch.vtensor<[3,4],f16> + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],f16>) -> !torch.vtensor<[3,4],f16> return %0 : !torch.vtensor<[3,4],f16> } } diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT16_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT16_expanded/model.mlir index ea87165c4..f6342d922 100644 --- a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT16_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT16_expanded/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_castlike_FLOAT_to_FLOAT16_expanded(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],f16>) -> !torch.vtensor<[3,4],f16> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 10 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f16> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 10 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f16> return %0 : !torch.vtensor<[3,4],f16> } } diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN/input_0.npy new file mode 100644 index 000000000..cf5f4645d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN/input_1.npy new file mode 100644 index 000000000..ce0222503 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN/model.mlir new file mode 100644 index 000000000..7892dea44 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT_to_FLOAT8E4M3FN(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],f8E4M3FN>) -> !torch.vtensor<[3,4],f8E4M3FN> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],f8E4M3FN>) -> !torch.vtensor<[3,4],f8E4M3FN> + return %0 : !torch.vtensor<[3,4],f8E4M3FN> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN/output_0.npy new file mode 100644 index 000000000..7ac4b86a7 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ/input_0.npy new file mode 100644 index 000000000..cf5f4645d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ/input_1.npy new file mode 100644 index 000000000..ce0222503 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ/model.mlir new file mode 100644 index 000000000..4bf5a30d2 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT_to_FLOAT8E4M3FNUZ(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],f8E5M2FNUZ>) -> !torch.vtensor<[3,4],f8E5M2FNUZ> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],f8E5M2FNUZ>) -> !torch.vtensor<[3,4],f8E5M2FNUZ> + return %0 : !torch.vtensor<[3,4],f8E5M2FNUZ> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ/output_0.npy new file mode 100644 index 000000000..a2ee45a4e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded/input_0.npy new file mode 100644 index 000000000..cf5f4645d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded/input_1.npy new file mode 100644 index 000000000..ce0222503 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded/model.mlir new file mode 100644 index 000000000..a08e0f464 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],f8E5M2FNUZ>) -> !torch.vtensor<[3,4],f8E5M2FNUZ> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 18 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f8E5M2FNUZ> + return %0 : !torch.vtensor<[3,4],f8E5M2FNUZ> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded/output_0.npy new file mode 100644 index 000000000..a2ee45a4e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded/input_0.npy new file mode 100644 index 000000000..cf5f4645d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded/input_1.npy new file mode 100644 index 000000000..ce0222503 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded/model.mlir new file mode 100644 index 000000000..fcab37b43 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],f8E4M3FN>) -> !torch.vtensor<[3,4],f8E4M3FN> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 17 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f8E4M3FN> + return %0 : !torch.vtensor<[3,4],f8E4M3FN> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded/output_0.npy new file mode 100644 index 000000000..7ac4b86a7 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2/input_0.npy new file mode 100644 index 000000000..cf5f4645d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2/input_1.npy new file mode 100644 index 000000000..af8a234e1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2/model.mlir new file mode 100644 index 000000000..ec0b3a887 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT_to_FLOAT8E5M2(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],f8E5M2>) -> !torch.vtensor<[3,4],f8E5M2> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],f8E5M2>) -> !torch.vtensor<[3,4],f8E5M2> + return %0 : !torch.vtensor<[3,4],f8E5M2> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2/output_0.npy new file mode 100644 index 000000000..761e13d3f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ/input_0.npy new file mode 100644 index 000000000..cf5f4645d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ/input_1.npy new file mode 100644 index 000000000..af8a234e1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ/model.mlir new file mode 100644 index 000000000..8ba811056 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT_to_FLOAT8E5M2FNUZ(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],f8E5M2FNUZ>) -> !torch.vtensor<[3,4],f8E5M2FNUZ> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],f8E5M2FNUZ>) -> !torch.vtensor<[3,4],f8E5M2FNUZ> + return %0 : !torch.vtensor<[3,4],f8E5M2FNUZ> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ/output_0.npy new file mode 100644 index 000000000..761e13d3f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded/input_0.npy new file mode 100644 index 000000000..cf5f4645d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded/input_1.npy new file mode 100644 index 000000000..af8a234e1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded/model.mlir new file mode 100644 index 000000000..a769ba2f1 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],f8E5M2FNUZ>) -> !torch.vtensor<[3,4],f8E5M2FNUZ> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 20 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f8E5M2FNUZ> + return %0 : !torch.vtensor<[3,4],f8E5M2FNUZ> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded/output_0.npy new file mode 100644 index 000000000..761e13d3f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2_expanded/input_0.npy new file mode 100644 index 000000000..cf5f4645d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2_expanded/input_1.npy new file mode 100644 index 000000000..af8a234e1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2_expanded/model.mlir new file mode 100644 index 000000000..f5c3ee71b --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2_expanded/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT_to_FLOAT8E5M2_expanded(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],f8E5M2>) -> !torch.vtensor<[3,4],f8E5M2> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 19 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f8E5M2> + return %0 : !torch.vtensor<[3,4],f8E5M2> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2_expanded/output_0.npy new file mode 100644 index 000000000..761e13d3f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_FLOAT8E5M2_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING/input_0.npy new file mode 100644 index 000000000..a1ea94a5a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING/input_1.npy new file mode 100644 index 000000000..cc7eb0b05 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING/model.mlir new file mode 100644 index 000000000..d584bab72 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT_to_STRING(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],!torch.str>) -> !torch.vtensor<[3,4],!torch.str> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],!torch.str>) -> !torch.vtensor<[3,4],!torch.str> + return %0 : !torch.vtensor<[3,4],!torch.str> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING/output_0.npy new file mode 100644 index 000000000..9c4779909 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING_expanded/input_0.npy new file mode 100644 index 000000000..a1ea94a5a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING_expanded/input_1.npy new file mode 100644 index 000000000..cc7eb0b05 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING_expanded/model.mlir new file mode 100644 index 000000000..328fd8684 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING_expanded/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_FLOAT_to_STRING_expanded(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],!torch.str>) -> !torch.vtensor<[3,4],!torch.str> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 8 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],!torch.str> + return %0 : !torch.vtensor<[3,4],!torch.str> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING_expanded/output_0.npy new file mode 100644 index 000000000..9c4779909 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_FLOAT_to_STRING_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT/input_0.npy new file mode 100644 index 000000000..b52101d9c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT/input_1.npy new file mode 100644 index 000000000..698233853 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT/model.mlir b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT/model.mlir new file mode 100644 index 000000000..de635d62c --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_STRING_to_FLOAT(%arg0: !torch.vtensor<[3,4],!torch.str>, %arg1: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.CastLike"(%arg0, %arg1) : (!torch.vtensor<[3,4],!torch.str>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> + return %0 : !torch.vtensor<[3,4],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT/output_0.npy new file mode 100644 index 000000000..cf5f4645d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT_expanded/input_0.npy new file mode 100644 index 000000000..b52101d9c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT_expanded/input_1.npy new file mode 100644 index 000000000..698233853 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT_expanded/model.mlir b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT_expanded/model.mlir new file mode 100644 index 000000000..7b24feca0 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT_expanded/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_castlike_STRING_to_FLOAT_expanded(%arg0: !torch.vtensor<[3,4],!torch.str>, %arg1: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.saturate = 1 : si64, torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],!torch.str>) -> !torch.vtensor<[3,4],f32> + return %0 : !torch.vtensor<[3,4],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT_expanded/output_0.npy new file mode 100644 index 000000000..cf5f4645d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_castlike_STRING_to_FLOAT_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_ceil/model.mlir b/iree_tests/onnx/node/generated/test_ceil/model.mlir index 43faded4a..63b5d458b 100644 --- a/iree_tests/onnx/node/generated/test_ceil/model.mlir +++ b/iree_tests/onnx/node/generated/test_ceil/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_ceil(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Ceil"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Ceil"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_ceil_example/model.mlir b/iree_tests/onnx/node/generated/test_ceil_example/model.mlir index 2ae608da3..c8400f595 100644 --- a/iree_tests/onnx/node/generated/test_ceil_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_ceil_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_ceil_example(%arg0: !torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Ceil"(%arg0) : (!torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Ceil"(%arg0) : (!torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> return %0 : !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_celu/model.mlir b/iree_tests/onnx/node/generated/test_celu/model.mlir index fe39dc4e9..8b6e4f3b3 100644 --- a/iree_tests/onnx/node/generated/test_celu/model.mlir +++ b/iree_tests/onnx/node/generated/test_celu/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_celu(%arg0: !torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Celu"(%arg0) {torch.onnx.alpha = 2.000000e+00 : f32} : (!torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Celu"(%arg0) {torch.onnx.alpha = 2.000000e+00 : f32} : (!torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> return %0 : !torch.vtensor<[3,3,3,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_celu_expanded/model.mlir b/iree_tests/onnx/node/generated/test_celu_expanded/model.mlir index f623cbe6c..59e8940d4 100644 --- a/iree_tests/onnx/node/generated/test_celu_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_celu_expanded/model.mlir @@ -1,9 +1,10 @@ module { func.func @test_celu_expanded(%arg0: !torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<2.000000e+00> : tensor<1xf32>) : !torch.vtensor<[1],f32> - %1 = torch.operator "onnx.Div"(%arg0, %0) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,3,3,1],f32> - %2 = torch.operator "onnx.Elu"(%1) {torch.onnx.alpha = 1.000000e+00 : f32} : (!torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> - %3 = torch.operator "onnx.Mul"(%0, %2) : (!torch.vtensor<[1],f32>, !torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2.000000e+00> : tensor<1xf32>} : () -> !torch.vtensor<[1],f32> + %1 = torch.operator "onnx.Div"(%arg0, %0) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,3,3,1],f32> + %2 = torch.operator "onnx.Elu"(%1) {torch.onnx.alpha = 1.000000e+00 : f32} : (!torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> + %3 = torch.operator "onnx.Mul"(%0, %2) : (!torch.vtensor<[1],f32>, !torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> return %3 : !torch.vtensor<[3,3,3,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop/model.mlir b/iree_tests/onnx/node/generated/test_center_crop_pad_crop/model.mlir index c58f06d43..22930aed5 100644 --- a/iree_tests/onnx/node/generated/test_center_crop_pad_crop/model.mlir +++ b/iree_tests/onnx/node/generated/test_center_crop_pad_crop/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_center_crop_pad_crop(%arg0: !torch.vtensor<[20,10,3],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[10,7,3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CenterCropPad"(%arg0, %arg1) : (!torch.vtensor<[20,10,3],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[10,7,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.CenterCropPad"(%arg0, %arg1) : (!torch.vtensor<[20,10,3],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[10,7,3],f32> return %0 : !torch.vtensor<[10,7,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_and_pad/model.mlir b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_and_pad/model.mlir index ef8684ddd..be9432529 100644 --- a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_and_pad/model.mlir +++ b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_and_pad/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_center_crop_pad_crop_and_pad(%arg0: !torch.vtensor<[20,8,3],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[10,10,3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CenterCropPad"(%arg0, %arg1) : (!torch.vtensor<[20,8,3],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[10,10,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.CenterCropPad"(%arg0, %arg1) : (!torch.vtensor<[20,8,3],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[10,10,3],f32> return %0 : !torch.vtensor<[10,10,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_and_pad_expanded/model.mlir b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_and_pad_expanded/model.mlir index 6c20b107a..0ea5bc1d9 100644 --- a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_and_pad_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_and_pad_expanded/model.mlir @@ -1,18 +1,19 @@ module { func.func @test_center_crop_pad_crop_and_pad_expanded(%arg0: !torch.vtensor<[20,8,3],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[10,10,3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<2> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[20,8,3],f32>) -> !torch.vtensor<[3],si64> - %2 = torch.operator "onnx.Max"(%1, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> - %3 = torch.operator "onnx.Sub"(%2, %1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> - %4 = torch.operator "onnx.Div"(%3, %0) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> - %5 = torch.operator "onnx.Sub"(%3, %4) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> - %6 = torch.operator "onnx.Concat"(%4, %5) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[6],si64> - %7 = torch.operator "onnx.Pad"(%arg0, %6) : (!torch.vtensor<[20,8,3],f32>, !torch.vtensor<[6],si64>) -> !torch.vtensor<[?,?,?],f32> - %8 = torch.operator "onnx.Shape"(%7) : (!torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[3],si64> - %9 = torch.operator "onnx.Sub"(%8, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> - %10 = torch.operator "onnx.Div"(%9, %0) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> - %11 = torch.operator "onnx.Add"(%10, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> - %12 = torch.operator "onnx.Slice"(%7, %10, %11) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[10,10,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[20,8,3],f32>) -> !torch.vtensor<[3],si64> + %2 = torch.operator "onnx.Max"(%1, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Sub"(%2, %1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %4 = torch.operator "onnx.Div"(%3, %0) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> + %5 = torch.operator "onnx.Sub"(%3, %4) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %6 = torch.operator "onnx.Concat"(%4, %5) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[6],si64> + %7 = torch.operator "onnx.Pad"(%arg0, %6) : (!torch.vtensor<[20,8,3],f32>, !torch.vtensor<[6],si64>) -> !torch.vtensor<[?,?,?],f32> + %8 = torch.operator "onnx.Shape"(%7) : (!torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[3],si64> + %9 = torch.operator "onnx.Sub"(%8, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %10 = torch.operator "onnx.Div"(%9, %0) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> + %11 = torch.operator "onnx.Add"(%10, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %12 = torch.operator "onnx.Slice"(%7, %10, %11) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[10,10,3],f32> return %12 : !torch.vtensor<[10,10,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw/model.mlir b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw/model.mlir index e5b2efcd1..21a669ee4 100644 --- a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw/model.mlir +++ b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_center_crop_pad_crop_axes_chw(%arg0: !torch.vtensor<[3,20,8],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,10,9],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CenterCropPad"(%arg0, %arg1) {torch.onnx.axes = [1 : si64, 2 : si64]} : (!torch.vtensor<[3,20,8],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,10,9],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.CenterCropPad"(%arg0, %arg1) {torch.onnx.axes = [1 : si64, 2 : si64]} : (!torch.vtensor<[3,20,8],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,10,9],f32> return %0 : !torch.vtensor<[3,10,9],f32> } } diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw_expanded/input_0.npy new file mode 100644 index 000000000..0374fb147 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw_expanded/input_1.npy new file mode 100644 index 000000000..1a48fecd0 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw_expanded/model.mlir b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw_expanded/model.mlir new file mode 100644 index 000000000..6c38a4088 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw_expanded/model.mlir @@ -0,0 +1,23 @@ +module { + func.func @test_center_crop_pad_crop_axes_chw_expanded(%arg0: !torch.vtensor<[3,20,8],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,10,9],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [1 : si64, 2 : si64]} : () -> !torch.vtensor<[2],si64> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,20,8],f32>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Gather"(%2, %1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %4 = torch.operator "onnx.Max"(%3, %arg1) : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %5 = torch.operator "onnx.Sub"(%4, %3) : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Div"(%5, %0) : (!torch.vtensor<[2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2],si64> + %7 = torch.operator "onnx.Sub"(%5, %6) : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %8 = torch.operator "onnx.Concat"(%6, %7) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[4],si64> + %9 = torch.operator "onnx.Pad"(%arg0, %8, %none, %1) : (!torch.vtensor<[3,20,8],f32>, !torch.vtensor<[4],si64>, !torch.none, !torch.vtensor<[2],si64>) -> !torch.vtensor<[?,?,?],f32> + %10 = torch.operator "onnx.Shape"(%9) : (!torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[3],si64> + %11 = torch.operator "onnx.Gather"(%10, %1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %12 = torch.operator "onnx.Sub"(%11, %arg1) : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %13 = torch.operator "onnx.Div"(%12, %0) : (!torch.vtensor<[2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2],si64> + %14 = torch.operator "onnx.Add"(%13, %arg1) : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %15 = torch.operator "onnx.Slice"(%9, %13, %14, %1) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,10,9],f32> + return %15 : !torch.vtensor<[3,10,9],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw_expanded/output_0.npy new file mode 100644 index 000000000..db8e7dc93 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_chw_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc/model.mlir b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc/model.mlir index 031c32642..9c382ea02 100644 --- a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc/model.mlir +++ b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_center_crop_pad_crop_axes_hwc(%arg0: !torch.vtensor<[20,8,3],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[10,9,3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CenterCropPad"(%arg0, %arg1) {torch.onnx.axes = [0 : si64, 1 : si64]} : (!torch.vtensor<[20,8,3],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[10,9,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.CenterCropPad"(%arg0, %arg1) {torch.onnx.axes = [0 : si64, 1 : si64]} : (!torch.vtensor<[20,8,3],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[10,9,3],f32> return %0 : !torch.vtensor<[10,9,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc_expanded/input_0.npy new file mode 100644 index 000000000..9dd9fb1d4 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc_expanded/input_1.npy new file mode 100644 index 000000000..1a48fecd0 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc_expanded/model.mlir b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc_expanded/model.mlir new file mode 100644 index 000000000..72190f85f --- /dev/null +++ b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc_expanded/model.mlir @@ -0,0 +1,23 @@ +module { + func.func @test_center_crop_pad_crop_axes_hwc_expanded(%arg0: !torch.vtensor<[20,8,3],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[10,9,3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [0 : si64, 1 : si64]} : () -> !torch.vtensor<[2],si64> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[20,8,3],f32>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Gather"(%2, %1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %4 = torch.operator "onnx.Max"(%3, %arg1) : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %5 = torch.operator "onnx.Sub"(%4, %3) : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Div"(%5, %0) : (!torch.vtensor<[2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2],si64> + %7 = torch.operator "onnx.Sub"(%5, %6) : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %8 = torch.operator "onnx.Concat"(%6, %7) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[4],si64> + %9 = torch.operator "onnx.Pad"(%arg0, %8, %none, %1) : (!torch.vtensor<[20,8,3],f32>, !torch.vtensor<[4],si64>, !torch.none, !torch.vtensor<[2],si64>) -> !torch.vtensor<[?,?,?],f32> + %10 = torch.operator "onnx.Shape"(%9) : (!torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[3],si64> + %11 = torch.operator "onnx.Gather"(%10, %1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %12 = torch.operator "onnx.Sub"(%11, %arg1) : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %13 = torch.operator "onnx.Div"(%12, %0) : (!torch.vtensor<[2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2],si64> + %14 = torch.operator "onnx.Add"(%13, %arg1) : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %15 = torch.operator "onnx.Slice"(%9, %13, %14, %1) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[10,9,3],f32> + return %15 : !torch.vtensor<[10,9,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc_expanded/output_0.npy new file mode 100644 index 000000000..29dea0c4b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_axes_hwc_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_expanded/model.mlir b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_expanded/model.mlir index 35052f577..af14aa471 100644 --- a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_expanded/model.mlir @@ -1,18 +1,19 @@ module { func.func @test_center_crop_pad_crop_expanded(%arg0: !torch.vtensor<[20,10,3],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[10,7,3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<2> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[20,10,3],f32>) -> !torch.vtensor<[3],si64> - %2 = torch.operator "onnx.Max"(%1, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> - %3 = torch.operator "onnx.Sub"(%2, %1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> - %4 = torch.operator "onnx.Div"(%3, %0) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> - %5 = torch.operator "onnx.Sub"(%3, %4) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> - %6 = torch.operator "onnx.Concat"(%4, %5) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[6],si64> - %7 = torch.operator "onnx.Pad"(%arg0, %6) : (!torch.vtensor<[20,10,3],f32>, !torch.vtensor<[6],si64>) -> !torch.vtensor<[?,?,?],f32> - %8 = torch.operator "onnx.Shape"(%7) : (!torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[3],si64> - %9 = torch.operator "onnx.Sub"(%8, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> - %10 = torch.operator "onnx.Div"(%9, %0) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> - %11 = torch.operator "onnx.Add"(%10, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> - %12 = torch.operator "onnx.Slice"(%7, %10, %11) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[10,7,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[20,10,3],f32>) -> !torch.vtensor<[3],si64> + %2 = torch.operator "onnx.Max"(%1, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Sub"(%2, %1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %4 = torch.operator "onnx.Div"(%3, %0) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> + %5 = torch.operator "onnx.Sub"(%3, %4) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %6 = torch.operator "onnx.Concat"(%4, %5) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[6],si64> + %7 = torch.operator "onnx.Pad"(%arg0, %6) : (!torch.vtensor<[20,10,3],f32>, !torch.vtensor<[6],si64>) -> !torch.vtensor<[?,?,?],f32> + %8 = torch.operator "onnx.Shape"(%7) : (!torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[3],si64> + %9 = torch.operator "onnx.Sub"(%8, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %10 = torch.operator "onnx.Div"(%9, %0) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> + %11 = torch.operator "onnx.Add"(%10, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %12 = torch.operator "onnx.Slice"(%7, %10, %11) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[10,7,3],f32> return %12 : !torch.vtensor<[10,7,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc/model.mlir b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc/model.mlir index d28728354..27e245ea9 100644 --- a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc/model.mlir +++ b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_center_crop_pad_crop_negative_axes_hwc(%arg0: !torch.vtensor<[20,8,3],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[10,9,3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CenterCropPad"(%arg0, %arg1) {torch.onnx.axes = [-3 : si64, -2 : si64]} : (!torch.vtensor<[20,8,3],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[10,9,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.CenterCropPad"(%arg0, %arg1) {torch.onnx.axes = [-3 : si64, -2 : si64]} : (!torch.vtensor<[20,8,3],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[10,9,3],f32> return %0 : !torch.vtensor<[10,9,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc_expanded/input_0.npy new file mode 100644 index 000000000..9dd9fb1d4 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc_expanded/input_1.npy new file mode 100644 index 000000000..1a48fecd0 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc_expanded/model.mlir b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc_expanded/model.mlir new file mode 100644 index 000000000..3469a9d17 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc_expanded/model.mlir @@ -0,0 +1,23 @@ +module { + func.func @test_center_crop_pad_crop_negative_axes_hwc_expanded(%arg0: !torch.vtensor<[20,8,3],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[10,9,3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [-3 : si64, -2 : si64]} : () -> !torch.vtensor<[2],si64> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[20,8,3],f32>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Gather"(%2, %1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %4 = torch.operator "onnx.Max"(%3, %arg1) : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %5 = torch.operator "onnx.Sub"(%4, %3) : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Div"(%5, %0) : (!torch.vtensor<[2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2],si64> + %7 = torch.operator "onnx.Sub"(%5, %6) : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %8 = torch.operator "onnx.Concat"(%6, %7) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[4],si64> + %9 = torch.operator "onnx.Pad"(%arg0, %8, %none, %1) : (!torch.vtensor<[20,8,3],f32>, !torch.vtensor<[4],si64>, !torch.none, !torch.vtensor<[2],si64>) -> !torch.vtensor<[?,?,?],f32> + %10 = torch.operator "onnx.Shape"(%9) : (!torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[3],si64> + %11 = torch.operator "onnx.Gather"(%10, %1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %12 = torch.operator "onnx.Sub"(%11, %arg1) : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %13 = torch.operator "onnx.Div"(%12, %0) : (!torch.vtensor<[2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2],si64> + %14 = torch.operator "onnx.Add"(%13, %arg1) : (!torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2],si64> + %15 = torch.operator "onnx.Slice"(%9, %13, %14, %1) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[10,9,3],f32> + return %15 : !torch.vtensor<[10,9,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc_expanded/output_0.npy new file mode 100644 index 000000000..29dea0c4b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc_expanded/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_center_crop_pad_crop_negative_axes_hwc_expanded/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_pad/model.mlir b/iree_tests/onnx/node/generated/test_center_crop_pad_pad/model.mlir index 3b6849762..f1283b980 100644 --- a/iree_tests/onnx/node/generated/test_center_crop_pad_pad/model.mlir +++ b/iree_tests/onnx/node/generated/test_center_crop_pad_pad/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_center_crop_pad_pad(%arg0: !torch.vtensor<[10,7,3],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[20,10,3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CenterCropPad"(%arg0, %arg1) : (!torch.vtensor<[10,7,3],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[20,10,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.CenterCropPad"(%arg0, %arg1) : (!torch.vtensor<[10,7,3],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[20,10,3],f32> return %0 : !torch.vtensor<[20,10,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_center_crop_pad_pad_expanded/model.mlir b/iree_tests/onnx/node/generated/test_center_crop_pad_pad_expanded/model.mlir index 947ad66f3..54a9e8ab7 100644 --- a/iree_tests/onnx/node/generated/test_center_crop_pad_pad_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_center_crop_pad_pad_expanded/model.mlir @@ -1,18 +1,19 @@ module { func.func @test_center_crop_pad_pad_expanded(%arg0: !torch.vtensor<[10,7,3],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[20,10,3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<2> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[10,7,3],f32>) -> !torch.vtensor<[3],si64> - %2 = torch.operator "onnx.Max"(%1, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> - %3 = torch.operator "onnx.Sub"(%2, %1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> - %4 = torch.operator "onnx.Div"(%3, %0) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> - %5 = torch.operator "onnx.Sub"(%3, %4) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> - %6 = torch.operator "onnx.Concat"(%4, %5) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[6],si64> - %7 = torch.operator "onnx.Pad"(%arg0, %6) : (!torch.vtensor<[10,7,3],f32>, !torch.vtensor<[6],si64>) -> !torch.vtensor<[?,?,?],f32> - %8 = torch.operator "onnx.Shape"(%7) : (!torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[3],si64> - %9 = torch.operator "onnx.Sub"(%8, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> - %10 = torch.operator "onnx.Div"(%9, %0) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> - %11 = torch.operator "onnx.Add"(%10, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> - %12 = torch.operator "onnx.Slice"(%7, %10, %11) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[20,10,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[10,7,3],f32>) -> !torch.vtensor<[3],si64> + %2 = torch.operator "onnx.Max"(%1, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Sub"(%2, %1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %4 = torch.operator "onnx.Div"(%3, %0) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> + %5 = torch.operator "onnx.Sub"(%3, %4) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %6 = torch.operator "onnx.Concat"(%4, %5) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[6],si64> + %7 = torch.operator "onnx.Pad"(%arg0, %6) : (!torch.vtensor<[10,7,3],f32>, !torch.vtensor<[6],si64>) -> !torch.vtensor<[?,?,?],f32> + %8 = torch.operator "onnx.Shape"(%7) : (!torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[3],si64> + %9 = torch.operator "onnx.Sub"(%8, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %10 = torch.operator "onnx.Div"(%9, %0) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> + %11 = torch.operator "onnx.Add"(%10, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %12 = torch.operator "onnx.Slice"(%7, %10, %11) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[20,10,3],f32> return %12 : !torch.vtensor<[20,10,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_clip/model.mlir b/iree_tests/onnx/node/generated/test_clip/model.mlir index e0f6bf374..28b36bc80 100644 --- a/iree_tests/onnx/node/generated/test_clip/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_clip(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Clip"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Clip"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_clip_default_inbounds/input_0.npy b/iree_tests/onnx/node/generated/test_clip_default_inbounds/input_0.npy new file mode 100644 index 000000000..ee47dffa6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_clip_default_inbounds/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_clip_default_inbounds/model.mlir b/iree_tests/onnx/node/generated/test_clip_default_inbounds/model.mlir new file mode 100644 index 000000000..47c727d49 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_clip_default_inbounds/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_clip_default_inbounds(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Clip"(%arg0, %none, %none) : (!torch.vtensor<[3],f32>, !torch.none, !torch.none) -> !torch.vtensor<[3],f32> + return %0 : !torch.vtensor<[3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_clip_default_inbounds/output_0.npy b/iree_tests/onnx/node/generated/test_clip_default_inbounds/output_0.npy new file mode 100644 index 000000000..ee47dffa6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_clip_default_inbounds/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_clip_default_inbounds/test_data_flags.txt b/iree_tests/onnx/node/generated/test_clip_default_inbounds/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_clip_default_inbounds/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_clip_default_inbounds_expanded/model.mlir b/iree_tests/onnx/node/generated/test_clip_default_inbounds_expanded/model.mlir index c2b5077c5..525511b46 100644 --- a/iree_tests/onnx/node/generated/test_clip_default_inbounds_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_default_inbounds_expanded/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_clip_default_inbounds_expanded(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Identity"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Identity"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_clip_default_int8_inbounds/input_0.npy b/iree_tests/onnx/node/generated/test_clip_default_int8_inbounds/input_0.npy new file mode 100644 index 000000000..6eda09fb8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_clip_default_int8_inbounds/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_clip_default_int8_inbounds/model.mlir b/iree_tests/onnx/node/generated/test_clip_default_int8_inbounds/model.mlir new file mode 100644 index 000000000..4d89e1aeb --- /dev/null +++ b/iree_tests/onnx/node/generated/test_clip_default_int8_inbounds/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_clip_default_int8_inbounds(%arg0: !torch.vtensor<[3],si8>) -> !torch.vtensor<[3],si8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Clip"(%arg0, %none, %none) : (!torch.vtensor<[3],si8>, !torch.none, !torch.none) -> !torch.vtensor<[3],si8> + return %0 : !torch.vtensor<[3],si8> + } +} + diff --git a/iree_tests/onnx/node/generated/test_clip_default_int8_inbounds/output_0.npy b/iree_tests/onnx/node/generated/test_clip_default_int8_inbounds/output_0.npy new file mode 100644 index 000000000..6eda09fb8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_clip_default_int8_inbounds/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_clip_default_int8_inbounds/test_data_flags.txt b/iree_tests/onnx/node/generated/test_clip_default_int8_inbounds/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_clip_default_int8_inbounds/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_clip_default_int8_inbounds_expanded/model.mlir b/iree_tests/onnx/node/generated/test_clip_default_int8_inbounds_expanded/model.mlir index 727490b79..8bd8febf0 100644 --- a/iree_tests/onnx/node/generated/test_clip_default_int8_inbounds_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_default_int8_inbounds_expanded/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_clip_default_int8_inbounds_expanded(%arg0: !torch.vtensor<[3],si8>) -> !torch.vtensor<[3],si8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Identity"(%arg0) : (!torch.vtensor<[3],si8>) -> !torch.vtensor<[3],si8> + %none = torch.constant.none + %0 = torch.operator "onnx.Identity"(%arg0) : (!torch.vtensor<[3],si8>) -> !torch.vtensor<[3],si8> return %0 : !torch.vtensor<[3],si8> } } diff --git a/iree_tests/onnx/node/generated/test_clip_default_int8_max/input_0.npy b/iree_tests/onnx/node/generated/test_clip_default_int8_max/input_0.npy new file mode 100644 index 000000000..c0bc83ed3 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_clip_default_int8_max/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_clip_default_int8_max/input_1.npy b/iree_tests/onnx/node/generated/test_clip_default_int8_max/input_1.npy new file mode 100644 index 000000000..d1c44fea8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_clip_default_int8_max/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_clip_default_int8_max/model.mlir b/iree_tests/onnx/node/generated/test_clip_default_int8_max/model.mlir new file mode 100644 index 000000000..ccbc4d6c0 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_clip_default_int8_max/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_clip_default_int8_max(%arg0: !torch.vtensor<[3,4,5],si8>, %arg1: !torch.vtensor<[],si8>) -> !torch.vtensor<[3,4,5],si8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Clip"(%arg0, %none, %arg1) : (!torch.vtensor<[3,4,5],si8>, !torch.none, !torch.vtensor<[],si8>) -> !torch.vtensor<[3,4,5],si8> + return %0 : !torch.vtensor<[3,4,5],si8> + } +} + diff --git a/iree_tests/onnx/node/generated/test_clip_default_int8_max/output_0.npy b/iree_tests/onnx/node/generated/test_clip_default_int8_max/output_0.npy new file mode 100644 index 000000000..ef9a182c7 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_clip_default_int8_max/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_clip_default_int8_max/test_data_flags.txt b/iree_tests/onnx/node/generated/test_clip_default_int8_max/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_clip_default_int8_max/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_clip_default_int8_max_expanded/model.mlir b/iree_tests/onnx/node/generated/test_clip_default_int8_max_expanded/model.mlir index 9c5713161..53292d707 100644 --- a/iree_tests/onnx/node/generated/test_clip_default_int8_max_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_default_int8_max_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_clip_default_int8_max_expanded(%arg0: !torch.vtensor<[3,4,5],si8>, %arg1: !torch.vtensor<[],si8>) -> !torch.vtensor<[3,4,5],si8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Less"(%arg1, %arg0) : (!torch.vtensor<[],si8>, !torch.vtensor<[3,4,5],si8>) -> !torch.vtensor<[3,4,5],i1> - %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[],si8>, !torch.vtensor<[3,4,5],si8>) -> !torch.vtensor<[3,4,5],si8> + %none = torch.constant.none + %0 = torch.operator "onnx.Less"(%arg1, %arg0) : (!torch.vtensor<[],si8>, !torch.vtensor<[3,4,5],si8>) -> !torch.vtensor<[3,4,5],i1> + %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[],si8>, !torch.vtensor<[3,4,5],si8>) -> !torch.vtensor<[3,4,5],si8> return %1 : !torch.vtensor<[3,4,5],si8> } } diff --git a/iree_tests/onnx/node/generated/test_clip_default_int8_min/model.mlir b/iree_tests/onnx/node/generated/test_clip_default_int8_min/model.mlir index 0e7d087db..5c7a4b959 100644 --- a/iree_tests/onnx/node/generated/test_clip_default_int8_min/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_default_int8_min/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_clip_default_int8_min(%arg0: !torch.vtensor<[3,4,5],si8>, %arg1: !torch.vtensor<[],si8>) -> !torch.vtensor<[3,4,5],si8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Clip"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],si8>, !torch.vtensor<[],si8>) -> !torch.vtensor<[3,4,5],si8> + %none = torch.constant.none + %0 = torch.operator "onnx.Clip"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],si8>, !torch.vtensor<[],si8>) -> !torch.vtensor<[3,4,5],si8> return %0 : !torch.vtensor<[3,4,5],si8> } } diff --git a/iree_tests/onnx/node/generated/test_clip_default_int8_min_expanded/model.mlir b/iree_tests/onnx/node/generated/test_clip_default_int8_min_expanded/model.mlir index 7ce919524..401688328 100644 --- a/iree_tests/onnx/node/generated/test_clip_default_int8_min_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_default_int8_min_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_clip_default_int8_min_expanded(%arg0: !torch.vtensor<[3,4,5],si8>, %arg1: !torch.vtensor<[],si8>) -> !torch.vtensor<[3,4,5],si8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],si8>, !torch.vtensor<[],si8>) -> !torch.vtensor<[3,4,5],i1> - %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[],si8>, !torch.vtensor<[3,4,5],si8>) -> !torch.vtensor<[3,4,5],si8> + %none = torch.constant.none + %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],si8>, !torch.vtensor<[],si8>) -> !torch.vtensor<[3,4,5],i1> + %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[],si8>, !torch.vtensor<[3,4,5],si8>) -> !torch.vtensor<[3,4,5],si8> return %1 : !torch.vtensor<[3,4,5],si8> } } diff --git a/iree_tests/onnx/node/generated/test_clip_default_max/input_0.npy b/iree_tests/onnx/node/generated/test_clip_default_max/input_0.npy new file mode 100644 index 000000000..68c2f70ff Binary files /dev/null and b/iree_tests/onnx/node/generated/test_clip_default_max/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_clip_default_max/input_1.npy b/iree_tests/onnx/node/generated/test_clip_default_max/input_1.npy new file mode 100644 index 000000000..57df8cc3b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_clip_default_max/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_clip_default_max/model.mlir b/iree_tests/onnx/node/generated/test_clip_default_max/model.mlir new file mode 100644 index 000000000..8ba5240a5 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_clip_default_max/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_clip_default_max(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Clip"(%arg0, %none, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.none, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + return %0 : !torch.vtensor<[3,4,5],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_clip_default_max/output_0.npy b/iree_tests/onnx/node/generated/test_clip_default_max/output_0.npy new file mode 100644 index 000000000..6fa59794b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_clip_default_max/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_clip_default_max/test_data_flags.txt b/iree_tests/onnx/node/generated/test_clip_default_max/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_clip_default_max/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_clip_default_max_expanded/model.mlir b/iree_tests/onnx/node/generated/test_clip_default_max_expanded/model.mlir index 32692ce52..b5f70e48e 100644 --- a/iree_tests/onnx/node/generated/test_clip_default_max_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_default_max_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_clip_default_max_expanded(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Less"(%arg1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> - %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Less"(%arg1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> + %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %1 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_clip_default_min/model.mlir b/iree_tests/onnx/node/generated/test_clip_default_min/model.mlir index 1562a7baa..e5abe1ef7 100644 --- a/iree_tests/onnx/node/generated/test_clip_default_min/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_default_min/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_clip_default_min(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Clip"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Clip"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_clip_default_min_expanded/model.mlir b/iree_tests/onnx/node/generated/test_clip_default_min_expanded/model.mlir index 27d5e0a63..eb2b0205d 100644 --- a/iree_tests/onnx/node/generated/test_clip_default_min_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_default_min_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_clip_default_min_expanded(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> - %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> + %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %1 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_clip_example/model.mlir b/iree_tests/onnx/node/generated/test_clip_example/model.mlir index 53926c478..5f33e9136 100644 --- a/iree_tests/onnx/node/generated/test_clip_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_clip_example(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Clip"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Clip"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_clip_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_clip_example_expanded/model.mlir index e56b49c24..0fa131d18 100644 --- a/iree_tests/onnx/node/generated/test_clip_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_example_expanded/model.mlir @@ -1,9 +1,10 @@ module { func.func @test_clip_example_expanded(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],i1> - %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %2 = torch.operator "onnx.Less"(%arg2, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],i1> - %3 = torch.operator "onnx.Where"(%2, %arg2, %1) : (!torch.vtensor<[3],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],i1> + %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %2 = torch.operator "onnx.Less"(%arg2, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],i1> + %3 = torch.operator "onnx.Where"(%2, %arg2, %1) : (!torch.vtensor<[3],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %3 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_clip_expanded/model.mlir b/iree_tests/onnx/node/generated/test_clip_expanded/model.mlir index 826614a1a..64806a97d 100644 --- a/iree_tests/onnx/node/generated/test_clip_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_expanded/model.mlir @@ -1,9 +1,10 @@ module { func.func @test_clip_expanded(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> - %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %2 = torch.operator "onnx.Less"(%arg2, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> - %3 = torch.operator "onnx.Where"(%2, %arg2, %1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> + %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %2 = torch.operator "onnx.Less"(%arg2, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> + %3 = torch.operator "onnx.Where"(%2, %arg2, %1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %3 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_clip_inbounds/model.mlir b/iree_tests/onnx/node/generated/test_clip_inbounds/model.mlir index 6e588aaac..ea19764f6 100644 --- a/iree_tests/onnx/node/generated/test_clip_inbounds/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_inbounds/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_clip_inbounds(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Clip"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Clip"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_clip_inbounds_expanded/model.mlir b/iree_tests/onnx/node/generated/test_clip_inbounds_expanded/model.mlir index 7e6e7282a..35b1d6c59 100644 --- a/iree_tests/onnx/node/generated/test_clip_inbounds_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_inbounds_expanded/model.mlir @@ -1,9 +1,10 @@ module { func.func @test_clip_inbounds_expanded(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],i1> - %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %2 = torch.operator "onnx.Less"(%arg2, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],i1> - %3 = torch.operator "onnx.Where"(%2, %arg2, %1) : (!torch.vtensor<[3],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],i1> + %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %2 = torch.operator "onnx.Less"(%arg2, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],i1> + %3 = torch.operator "onnx.Where"(%2, %arg2, %1) : (!torch.vtensor<[3],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %3 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_clip_outbounds/model.mlir b/iree_tests/onnx/node/generated/test_clip_outbounds/model.mlir index 7ffde2e59..d4f99ccd6 100644 --- a/iree_tests/onnx/node/generated/test_clip_outbounds/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_outbounds/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_clip_outbounds(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Clip"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Clip"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_clip_outbounds_expanded/model.mlir b/iree_tests/onnx/node/generated/test_clip_outbounds_expanded/model.mlir index cafd298ef..037efdf9a 100644 --- a/iree_tests/onnx/node/generated/test_clip_outbounds_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_outbounds_expanded/model.mlir @@ -1,9 +1,10 @@ module { func.func @test_clip_outbounds_expanded(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],i1> - %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %2 = torch.operator "onnx.Less"(%arg2, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],i1> - %3 = torch.operator "onnx.Where"(%2, %arg2, %1) : (!torch.vtensor<[3],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],i1> + %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %2 = torch.operator "onnx.Less"(%arg2, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],i1> + %3 = torch.operator "onnx.Where"(%2, %arg2, %1) : (!torch.vtensor<[3],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %3 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_clip_splitbounds/model.mlir b/iree_tests/onnx/node/generated/test_clip_splitbounds/model.mlir index 5ef898ea1..26834f091 100644 --- a/iree_tests/onnx/node/generated/test_clip_splitbounds/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_splitbounds/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_clip_splitbounds(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Clip"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Clip"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_clip_splitbounds_expanded/model.mlir b/iree_tests/onnx/node/generated/test_clip_splitbounds_expanded/model.mlir index 326ab9473..fe932d45a 100644 --- a/iree_tests/onnx/node/generated/test_clip_splitbounds_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_clip_splitbounds_expanded/model.mlir @@ -1,9 +1,10 @@ module { func.func @test_clip_splitbounds_expanded(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],i1> - %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %2 = torch.operator "onnx.Less"(%arg2, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],i1> - %3 = torch.operator "onnx.Where"(%2, %arg2, %1) : (!torch.vtensor<[3],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],i1> + %1 = torch.operator "onnx.Where"(%0, %arg1, %arg0) : (!torch.vtensor<[3],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %2 = torch.operator "onnx.Less"(%arg2, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],i1> + %3 = torch.operator "onnx.Where"(%2, %arg2, %1) : (!torch.vtensor<[3],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %3 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_col2im/model.mlir b/iree_tests/onnx/node/generated/test_col2im/model.mlir index b84fb07bd..801660255 100644 --- a/iree_tests/onnx/node/generated/test_col2im/model.mlir +++ b/iree_tests/onnx/node/generated/test_col2im/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_col2im(%arg0: !torch.vtensor<[1,5,5],f32>, %arg1: !torch.vtensor<[2],si64>, %arg2: !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,5,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Col2Im"(%arg0, %arg1, %arg2) : (!torch.vtensor<[1,5,5],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,5,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Col2Im"(%arg0, %arg1, %arg2) : (!torch.vtensor<[1,5,5],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,5,5],f32> return %0 : !torch.vtensor<[1,1,5,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_col2im_5d/model.mlir b/iree_tests/onnx/node/generated/test_col2im_5d/model.mlir index bbfc2a0a2..5d9585687 100644 --- a/iree_tests/onnx/node/generated/test_col2im_5d/model.mlir +++ b/iree_tests/onnx/node/generated/test_col2im_5d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_col2im_5d(%arg0: !torch.vtensor<[1,10,12],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[3],si64>) -> !torch.vtensor<[1,2,3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Col2Im"(%arg0, %arg1, %arg2) : (!torch.vtensor<[1,10,12],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[1,2,3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Col2Im"(%arg0, %arg1, %arg2) : (!torch.vtensor<[1,10,12],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[1,2,3,4,5],f32> return %0 : !torch.vtensor<[1,2,3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_col2im_dilations/model.mlir b/iree_tests/onnx/node/generated/test_col2im_dilations/model.mlir index d1bd9ff05..a5b9e5542 100644 --- a/iree_tests/onnx/node/generated/test_col2im_dilations/model.mlir +++ b/iree_tests/onnx/node/generated/test_col2im_dilations/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_col2im_dilations(%arg0: !torch.vtensor<[1,4,5],f32>, %arg1: !torch.vtensor<[2],si64>, %arg2: !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,6,6],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Col2Im"(%arg0, %arg1, %arg2) {torch.onnx.dilations = [1 : si64, 5 : si64]} : (!torch.vtensor<[1,4,5],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,6,6],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Col2Im"(%arg0, %arg1, %arg2) {torch.onnx.dilations = [1 : si64, 5 : si64]} : (!torch.vtensor<[1,4,5],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,6,6],f32> return %0 : !torch.vtensor<[1,1,6,6],f32> } } diff --git a/iree_tests/onnx/node/generated/test_col2im_pads/model.mlir b/iree_tests/onnx/node/generated/test_col2im_pads/model.mlir index 0dae7a19a..7417a47d3 100644 --- a/iree_tests/onnx/node/generated/test_col2im_pads/model.mlir +++ b/iree_tests/onnx/node/generated/test_col2im_pads/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_col2im_pads(%arg0: !torch.vtensor<[1,5,15],f32>, %arg1: !torch.vtensor<[2],si64>, %arg2: !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,5,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Col2Im"(%arg0, %arg1, %arg2) {torch.onnx.pads = [0 : si64, 1 : si64, 0 : si64, 1 : si64]} : (!torch.vtensor<[1,5,15],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,5,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Col2Im"(%arg0, %arg1, %arg2) {torch.onnx.pads = [0 : si64, 1 : si64, 0 : si64, 1 : si64]} : (!torch.vtensor<[1,5,15],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,5,5],f32> return %0 : !torch.vtensor<[1,1,5,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_col2im_strides/model.mlir b/iree_tests/onnx/node/generated/test_col2im_strides/model.mlir index ff0fba2fd..cc35109b7 100644 --- a/iree_tests/onnx/node/generated/test_col2im_strides/model.mlir +++ b/iree_tests/onnx/node/generated/test_col2im_strides/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_col2im_strides(%arg0: !torch.vtensor<[1,9,4],f32>, %arg1: !torch.vtensor<[2],si64>, %arg2: !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,5,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Col2Im"(%arg0, %arg1, %arg2) {torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,9,4],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,5,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Col2Im"(%arg0, %arg1, %arg2) {torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,9,4],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,5,5],f32> return %0 : !torch.vtensor<[1,1,5,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_compress_0/model.mlir b/iree_tests/onnx/node/generated/test_compress_0/model.mlir index 4ec4d100a..e16cb201c 100644 --- a/iree_tests/onnx/node/generated/test_compress_0/model.mlir +++ b/iree_tests/onnx/node/generated/test_compress_0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_compress_0(%arg0: !torch.vtensor<[3,2],f32>, %arg1: !torch.vtensor<[3],i1>) -> !torch.vtensor<[2,2],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Compress"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,2],f32>, !torch.vtensor<[3],i1>) -> !torch.vtensor<[2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Compress"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,2],f32>, !torch.vtensor<[3],i1>) -> !torch.vtensor<[2,2],f32> return %0 : !torch.vtensor<[2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_compress_1/model.mlir b/iree_tests/onnx/node/generated/test_compress_1/model.mlir index d838bb9a7..0a730fb91 100644 --- a/iree_tests/onnx/node/generated/test_compress_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_compress_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_compress_1(%arg0: !torch.vtensor<[3,2],f32>, %arg1: !torch.vtensor<[2],i1>) -> !torch.vtensor<[3,1],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Compress"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,2],f32>, !torch.vtensor<[2],i1>) -> !torch.vtensor<[3,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Compress"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,2],f32>, !torch.vtensor<[2],i1>) -> !torch.vtensor<[3,1],f32> return %0 : !torch.vtensor<[3,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_compress_default_axis/model.mlir b/iree_tests/onnx/node/generated/test_compress_default_axis/model.mlir index 5b95569bc..73b48236a 100644 --- a/iree_tests/onnx/node/generated/test_compress_default_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_compress_default_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_compress_default_axis(%arg0: !torch.vtensor<[3,2],f32>, %arg1: !torch.vtensor<[5],i1>) -> !torch.vtensor<[2],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Compress"(%arg0, %arg1) : (!torch.vtensor<[3,2],f32>, !torch.vtensor<[5],i1>) -> !torch.vtensor<[2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Compress"(%arg0, %arg1) : (!torch.vtensor<[3,2],f32>, !torch.vtensor<[5],i1>) -> !torch.vtensor<[2],f32> return %0 : !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_compress_negative_axis/model.mlir b/iree_tests/onnx/node/generated/test_compress_negative_axis/model.mlir index a3489b8ae..9e44afee0 100644 --- a/iree_tests/onnx/node/generated/test_compress_negative_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_compress_negative_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_compress_negative_axis(%arg0: !torch.vtensor<[3,2],f32>, %arg1: !torch.vtensor<[2],i1>) -> !torch.vtensor<[3,1],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Compress"(%arg0, %arg1) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[3,2],f32>, !torch.vtensor<[2],i1>) -> !torch.vtensor<[3,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Compress"(%arg0, %arg1) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[3,2],f32>, !torch.vtensor<[2],i1>) -> !torch.vtensor<[3,1],f32> return %0 : !torch.vtensor<[3,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_concat_1d_axis_0/model.mlir b/iree_tests/onnx/node/generated/test_concat_1d_axis_0/model.mlir index c44aec8e5..bf6247fb0 100644 --- a/iree_tests/onnx/node/generated/test_concat_1d_axis_0/model.mlir +++ b/iree_tests/onnx/node/generated/test_concat_1d_axis_0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_concat_1d_axis_0(%arg0: !torch.vtensor<[2],f32>, %arg1: !torch.vtensor<[2],f32>) -> !torch.vtensor<[4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) -> !torch.vtensor<[4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) -> !torch.vtensor<[4],f32> return %0 : !torch.vtensor<[4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_concat_1d_axis_negative_1/model.mlir b/iree_tests/onnx/node/generated/test_concat_1d_axis_negative_1/model.mlir index c9f687f66..52a05dfc3 100644 --- a/iree_tests/onnx/node/generated/test_concat_1d_axis_negative_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_concat_1d_axis_negative_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_concat_1d_axis_negative_1(%arg0: !torch.vtensor<[2],f32>, %arg1: !torch.vtensor<[2],f32>) -> !torch.vtensor<[4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) -> !torch.vtensor<[4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) -> !torch.vtensor<[4],f32> return %0 : !torch.vtensor<[4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_concat_2d_axis_0/model.mlir b/iree_tests/onnx/node/generated/test_concat_2d_axis_0/model.mlir index 0da71d979..b7fc8d02f 100644 --- a/iree_tests/onnx/node/generated/test_concat_2d_axis_0/model.mlir +++ b/iree_tests/onnx/node/generated/test_concat_2d_axis_0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_concat_2d_axis_0(%arg0: !torch.vtensor<[2,2],f32>, %arg1: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[4,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[4,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[4,2],f32> return %0 : !torch.vtensor<[4,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_concat_2d_axis_1/model.mlir b/iree_tests/onnx/node/generated/test_concat_2d_axis_1/model.mlir index 184c35811..71c00906a 100644 --- a/iree_tests/onnx/node/generated/test_concat_2d_axis_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_concat_2d_axis_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_concat_2d_axis_1(%arg0: !torch.vtensor<[2,2],f32>, %arg1: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,4],f32> return %0 : !torch.vtensor<[2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_concat_2d_axis_negative_1/model.mlir b/iree_tests/onnx/node/generated/test_concat_2d_axis_negative_1/model.mlir index 569f12e0b..ad4ce8897 100644 --- a/iree_tests/onnx/node/generated/test_concat_2d_axis_negative_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_concat_2d_axis_negative_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_concat_2d_axis_negative_1(%arg0: !torch.vtensor<[2,2],f32>, %arg1: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,4],f32> return %0 : !torch.vtensor<[2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_concat_2d_axis_negative_2/model.mlir b/iree_tests/onnx/node/generated/test_concat_2d_axis_negative_2/model.mlir index 4145dbe16..adf48cf2f 100644 --- a/iree_tests/onnx/node/generated/test_concat_2d_axis_negative_2/model.mlir +++ b/iree_tests/onnx/node/generated/test_concat_2d_axis_negative_2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_concat_2d_axis_negative_2(%arg0: !torch.vtensor<[2,2],f32>, %arg1: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[4,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[4,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[4,2],f32> return %0 : !torch.vtensor<[4,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_concat_3d_axis_0/model.mlir b/iree_tests/onnx/node/generated/test_concat_3d_axis_0/model.mlir index 806508747..4e0e3e657 100644 --- a/iree_tests/onnx/node/generated/test_concat_3d_axis_0/model.mlir +++ b/iree_tests/onnx/node/generated/test_concat_3d_axis_0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_concat_3d_axis_0(%arg0: !torch.vtensor<[2,2,2],f32>, %arg1: !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[4,2,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,2,2],f32>, !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[4,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,2,2],f32>, !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[4,2,2],f32> return %0 : !torch.vtensor<[4,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_concat_3d_axis_1/model.mlir b/iree_tests/onnx/node/generated/test_concat_3d_axis_1/model.mlir index 48352ba8b..d25e5147d 100644 --- a/iree_tests/onnx/node/generated/test_concat_3d_axis_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_concat_3d_axis_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_concat_3d_axis_1(%arg0: !torch.vtensor<[2,2,2],f32>, %arg1: !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[2,4,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,2,2],f32>, !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[2,4,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,2,2],f32>, !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[2,4,2],f32> return %0 : !torch.vtensor<[2,4,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_concat_3d_axis_2/model.mlir b/iree_tests/onnx/node/generated/test_concat_3d_axis_2/model.mlir index f9736d808..23d91addd 100644 --- a/iree_tests/onnx/node/generated/test_concat_3d_axis_2/model.mlir +++ b/iree_tests/onnx/node/generated/test_concat_3d_axis_2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_concat_3d_axis_2(%arg0: !torch.vtensor<[2,2,2],f32>, %arg1: !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[2,2,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[2,2,2],f32>, !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[2,2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[2,2,2],f32>, !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[2,2,4],f32> return %0 : !torch.vtensor<[2,2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_concat_3d_axis_negative_1/model.mlir b/iree_tests/onnx/node/generated/test_concat_3d_axis_negative_1/model.mlir index 99963fc0e..c4886a1b4 100644 --- a/iree_tests/onnx/node/generated/test_concat_3d_axis_negative_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_concat_3d_axis_negative_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_concat_3d_axis_negative_1(%arg0: !torch.vtensor<[2,2,2],f32>, %arg1: !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[2,2,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[2,2,2],f32>, !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[2,2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[2,2,2],f32>, !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[2,2,4],f32> return %0 : !torch.vtensor<[2,2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_concat_3d_axis_negative_2/model.mlir b/iree_tests/onnx/node/generated/test_concat_3d_axis_negative_2/model.mlir index 865096628..d28a5e362 100644 --- a/iree_tests/onnx/node/generated/test_concat_3d_axis_negative_2/model.mlir +++ b/iree_tests/onnx/node/generated/test_concat_3d_axis_negative_2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_concat_3d_axis_negative_2(%arg0: !torch.vtensor<[2,2,2],f32>, %arg1: !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[2,4,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[2,2,2],f32>, !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[2,4,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[2,2,2],f32>, !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[2,4,2],f32> return %0 : !torch.vtensor<[2,4,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_concat_3d_axis_negative_3/model.mlir b/iree_tests/onnx/node/generated/test_concat_3d_axis_negative_3/model.mlir index cf1f05c5a..faf2c985d 100644 --- a/iree_tests/onnx/node/generated/test_concat_3d_axis_negative_3/model.mlir +++ b/iree_tests/onnx/node/generated/test_concat_3d_axis_negative_3/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_concat_3d_axis_negative_3(%arg0: !torch.vtensor<[2,2,2],f32>, %arg1: !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[4,2,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = -3 : si64} : (!torch.vtensor<[2,2,2],f32>, !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[4,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Concat"(%arg0, %arg1) {torch.onnx.axis = -3 : si64} : (!torch.vtensor<[2,2,2],f32>, !torch.vtensor<[2,2,2],f32>) -> !torch.vtensor<[4,2,2],f32> return %0 : !torch.vtensor<[4,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_constant/model.mlir b/iree_tests/onnx/node/generated/test_constant/model.mlir index 4f9a22eb2..f8e61ded0 100644 --- a/iree_tests/onnx/node/generated/test_constant/model.mlir +++ b/iree_tests/onnx/node/generated/test_constant/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_constant() -> !torch.vtensor<[5,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[[1.76405239, 0.400157213, 9.787380e-01, 2.24089313, 1.867558], [-0.977277874, 0.950088441, -0.151357204, -0.103218853, 0.410598516], [0.144043565, 1.45427346, 0.761037707, 0.121675014, 0.443863243], [0.333674341, 1.49407911, -0.205158263, 0.313067704, -0.854095757], [-2.55298972, 0.653618574, 0.864436209, -7.421650e-01, 2.26975465]]> : tensor<5x5xf32>) : !torch.vtensor<[5,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[[1.76405239, 0.400157213, 9.787380e-01, 2.24089313, 1.867558], [-0.977277874, 0.950088441, -0.151357204, -0.103218853, 0.410598516], [0.144043565, 1.45427346, 0.761037707, 0.121675014, 0.443863243], [0.333674341, 1.49407911, -0.205158263, 0.313067704, -0.854095757], [-2.55298972, 0.653618574, 0.864436209, -7.421650e-01, 2.26975465]]> : tensor<5x5xf32>} : () -> !torch.vtensor<[5,5],f32> return %0 : !torch.vtensor<[5,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_constant_pad/model.mlir b/iree_tests/onnx/node/generated/test_constant_pad/model.mlir index 05ee7c049..663def1ca 100644 --- a/iree_tests/onnx/node/generated/test_constant_pad/model.mlir +++ b/iree_tests/onnx/node/generated/test_constant_pad/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_constant_pad(%arg0: !torch.vtensor<[1,3,4,5],f32>, %arg1: !torch.vtensor<[8],si64>, %arg2: !torch.vtensor<[],f32>) -> !torch.vtensor<[1,3,7,12],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pad"(%arg0, %arg1, %arg2) {torch.onnx.mode = "constant"} : (!torch.vtensor<[1,3,4,5],f32>, !torch.vtensor<[8],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,3,7,12],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Pad"(%arg0, %arg1, %arg2) {torch.onnx.mode = "constant"} : (!torch.vtensor<[1,3,4,5],f32>, !torch.vtensor<[8],si64>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,3,7,12],f32> return %0 : !torch.vtensor<[1,3,7,12],f32> } } diff --git a/iree_tests/onnx/node/generated/test_constant_pad_axes/model.mlir b/iree_tests/onnx/node/generated/test_constant_pad_axes/model.mlir index 69b881fc5..98eaab78f 100644 --- a/iree_tests/onnx/node/generated/test_constant_pad_axes/model.mlir +++ b/iree_tests/onnx/node/generated/test_constant_pad_axes/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_constant_pad_axes(%arg0: !torch.vtensor<[1,3,4,5],f32>, %arg1: !torch.vtensor<[4],si64>, %arg2: !torch.vtensor<[],f32>, %arg3: !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,3,4,12],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pad"(%arg0, %arg1, %arg2, %arg3) {torch.onnx.mode = "constant"} : (!torch.vtensor<[1,3,4,5],f32>, !torch.vtensor<[4],si64>, !torch.vtensor<[],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,3,4,12],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Pad"(%arg0, %arg1, %arg2, %arg3) {torch.onnx.mode = "constant"} : (!torch.vtensor<[1,3,4,5],f32>, !torch.vtensor<[4],si64>, !torch.vtensor<[],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,3,4,12],f32> return %0 : !torch.vtensor<[1,3,4,12],f32> } } diff --git a/iree_tests/onnx/node/generated/test_constant_pad_negative_axes/model.mlir b/iree_tests/onnx/node/generated/test_constant_pad_negative_axes/model.mlir index 81ec5751a..da3c37566 100644 --- a/iree_tests/onnx/node/generated/test_constant_pad_negative_axes/model.mlir +++ b/iree_tests/onnx/node/generated/test_constant_pad_negative_axes/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_constant_pad_negative_axes(%arg0: !torch.vtensor<[1,3,4,5],f32>, %arg1: !torch.vtensor<[4],si64>, %arg2: !torch.vtensor<[],f32>, %arg3: !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,3,4,12],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pad"(%arg0, %arg1, %arg2, %arg3) {torch.onnx.mode = "constant"} : (!torch.vtensor<[1,3,4,5],f32>, !torch.vtensor<[4],si64>, !torch.vtensor<[],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,3,4,12],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Pad"(%arg0, %arg1, %arg2, %arg3) {torch.onnx.mode = "constant"} : (!torch.vtensor<[1,3,4,5],f32>, !torch.vtensor<[4],si64>, !torch.vtensor<[],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,3,4,12],f32> return %0 : !torch.vtensor<[1,3,4,12],f32> } } diff --git a/iree_tests/onnx/node/generated/test_constantofshape_float_ones/input_0.npy b/iree_tests/onnx/node/generated/test_constantofshape_float_ones/input_0.npy new file mode 100644 index 000000000..0f1c5b3c0 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_constantofshape_float_ones/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_constantofshape_float_ones/model.mlir b/iree_tests/onnx/node/generated/test_constantofshape_float_ones/model.mlir new file mode 100644 index 000000000..116db0183 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_constantofshape_float_ones/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_constantofshape_float_ones(%arg0: !torch.vtensor<[3],si64>) -> !torch.vtensor<[4,3,2],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.ConstantOfShape"(%arg0) {torch.onnx.value = dense<1.000000e+00> : tensor<1xf32>} : (!torch.vtensor<[3],si64>) -> !torch.vtensor<[4,3,2],f32> + return %0 : !torch.vtensor<[4,3,2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_constantofshape_float_ones/output_0.npy b/iree_tests/onnx/node/generated/test_constantofshape_float_ones/output_0.npy new file mode 100644 index 000000000..c001c796e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_constantofshape_float_ones/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_constantofshape_float_ones/test_data_flags.txt b/iree_tests/onnx/node/generated/test_constantofshape_float_ones/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_constantofshape_float_ones/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_constantofshape_int_shape_zero/input_0.npy b/iree_tests/onnx/node/generated/test_constantofshape_int_shape_zero/input_0.npy new file mode 100644 index 000000000..8d15fe27e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_constantofshape_int_shape_zero/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_constantofshape_int_shape_zero/model.mlir b/iree_tests/onnx/node/generated/test_constantofshape_int_shape_zero/model.mlir new file mode 100644 index 000000000..3aa5b2335 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_constantofshape_int_shape_zero/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_constantofshape_int_shape_zero(%arg0: !torch.vtensor<[1],si64>) -> !torch.vtensor<[0],si32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.ConstantOfShape"(%arg0) {torch.onnx.value = dense<0> : tensor<1xsi32>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[0],si32> + return %0 : !torch.vtensor<[0],si32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_constantofshape_int_shape_zero/output_0.npy b/iree_tests/onnx/node/generated/test_constantofshape_int_shape_zero/output_0.npy new file mode 100644 index 000000000..8a8e0f82d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_constantofshape_int_shape_zero/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_constantofshape_int_shape_zero/test_data_flags.txt b/iree_tests/onnx/node/generated/test_constantofshape_int_shape_zero/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_constantofshape_int_shape_zero/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_constantofshape_int_zeros/input_0.npy b/iree_tests/onnx/node/generated/test_constantofshape_int_zeros/input_0.npy new file mode 100644 index 000000000..9b28577bb Binary files /dev/null and b/iree_tests/onnx/node/generated/test_constantofshape_int_zeros/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_constantofshape_int_zeros/model.mlir b/iree_tests/onnx/node/generated/test_constantofshape_int_zeros/model.mlir new file mode 100644 index 000000000..fd88a83bd --- /dev/null +++ b/iree_tests/onnx/node/generated/test_constantofshape_int_zeros/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_constantofshape_int_zeros(%arg0: !torch.vtensor<[2],si64>) -> !torch.vtensor<[10,6],si32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.ConstantOfShape"(%arg0) {torch.onnx.value = dense<0> : tensor<1xsi32>} : (!torch.vtensor<[2],si64>) -> !torch.vtensor<[10,6],si32> + return %0 : !torch.vtensor<[10,6],si32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_constantofshape_int_zeros/output_0.npy b/iree_tests/onnx/node/generated/test_constantofshape_int_zeros/output_0.npy new file mode 100644 index 000000000..b371bf9b3 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_constantofshape_int_zeros/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_constantofshape_int_zeros/test_data_flags.txt b/iree_tests/onnx/node/generated/test_constantofshape_int_zeros/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_constantofshape_int_zeros/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_conv_with_autopad_same/model.mlir b/iree_tests/onnx/node/generated/test_conv_with_autopad_same/model.mlir index 4d20bd9ca..8257f91b1 100644 --- a/iree_tests/onnx/node/generated/test_conv_with_autopad_same/model.mlir +++ b/iree_tests/onnx/node/generated/test_conv_with_autopad_same/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_conv_with_autopad_same(%arg0: !torch.vtensor<[1,1,5,5],f32>, %arg1: !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,3,3],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Conv"(%arg0, %arg1) {torch.onnx.auto_pad = "SAME_LOWER", torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>, !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,3,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Conv"(%arg0, %arg1) {torch.onnx.auto_pad = "SAME_LOWER", torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>, !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,3,3],f32> return %0 : !torch.vtensor<[1,1,3,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_conv_with_strides_and_asymmetric_padding/model.mlir b/iree_tests/onnx/node/generated/test_conv_with_strides_and_asymmetric_padding/model.mlir index 11c12cbfe..31a72cef5 100644 --- a/iree_tests/onnx/node/generated/test_conv_with_strides_and_asymmetric_padding/model.mlir +++ b/iree_tests/onnx/node/generated/test_conv_with_strides_and_asymmetric_padding/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_conv_with_strides_and_asymmetric_padding(%arg0: !torch.vtensor<[1,1,7,5],f32>, %arg1: !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,4,2],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Conv"(%arg0, %arg1) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.pads = [1 : si64, 0 : si64, 1 : si64, 0 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,7,5],f32>, !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,4,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Conv"(%arg0, %arg1) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.pads = [1 : si64, 0 : si64, 1 : si64, 0 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,7,5],f32>, !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,4,2],f32> return %0 : !torch.vtensor<[1,1,4,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_conv_with_strides_no_padding/model.mlir b/iree_tests/onnx/node/generated/test_conv_with_strides_no_padding/model.mlir index f287bac47..c644e6ce5 100644 --- a/iree_tests/onnx/node/generated/test_conv_with_strides_no_padding/model.mlir +++ b/iree_tests/onnx/node/generated/test_conv_with_strides_no_padding/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_conv_with_strides_no_padding(%arg0: !torch.vtensor<[1,1,7,5],f32>, %arg1: !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,3,2],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Conv"(%arg0, %arg1) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.pads = [0 : si64, 0 : si64, 0 : si64, 0 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,7,5],f32>, !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Conv"(%arg0, %arg1) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.pads = [0 : si64, 0 : si64, 0 : si64, 0 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,7,5],f32>, !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,3,2],f32> return %0 : !torch.vtensor<[1,1,3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_conv_with_strides_padding/model.mlir b/iree_tests/onnx/node/generated/test_conv_with_strides_padding/model.mlir index 19abc77a3..e9c3fe21a 100644 --- a/iree_tests/onnx/node/generated/test_conv_with_strides_padding/model.mlir +++ b/iree_tests/onnx/node/generated/test_conv_with_strides_padding/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_conv_with_strides_padding(%arg0: !torch.vtensor<[1,1,7,5],f32>, %arg1: !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,4,3],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Conv"(%arg0, %arg1) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.pads = [1 : si64, 1 : si64, 1 : si64, 1 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,7,5],f32>, !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,4,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Conv"(%arg0, %arg1) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.pads = [1 : si64, 1 : si64, 1 : si64, 1 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,7,5],f32>, !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,4,3],f32> return %0 : !torch.vtensor<[1,1,4,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_convinteger_with_padding/model.mlir b/iree_tests/onnx/node/generated/test_convinteger_with_padding/model.mlir index 792be1fd0..f02968f36 100644 --- a/iree_tests/onnx/node/generated/test_convinteger_with_padding/model.mlir +++ b/iree_tests/onnx/node/generated/test_convinteger_with_padding/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_convinteger_with_padding(%arg0: !torch.vtensor<[1,1,3,3],ui8>, %arg1: !torch.vtensor<[1,1,2,2],ui8>, %arg2: !torch.vtensor<[],ui8>) -> !torch.vtensor<[1,1,4,4],si32> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ConvInteger"(%arg0, %arg1, %arg2) {torch.onnx.pads = [1 : si64, 1 : si64, 1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,3,3],ui8>, !torch.vtensor<[1,1,2,2],ui8>, !torch.vtensor<[],ui8>) -> !torch.vtensor<[1,1,4,4],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.ConvInteger"(%arg0, %arg1, %arg2) {torch.onnx.pads = [1 : si64, 1 : si64, 1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,3,3],ui8>, !torch.vtensor<[1,1,2,2],ui8>, !torch.vtensor<[],ui8>) -> !torch.vtensor<[1,1,4,4],si32> return %0 : !torch.vtensor<[1,1,4,4],si32> } } diff --git a/iree_tests/onnx/node/generated/test_convinteger_without_padding/model.mlir b/iree_tests/onnx/node/generated/test_convinteger_without_padding/model.mlir index ca4a4ffee..7b4615d79 100644 --- a/iree_tests/onnx/node/generated/test_convinteger_without_padding/model.mlir +++ b/iree_tests/onnx/node/generated/test_convinteger_without_padding/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_convinteger_without_padding(%arg0: !torch.vtensor<[1,1,3,3],ui8>, %arg1: !torch.vtensor<[1,1,2,2],ui8>, %arg2: !torch.vtensor<[],ui8>) -> !torch.vtensor<[1,1,2,2],si32> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ConvInteger"(%arg0, %arg1, %arg2) : (!torch.vtensor<[1,1,3,3],ui8>, !torch.vtensor<[1,1,2,2],ui8>, !torch.vtensor<[],ui8>) -> !torch.vtensor<[1,1,2,2],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.ConvInteger"(%arg0, %arg1, %arg2) : (!torch.vtensor<[1,1,3,3],ui8>, !torch.vtensor<[1,1,2,2],ui8>, !torch.vtensor<[],ui8>) -> !torch.vtensor<[1,1,2,2],si32> return %0 : !torch.vtensor<[1,1,2,2],si32> } } diff --git a/iree_tests/onnx/node/generated/test_convtranspose/model.mlir b/iree_tests/onnx/node/generated/test_convtranspose/model.mlir index 2bbcd06d8..4e78286f3 100644 --- a/iree_tests/onnx/node/generated/test_convtranspose/model.mlir +++ b/iree_tests/onnx/node/generated/test_convtranspose/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_convtranspose(%arg0: !torch.vtensor<[1,1,3,3],f32>, %arg1: !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,5,5],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,5,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,5,5],f32> return %0 : !torch.vtensor<[1,2,5,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_convtranspose_1d/model.mlir b/iree_tests/onnx/node/generated/test_convtranspose_1d/model.mlir index c5d01f905..3a8d30590 100644 --- a/iree_tests/onnx/node/generated/test_convtranspose_1d/model.mlir +++ b/iree_tests/onnx/node/generated/test_convtranspose_1d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_convtranspose_1d(%arg0: !torch.vtensor<[1,1,3],f32>, %arg1: !torch.vtensor<[1,2,3],f32>) -> !torch.vtensor<[1,2,5],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) : (!torch.vtensor<[1,1,3],f32>, !torch.vtensor<[1,2,3],f32>) -> !torch.vtensor<[1,2,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) : (!torch.vtensor<[1,1,3],f32>, !torch.vtensor<[1,2,3],f32>) -> !torch.vtensor<[1,2,5],f32> return %0 : !torch.vtensor<[1,2,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_convtranspose_3d/model.mlir b/iree_tests/onnx/node/generated/test_convtranspose_3d/model.mlir index 87f8444e3..bf81efeef 100644 --- a/iree_tests/onnx/node/generated/test_convtranspose_3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_convtranspose_3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_convtranspose_3d(%arg0: !torch.vtensor<[1,1,3,4,5],f32>, %arg1: !torch.vtensor<[1,2,3,3,3],f32>) -> !torch.vtensor<[1,2,5,6,7],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) : (!torch.vtensor<[1,1,3,4,5],f32>, !torch.vtensor<[1,2,3,3,3],f32>) -> !torch.vtensor<[1,2,5,6,7],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) : (!torch.vtensor<[1,1,3,4,5],f32>, !torch.vtensor<[1,2,3,3,3],f32>) -> !torch.vtensor<[1,2,5,6,7],f32> return %0 : !torch.vtensor<[1,2,5,6,7],f32> } } diff --git a/iree_tests/onnx/node/generated/test_convtranspose_autopad_same/model.mlir b/iree_tests/onnx/node/generated/test_convtranspose_autopad_same/model.mlir index 9a2fdc0b0..2695ff383 100644 --- a/iree_tests/onnx/node/generated/test_convtranspose_autopad_same/model.mlir +++ b/iree_tests/onnx/node/generated/test_convtranspose_autopad_same/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_convtranspose_autopad_same(%arg0: !torch.vtensor<[1,1,3,3],f32>, %arg1: !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,6,6],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) {torch.onnx.auto_pad = "SAME_UPPER", torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,6,6],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) {torch.onnx.auto_pad = "SAME_UPPER", torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,6,6],f32> return %0 : !torch.vtensor<[1,2,6,6],f32> } } diff --git a/iree_tests/onnx/node/generated/test_convtranspose_dilations/model.mlir b/iree_tests/onnx/node/generated/test_convtranspose_dilations/model.mlir index 3203072e6..0e73f427e 100644 --- a/iree_tests/onnx/node/generated/test_convtranspose_dilations/model.mlir +++ b/iree_tests/onnx/node/generated/test_convtranspose_dilations/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_convtranspose_dilations(%arg0: !torch.vtensor<[1,1,3,3],f32>, %arg1: !torch.vtensor<[1,1,2,2],f32>) -> !torch.vtensor<[1,1,5,5],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) {torch.onnx.dilations = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,1,2,2],f32>) -> !torch.vtensor<[1,1,5,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) {torch.onnx.dilations = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,1,2,2],f32>) -> !torch.vtensor<[1,1,5,5],f32> return %0 : !torch.vtensor<[1,1,5,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_convtranspose_kernel_shape/model.mlir b/iree_tests/onnx/node/generated/test_convtranspose_kernel_shape/model.mlir index cbdf9ec07..7d020e864 100644 --- a/iree_tests/onnx/node/generated/test_convtranspose_kernel_shape/model.mlir +++ b/iree_tests/onnx/node/generated/test_convtranspose_kernel_shape/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_convtranspose_kernel_shape(%arg0: !torch.vtensor<[1,1,3,3],f32>, %arg1: !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,10,8],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.output_padding = [1 : si64, 1 : si64], torch.onnx.output_shape = [10 : si64, 8 : si64], torch.onnx.strides = [3 : si64, 2 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,10,8],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.output_padding = [1 : si64, 1 : si64], torch.onnx.output_shape = [10 : si64, 8 : si64], torch.onnx.strides = [3 : si64, 2 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,10,8],f32> return %0 : !torch.vtensor<[1,2,10,8],f32> } } diff --git a/iree_tests/onnx/node/generated/test_convtranspose_output_shape/model.mlir b/iree_tests/onnx/node/generated/test_convtranspose_output_shape/model.mlir index 72ea5f305..4812fc41b 100644 --- a/iree_tests/onnx/node/generated/test_convtranspose_output_shape/model.mlir +++ b/iree_tests/onnx/node/generated/test_convtranspose_output_shape/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_convtranspose_output_shape(%arg0: !torch.vtensor<[1,1,3,3],f32>, %arg1: !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,10,8],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) {torch.onnx.output_shape = [10 : si64, 8 : si64], torch.onnx.strides = [3 : si64, 2 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,10,8],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) {torch.onnx.output_shape = [10 : si64, 8 : si64], torch.onnx.strides = [3 : si64, 2 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,10,8],f32> return %0 : !torch.vtensor<[1,2,10,8],f32> } } diff --git a/iree_tests/onnx/node/generated/test_convtranspose_pad/model.mlir b/iree_tests/onnx/node/generated/test_convtranspose_pad/model.mlir index 480c89a19..c9acdf7eb 100644 --- a/iree_tests/onnx/node/generated/test_convtranspose_pad/model.mlir +++ b/iree_tests/onnx/node/generated/test_convtranspose_pad/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_convtranspose_pad(%arg0: !torch.vtensor<[1,1,3,3],f32>, %arg1: !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,10,8],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) {torch.onnx.output_padding = [1 : si64, 1 : si64], torch.onnx.strides = [3 : si64, 2 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,10,8],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) {torch.onnx.output_padding = [1 : si64, 1 : si64], torch.onnx.strides = [3 : si64, 2 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,10,8],f32> return %0 : !torch.vtensor<[1,2,10,8],f32> } } diff --git a/iree_tests/onnx/node/generated/test_convtranspose_pads/model.mlir b/iree_tests/onnx/node/generated/test_convtranspose_pads/model.mlir index e87780e5a..1fd779983 100644 --- a/iree_tests/onnx/node/generated/test_convtranspose_pads/model.mlir +++ b/iree_tests/onnx/node/generated/test_convtranspose_pads/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_convtranspose_pads(%arg0: !torch.vtensor<[1,1,3,3],f32>, %arg1: !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,7,3],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) {torch.onnx.pads = [1 : si64, 2 : si64, 1 : si64, 2 : si64], torch.onnx.strides = [3 : si64, 2 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,7,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ConvTranspose"(%arg0, %arg1) {torch.onnx.pads = [1 : si64, 2 : si64, 1 : si64, 2 : si64], torch.onnx.strides = [3 : si64, 2 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,2,3,3],f32>) -> !torch.vtensor<[1,2,7,3],f32> return %0 : !torch.vtensor<[1,2,7,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_cos/model.mlir b/iree_tests/onnx/node/generated/test_cos/model.mlir index 8209773e5..02631402c 100644 --- a/iree_tests/onnx/node/generated/test_cos/model.mlir +++ b/iree_tests/onnx/node/generated/test_cos/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cos(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cos"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Cos"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_cos_example/model.mlir b/iree_tests/onnx/node/generated/test_cos_example/model.mlir index 6451d62b6..73ae1d9d2 100644 --- a/iree_tests/onnx/node/generated/test_cos_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_cos_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cos_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cos"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Cos"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_cosh/model.mlir b/iree_tests/onnx/node/generated/test_cosh/model.mlir index 26dcda667..dc6078302 100644 --- a/iree_tests/onnx/node/generated/test_cosh/model.mlir +++ b/iree_tests/onnx/node/generated/test_cosh/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cosh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cosh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Cosh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_cosh_example/model.mlir b/iree_tests/onnx/node/generated/test_cosh_example/model.mlir index d36ba896d..2c436635e 100644 --- a/iree_tests/onnx/node/generated/test_cosh_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_cosh_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cosh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cosh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Cosh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_cumsum_1d/model.mlir b/iree_tests/onnx/node/generated/test_cumsum_1d/model.mlir index 805438524..9067d8f26 100644 --- a/iree_tests/onnx/node/generated/test_cumsum_1d/model.mlir +++ b/iree_tests/onnx/node/generated/test_cumsum_1d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cumsum_1d(%arg0: !torch.vtensor<[5],f64>, %arg1: !torch.vtensor<[],si32>) -> !torch.vtensor<[5],f64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CumSum"(%arg0, %arg1) : (!torch.vtensor<[5],f64>, !torch.vtensor<[],si32>) -> !torch.vtensor<[5],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.CumSum"(%arg0, %arg1) : (!torch.vtensor<[5],f64>, !torch.vtensor<[],si32>) -> !torch.vtensor<[5],f64> return %0 : !torch.vtensor<[5],f64> } } diff --git a/iree_tests/onnx/node/generated/test_cumsum_1d_exclusive/model.mlir b/iree_tests/onnx/node/generated/test_cumsum_1d_exclusive/model.mlir index 61092f676..8a0552cb4 100644 --- a/iree_tests/onnx/node/generated/test_cumsum_1d_exclusive/model.mlir +++ b/iree_tests/onnx/node/generated/test_cumsum_1d_exclusive/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cumsum_1d_exclusive(%arg0: !torch.vtensor<[5],f64>, %arg1: !torch.vtensor<[],si32>) -> !torch.vtensor<[5],f64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CumSum"(%arg0, %arg1) {torch.onnx.exclusive = 1 : si64} : (!torch.vtensor<[5],f64>, !torch.vtensor<[],si32>) -> !torch.vtensor<[5],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.CumSum"(%arg0, %arg1) {torch.onnx.exclusive = 1 : si64} : (!torch.vtensor<[5],f64>, !torch.vtensor<[],si32>) -> !torch.vtensor<[5],f64> return %0 : !torch.vtensor<[5],f64> } } diff --git a/iree_tests/onnx/node/generated/test_cumsum_1d_reverse/model.mlir b/iree_tests/onnx/node/generated/test_cumsum_1d_reverse/model.mlir index 6ca919130..e7bafcb02 100644 --- a/iree_tests/onnx/node/generated/test_cumsum_1d_reverse/model.mlir +++ b/iree_tests/onnx/node/generated/test_cumsum_1d_reverse/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cumsum_1d_reverse(%arg0: !torch.vtensor<[5],f64>, %arg1: !torch.vtensor<[],si32>) -> !torch.vtensor<[5],f64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CumSum"(%arg0, %arg1) {torch.onnx.reverse = 1 : si64} : (!torch.vtensor<[5],f64>, !torch.vtensor<[],si32>) -> !torch.vtensor<[5],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.CumSum"(%arg0, %arg1) {torch.onnx.reverse = 1 : si64} : (!torch.vtensor<[5],f64>, !torch.vtensor<[],si32>) -> !torch.vtensor<[5],f64> return %0 : !torch.vtensor<[5],f64> } } diff --git a/iree_tests/onnx/node/generated/test_cumsum_1d_reverse_exclusive/model.mlir b/iree_tests/onnx/node/generated/test_cumsum_1d_reverse_exclusive/model.mlir index 594b0e24c..69b9b4148 100644 --- a/iree_tests/onnx/node/generated/test_cumsum_1d_reverse_exclusive/model.mlir +++ b/iree_tests/onnx/node/generated/test_cumsum_1d_reverse_exclusive/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cumsum_1d_reverse_exclusive(%arg0: !torch.vtensor<[5],f64>, %arg1: !torch.vtensor<[],si32>) -> !torch.vtensor<[5],f64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CumSum"(%arg0, %arg1) {torch.onnx.exclusive = 1 : si64, torch.onnx.reverse = 1 : si64} : (!torch.vtensor<[5],f64>, !torch.vtensor<[],si32>) -> !torch.vtensor<[5],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.CumSum"(%arg0, %arg1) {torch.onnx.exclusive = 1 : si64, torch.onnx.reverse = 1 : si64} : (!torch.vtensor<[5],f64>, !torch.vtensor<[],si32>) -> !torch.vtensor<[5],f64> return %0 : !torch.vtensor<[5],f64> } } diff --git a/iree_tests/onnx/node/generated/test_cumsum_2d_axis_0/model.mlir b/iree_tests/onnx/node/generated/test_cumsum_2d_axis_0/model.mlir index 9c070ecc9..c670ee02b 100644 --- a/iree_tests/onnx/node/generated/test_cumsum_2d_axis_0/model.mlir +++ b/iree_tests/onnx/node/generated/test_cumsum_2d_axis_0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cumsum_2d_axis_0(%arg0: !torch.vtensor<[2,3],f64>, %arg1: !torch.vtensor<[],si32>) -> !torch.vtensor<[2,3],f64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CumSum"(%arg0, %arg1) : (!torch.vtensor<[2,3],f64>, !torch.vtensor<[],si32>) -> !torch.vtensor<[2,3],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.CumSum"(%arg0, %arg1) : (!torch.vtensor<[2,3],f64>, !torch.vtensor<[],si32>) -> !torch.vtensor<[2,3],f64> return %0 : !torch.vtensor<[2,3],f64> } } diff --git a/iree_tests/onnx/node/generated/test_cumsum_2d_axis_1/model.mlir b/iree_tests/onnx/node/generated/test_cumsum_2d_axis_1/model.mlir index 583ac5f06..3ede05bf7 100644 --- a/iree_tests/onnx/node/generated/test_cumsum_2d_axis_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_cumsum_2d_axis_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cumsum_2d_axis_1(%arg0: !torch.vtensor<[2,3],f64>, %arg1: !torch.vtensor<[],si32>) -> !torch.vtensor<[2,3],f64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CumSum"(%arg0, %arg1) : (!torch.vtensor<[2,3],f64>, !torch.vtensor<[],si32>) -> !torch.vtensor<[2,3],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.CumSum"(%arg0, %arg1) : (!torch.vtensor<[2,3],f64>, !torch.vtensor<[],si32>) -> !torch.vtensor<[2,3],f64> return %0 : !torch.vtensor<[2,3],f64> } } diff --git a/iree_tests/onnx/node/generated/test_cumsum_2d_negative_axis/model.mlir b/iree_tests/onnx/node/generated/test_cumsum_2d_negative_axis/model.mlir index 356f27b61..bc8703bee 100644 --- a/iree_tests/onnx/node/generated/test_cumsum_2d_negative_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_cumsum_2d_negative_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_cumsum_2d_negative_axis(%arg0: !torch.vtensor<[2,3],f64>, %arg1: !torch.vtensor<[],si32>) -> !torch.vtensor<[2,3],f64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.CumSum"(%arg0, %arg1) : (!torch.vtensor<[2,3],f64>, !torch.vtensor<[],si32>) -> !torch.vtensor<[2,3],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.CumSum"(%arg0, %arg1) : (!torch.vtensor<[2,3],f64>, !torch.vtensor<[],si32>) -> !torch.vtensor<[2,3],f64> return %0 : !torch.vtensor<[2,3],f64> } } diff --git a/iree_tests/onnx/node/generated/test_deform_conv_with_mask_bias/model.mlir b/iree_tests/onnx/node/generated/test_deform_conv_with_mask_bias/model.mlir index 750b56510..e3d732d8d 100644 --- a/iree_tests/onnx/node/generated/test_deform_conv_with_mask_bias/model.mlir +++ b/iree_tests/onnx/node/generated/test_deform_conv_with_mask_bias/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_deform_conv_with_mask_bias(%arg0: !torch.vtensor<[1,1,3,3],f32>, %arg1: !torch.vtensor<[1,1,2,2],f32>, %arg2: !torch.vtensor<[1,8,2,2],f32>, %arg3: !torch.vtensor<[1],f32>, %arg4: !torch.vtensor<[1,4,2,2],f32>) -> !torch.vtensor<[1,1,2,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.DeformConv"(%arg0, %arg1, %arg2, %arg3, %arg4) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.pads = [0 : si64, 0 : si64, 0 : si64, 0 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,1,2,2],f32>, !torch.vtensor<[1,8,2,2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[1,4,2,2],f32>) -> !torch.vtensor<[1,1,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.DeformConv"(%arg0, %arg1, %arg2, %arg3, %arg4) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.pads = [0 : si64, 0 : si64, 0 : si64, 0 : si64]} : (!torch.vtensor<[1,1,3,3],f32>, !torch.vtensor<[1,1,2,2],f32>, !torch.vtensor<[1,8,2,2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[1,4,2,2],f32>) -> !torch.vtensor<[1,1,2,2],f32> return %0 : !torch.vtensor<[1,1,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_deform_conv_with_multiple_offset_groups/model.mlir b/iree_tests/onnx/node/generated/test_deform_conv_with_multiple_offset_groups/model.mlir index f78416d1e..6a6147e34 100644 --- a/iree_tests/onnx/node/generated/test_deform_conv_with_multiple_offset_groups/model.mlir +++ b/iree_tests/onnx/node/generated/test_deform_conv_with_multiple_offset_groups/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_deform_conv_with_multiple_offset_groups(%arg0: !torch.vtensor<[1,2,3,3],f32>, %arg1: !torch.vtensor<[1,2,2,2],f32>, %arg2: !torch.vtensor<[1,16,2,2],f32>) -> !torch.vtensor<[1,1,2,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.DeformConv"(%arg0, %arg1, %arg2) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.offset_group = 2 : si64, torch.onnx.pads = [0 : si64, 0 : si64, 0 : si64, 0 : si64]} : (!torch.vtensor<[1,2,3,3],f32>, !torch.vtensor<[1,2,2,2],f32>, !torch.vtensor<[1,16,2,2],f32>) -> !torch.vtensor<[1,1,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.DeformConv"(%arg0, %arg1, %arg2) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.offset_group = 2 : si64, torch.onnx.pads = [0 : si64, 0 : si64, 0 : si64, 0 : si64]} : (!torch.vtensor<[1,2,3,3],f32>, !torch.vtensor<[1,2,2,2],f32>, !torch.vtensor<[1,16,2,2],f32>) -> !torch.vtensor<[1,1,2,2],f32> return %0 : !torch.vtensor<[1,1,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_depthtospace_crd_mode_example/model.mlir b/iree_tests/onnx/node/generated/test_depthtospace_crd_mode_example/model.mlir index b4b1d4b7a..25434b483 100644 --- a/iree_tests/onnx/node/generated/test_depthtospace_crd_mode_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_depthtospace_crd_mode_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_depthtospace_crd_mode_example(%arg0: !torch.vtensor<[1,8,2,3],f32>) -> !torch.vtensor<[1,2,4,6],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.DepthToSpace"(%arg0) {torch.onnx.blocksize = 2 : si64, torch.onnx.mode = "CRD"} : (!torch.vtensor<[1,8,2,3],f32>) -> !torch.vtensor<[1,2,4,6],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.DepthToSpace"(%arg0) {torch.onnx.blocksize = 2 : si64, torch.onnx.mode = "CRD"} : (!torch.vtensor<[1,8,2,3],f32>) -> !torch.vtensor<[1,2,4,6],f32> return %0 : !torch.vtensor<[1,2,4,6],f32> } } diff --git a/iree_tests/onnx/node/generated/test_depthtospace_example/model.mlir b/iree_tests/onnx/node/generated/test_depthtospace_example/model.mlir index c4672c840..9619288ac 100644 --- a/iree_tests/onnx/node/generated/test_depthtospace_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_depthtospace_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_depthtospace_example(%arg0: !torch.vtensor<[1,8,2,3],f32>) -> !torch.vtensor<[1,2,4,6],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.DepthToSpace"(%arg0) {torch.onnx.blocksize = 2 : si64, torch.onnx.mode = "DCR"} : (!torch.vtensor<[1,8,2,3],f32>) -> !torch.vtensor<[1,2,4,6],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.DepthToSpace"(%arg0) {torch.onnx.blocksize = 2 : si64, torch.onnx.mode = "DCR"} : (!torch.vtensor<[1,8,2,3],f32>) -> !torch.vtensor<[1,2,4,6],f32> return %0 : !torch.vtensor<[1,2,4,6],f32> } } diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear/model.mlir b/iree_tests/onnx/node/generated/test_dequantizelinear/model.mlir index a25e85a24..2ffca9cbc 100644 --- a/iree_tests/onnx/node/generated/test_dequantizelinear/model.mlir +++ b/iree_tests/onnx/node/generated/test_dequantizelinear/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dequantizelinear(%arg0: !torch.vtensor<[4],ui8>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],ui8>) -> !torch.vtensor<[4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.DequantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[4],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) -> !torch.vtensor<[4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.DequantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[4],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) -> !torch.vtensor<[4],f32> return %0 : !torch.vtensor<[4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_axis/model.mlir b/iree_tests/onnx/node/generated/test_dequantizelinear_axis/model.mlir index cb3a47782..b5950687b 100644 --- a/iree_tests/onnx/node/generated/test_dequantizelinear_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_dequantizelinear_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dequantizelinear_axis(%arg0: !torch.vtensor<[1,3,3,2],ui8>, %arg1: !torch.vtensor<[3],f32>, %arg2: !torch.vtensor<[3],ui8>) -> !torch.vtensor<[1,3,3,2],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.DequantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[1,3,3,2],ui8>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],ui8>) -> !torch.vtensor<[1,3,3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.DequantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[1,3,3,2],ui8>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],ui8>) -> !torch.vtensor<[1,3,3,2],f32> return %0 : !torch.vtensor<[1,3,3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_blocked/model.mlir b/iree_tests/onnx/node/generated/test_dequantizelinear_blocked/model.mlir index af25af078..4c64560c8 100644 --- a/iree_tests/onnx/node/generated/test_dequantizelinear_blocked/model.mlir +++ b/iree_tests/onnx/node/generated/test_dequantizelinear_blocked/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dequantizelinear_blocked(%arg0: !torch.vtensor<[1,4,3,2],ui8>, %arg1: !torch.vtensor<[1,2,3,2],f32>, %arg2: !torch.vtensor<[1,2,3,2],ui8>) -> !torch.vtensor<[1,4,3,2],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.DequantizeLinear"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64, torch.onnx.block_size = 2 : si64} : (!torch.vtensor<[1,4,3,2],ui8>, !torch.vtensor<[1,2,3,2],f32>, !torch.vtensor<[1,2,3,2],ui8>) -> !torch.vtensor<[1,4,3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.DequantizeLinear"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64, torch.onnx.block_size = 2 : si64} : (!torch.vtensor<[1,4,3,2],ui8>, !torch.vtensor<[1,2,3,2],f32>, !torch.vtensor<[1,2,3,2],ui8>) -> !torch.vtensor<[1,4,3,2],f32> return %0 : !torch.vtensor<[1,4,3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn/input_0.npy b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn/input_0.npy new file mode 100644 index 000000000..5b5fb425b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn/input_1.npy b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn/input_1.npy new file mode 100644 index 000000000..656a8d759 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn/model.mlir b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn/model.mlir new file mode 100644 index 000000000..2f3be41c1 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_dequantizelinear_e4m3fn(%arg0: !torch.vtensor<[5],f8E4M3FN>, %arg1: !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.DequantizeLinear"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f8E4M3FN>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> + return %0 : !torch.vtensor<[5],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn/output_0.npy b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn/output_0.npy new file mode 100644 index 000000000..d2beff535 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn/test_data_flags.txt b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/input_0.npy b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/input_0.npy new file mode 100644 index 000000000..5b5fb425b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/input_1.npy b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/input_1.npy new file mode 100644 index 000000000..656a8d759 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/input_2.npy b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/input_2.npy new file mode 100644 index 000000000..c25d6a8c2 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/model.mlir b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/model.mlir new file mode 100644 index 000000000..fa6b9f729 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_dequantizelinear_e4m3fn_zero_point(%arg0: !torch.vtensor<[5],f8E4M3FN>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[1],f8E4M3FN>) -> !torch.vtensor<[5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.DequantizeLinear"(%arg0, %arg1, %arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f8E4M3FN>, !torch.vtensor<[],f32>, !torch.vtensor<[1],f8E4M3FN>) -> !torch.vtensor<[5],f32> + return %0 : !torch.vtensor<[5],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/output_0.npy b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/output_0.npy new file mode 100644 index 000000000..d2beff535 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/test_data_flags.txt b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/test_data_flags.txt new file mode 100644 index 000000000..cb3b7ab77 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_dequantizelinear_e4m3fn_zero_point/test_data_flags.txt @@ -0,0 +1,4 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_e5m2/input_0.npy b/iree_tests/onnx/node/generated/test_dequantizelinear_e5m2/input_0.npy new file mode 100644 index 000000000..06f2b61d1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dequantizelinear_e5m2/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_e5m2/input_1.npy b/iree_tests/onnx/node/generated/test_dequantizelinear_e5m2/input_1.npy new file mode 100644 index 000000000..656a8d759 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dequantizelinear_e5m2/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_e5m2/model.mlir b/iree_tests/onnx/node/generated/test_dequantizelinear_e5m2/model.mlir new file mode 100644 index 000000000..391abd866 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_dequantizelinear_e5m2/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_dequantizelinear_e5m2(%arg0: !torch.vtensor<[5],f8E5M2>, %arg1: !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.DequantizeLinear"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f8E5M2>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> + return %0 : !torch.vtensor<[5],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_e5m2/output_0.npy b/iree_tests/onnx/node/generated/test_dequantizelinear_e5m2/output_0.npy new file mode 100644 index 000000000..f44fa5fa8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dequantizelinear_e5m2/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_e5m2/test_data_flags.txt b/iree_tests/onnx/node/generated/test_dequantizelinear_e5m2/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_dequantizelinear_e5m2/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_int16/model.mlir b/iree_tests/onnx/node/generated/test_dequantizelinear_int16/model.mlir index 1ec03c47c..dd37a3b25 100644 --- a/iree_tests/onnx/node/generated/test_dequantizelinear_int16/model.mlir +++ b/iree_tests/onnx/node/generated/test_dequantizelinear_int16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dequantizelinear_int16(%arg0: !torch.vtensor<[4],si16>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],si16>) -> !torch.vtensor<[4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.DequantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[4],si16>, !torch.vtensor<[],f32>, !torch.vtensor<[],si16>) -> !torch.vtensor<[4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.DequantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[4],si16>, !torch.vtensor<[],f32>, !torch.vtensor<[],si16>) -> !torch.vtensor<[4],f32> return %0 : !torch.vtensor<[4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_dequantizelinear_uint16/model.mlir b/iree_tests/onnx/node/generated/test_dequantizelinear_uint16/model.mlir index 1505d5dfa..f8dd8e3f2 100644 --- a/iree_tests/onnx/node/generated/test_dequantizelinear_uint16/model.mlir +++ b/iree_tests/onnx/node/generated/test_dequantizelinear_uint16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dequantizelinear_uint16(%arg0: !torch.vtensor<[4],ui16>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],ui16>) -> !torch.vtensor<[4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.DequantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[4],ui16>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui16>) -> !torch.vtensor<[4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.DequantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[4],ui16>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui16>) -> !torch.vtensor<[4],f32> return %0 : !torch.vtensor<[4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_det_2d/model.mlir b/iree_tests/onnx/node/generated/test_det_2d/model.mlir index 7e435fbb3..74a4279c9 100644 --- a/iree_tests/onnx/node/generated/test_det_2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_det_2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_det_2d(%arg0: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Det"(%arg0) : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Det"(%arg0) : (!torch.vtensor<[2,2],f32>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_det_nd/model.mlir b/iree_tests/onnx/node/generated/test_det_nd/model.mlir index d41344aed..8b555f9fc 100644 --- a/iree_tests/onnx/node/generated/test_det_nd/model.mlir +++ b/iree_tests/onnx/node/generated/test_det_nd/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_det_nd(%arg0: !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Det"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Det"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_dft/input_0.npy b/iree_tests/onnx/node/generated/test_dft/input_0.npy new file mode 100644 index 000000000..a8ad45b6e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dft/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_dft/input_1.npy b/iree_tests/onnx/node/generated/test_dft/input_1.npy new file mode 100644 index 000000000..8269ea423 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dft/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_dft/model.mlir b/iree_tests/onnx/node/generated/test_dft/model.mlir new file mode 100644 index 000000000..ea4aab106 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_dft/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_dft(%arg0: !torch.vtensor<[1,10,10,1],f32>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[1,10,10,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.DFT"(%arg0, %none, %arg1) : (!torch.vtensor<[1,10,10,1],f32>, !torch.none, !torch.vtensor<[],si64>) -> !torch.vtensor<[1,10,10,2],f32> + return %0 : !torch.vtensor<[1,10,10,2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_dft/output_0.npy b/iree_tests/onnx/node/generated/test_dft/output_0.npy new file mode 100644 index 000000000..85bb7b339 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dft/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_dft/test_data_flags.txt b/iree_tests/onnx/node/generated/test_dft/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_dft/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_dft_axis/input_0.npy b/iree_tests/onnx/node/generated/test_dft_axis/input_0.npy new file mode 100644 index 000000000..a8ad45b6e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dft_axis/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_dft_axis/input_1.npy b/iree_tests/onnx/node/generated/test_dft_axis/input_1.npy new file mode 100644 index 000000000..8d8de214b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dft_axis/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_dft_axis/model.mlir b/iree_tests/onnx/node/generated/test_dft_axis/model.mlir new file mode 100644 index 000000000..45613443e --- /dev/null +++ b/iree_tests/onnx/node/generated/test_dft_axis/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_dft_axis(%arg0: !torch.vtensor<[1,10,10,1],f32>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[1,10,10,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.DFT"(%arg0, %none, %arg1) : (!torch.vtensor<[1,10,10,1],f32>, !torch.none, !torch.vtensor<[],si64>) -> !torch.vtensor<[1,10,10,2],f32> + return %0 : !torch.vtensor<[1,10,10,2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_dft_axis/output_0.npy b/iree_tests/onnx/node/generated/test_dft_axis/output_0.npy new file mode 100644 index 000000000..813d67c67 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dft_axis/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_dft_axis/test_data_flags.txt b/iree_tests/onnx/node/generated/test_dft_axis/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_dft_axis/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_dft_axis_opset19/model.mlir b/iree_tests/onnx/node/generated/test_dft_axis_opset19/model.mlir index 243ba2dad..f98dfa846 100644 --- a/iree_tests/onnx/node/generated/test_dft_axis_opset19/model.mlir +++ b/iree_tests/onnx/node/generated/test_dft_axis_opset19/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dft_axis_opset19(%arg0: !torch.vtensor<[1,10,10,1],f32>) -> !torch.vtensor<[1,10,10,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.DFT"(%arg0) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[1,10,10,1],f32>) -> !torch.vtensor<[1,10,10,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.DFT"(%arg0) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[1,10,10,1],f32>) -> !torch.vtensor<[1,10,10,2],f32> return %0 : !torch.vtensor<[1,10,10,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_dft_inverse/input_0.npy b/iree_tests/onnx/node/generated/test_dft_inverse/input_0.npy new file mode 100644 index 000000000..0cc7a0cc5 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dft_inverse/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_dft_inverse/input_1.npy b/iree_tests/onnx/node/generated/test_dft_inverse/input_1.npy new file mode 100644 index 000000000..8269ea423 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dft_inverse/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_dft_inverse/model.mlir b/iree_tests/onnx/node/generated/test_dft_inverse/model.mlir new file mode 100644 index 000000000..6435f69f8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_dft_inverse/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_dft_inverse(%arg0: !torch.vtensor<[1,10,10,2],f32>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[1,10,10,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.DFT"(%arg0, %none, %arg1) {torch.onnx.inverse = 1 : si64} : (!torch.vtensor<[1,10,10,2],f32>, !torch.none, !torch.vtensor<[],si64>) -> !torch.vtensor<[1,10,10,2],f32> + return %0 : !torch.vtensor<[1,10,10,2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_dft_inverse/output_0.npy b/iree_tests/onnx/node/generated/test_dft_inverse/output_0.npy new file mode 100644 index 000000000..6f22527b5 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_dft_inverse/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_dft_inverse/test_data_flags.txt b/iree_tests/onnx/node/generated/test_dft_inverse/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_dft_inverse/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_dft_inverse_opset19/model.mlir b/iree_tests/onnx/node/generated/test_dft_inverse_opset19/model.mlir index 37df71bbc..0fb1f24ad 100644 --- a/iree_tests/onnx/node/generated/test_dft_inverse_opset19/model.mlir +++ b/iree_tests/onnx/node/generated/test_dft_inverse_opset19/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dft_inverse_opset19(%arg0: !torch.vtensor<[1,10,10,2],f32>) -> !torch.vtensor<[1,10,10,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.DFT"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.inverse = 1 : si64} : (!torch.vtensor<[1,10,10,2],f32>) -> !torch.vtensor<[1,10,10,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.DFT"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.inverse = 1 : si64} : (!torch.vtensor<[1,10,10,2],f32>) -> !torch.vtensor<[1,10,10,2],f32> return %0 : !torch.vtensor<[1,10,10,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_dft_opset19/model.mlir b/iree_tests/onnx/node/generated/test_dft_opset19/model.mlir index 8e92d1e3d..b9efa152e 100644 --- a/iree_tests/onnx/node/generated/test_dft_opset19/model.mlir +++ b/iree_tests/onnx/node/generated/test_dft_opset19/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dft_opset19(%arg0: !torch.vtensor<[1,10,10,1],f32>) -> !torch.vtensor<[1,10,10,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.DFT"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[1,10,10,1],f32>) -> !torch.vtensor<[1,10,10,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.DFT"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[1,10,10,1],f32>) -> !torch.vtensor<[1,10,10,2],f32> return %0 : !torch.vtensor<[1,10,10,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_div/model.mlir b/iree_tests/onnx/node/generated/test_div/model.mlir index 505ef5eb0..fc61a9e31 100644 --- a/iree_tests/onnx/node/generated/test_div/model.mlir +++ b/iree_tests/onnx/node/generated/test_div/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_div(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Div"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Div"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_div_bcast/model.mlir b/iree_tests/onnx/node/generated/test_div_bcast/model.mlir index 917c67f30..a809ffefc 100644 --- a/iree_tests/onnx/node/generated/test_div_bcast/model.mlir +++ b/iree_tests/onnx/node/generated/test_div_bcast/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_div_bcast(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Div"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Div"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_div_example/model.mlir b/iree_tests/onnx/node/generated/test_div_example/model.mlir index a4de4f2b8..9e663a913 100644 --- a/iree_tests/onnx/node/generated/test_div_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_div_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_div_example(%arg0: !torch.vtensor<[2],f32>, %arg1: !torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Div"(%arg0, %arg1) : (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Div"(%arg0, %arg1) : (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> return %0 : !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_div_uint8/model.mlir b/iree_tests/onnx/node/generated/test_div_uint8/model.mlir index 14e97f58a..28a6b0510 100644 --- a/iree_tests/onnx/node/generated/test_div_uint8/model.mlir +++ b/iree_tests/onnx/node/generated/test_div_uint8/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_div_uint8(%arg0: !torch.vtensor<[3,4,5],ui8>, %arg1: !torch.vtensor<[3,4,5],ui8>) -> !torch.vtensor<[3,4,5],ui8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Div"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],ui8>, !torch.vtensor<[3,4,5],ui8>) -> !torch.vtensor<[3,4,5],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.Div"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],ui8>, !torch.vtensor<[3,4,5],ui8>) -> !torch.vtensor<[3,4,5],ui8> return %0 : !torch.vtensor<[3,4,5],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_dropout_default/model.mlir b/iree_tests/onnx/node/generated/test_dropout_default/model.mlir index ee3c220cb..7fb5684dc 100644 --- a/iree_tests/onnx/node/generated/test_dropout_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_dropout_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dropout_default(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Dropout"(%arg0) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Dropout"(%arg0) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_dropout_default_mask/model.mlir b/iree_tests/onnx/node/generated/test_dropout_default_mask/model.mlir index 6a2dee53e..4122aab71 100644 --- a/iree_tests/onnx/node/generated/test_dropout_default_mask/model.mlir +++ b/iree_tests/onnx/node/generated/test_dropout_default_mask/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dropout_default_mask(%arg0: !torch.vtensor<[3,4,5],f32>) -> (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.Dropout"(%arg0) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.Dropout"(%arg0) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1>) return %0#0, %0#1 : !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_dropout_default_mask_ratio/model.mlir b/iree_tests/onnx/node/generated/test_dropout_default_mask_ratio/model.mlir index baf5aa7ca..d91db1374 100644 --- a/iree_tests/onnx/node/generated/test_dropout_default_mask_ratio/model.mlir +++ b/iree_tests/onnx/node/generated/test_dropout_default_mask_ratio/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dropout_default_mask_ratio(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[],f32>) -> (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.Dropout"(%arg0, %arg1) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.Dropout"(%arg0, %arg1) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1>) return %0#0, %0#1 : !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_dropout_default_old/model.mlir b/iree_tests/onnx/node/generated/test_dropout_default_old/model.mlir index 0e8da97d4..69c4019d0 100644 --- a/iree_tests/onnx/node/generated/test_dropout_default_old/model.mlir +++ b/iree_tests/onnx/node/generated/test_dropout_default_old/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dropout_default_old(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Dropout"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Dropout"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_dropout_default_ratio/model.mlir b/iree_tests/onnx/node/generated/test_dropout_default_ratio/model.mlir index c20e88a26..11b4ac3a4 100644 --- a/iree_tests/onnx/node/generated/test_dropout_default_ratio/model.mlir +++ b/iree_tests/onnx/node/generated/test_dropout_default_ratio/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dropout_default_ratio(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Dropout"(%arg0, %arg1) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Dropout"(%arg0, %arg1) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_dropout_random_old/model.mlir b/iree_tests/onnx/node/generated/test_dropout_random_old/model.mlir index 2c9e535f0..a70199380 100644 --- a/iree_tests/onnx/node/generated/test_dropout_random_old/model.mlir +++ b/iree_tests/onnx/node/generated/test_dropout_random_old/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dropout_random_old(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Dropout"(%arg0) {torch.onnx.ratio = 2.000000e-01 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Dropout"(%arg0) {torch.onnx.ratio = 2.000000e-01 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_dynamicquantizelinear/model.mlir b/iree_tests/onnx/node/generated/test_dynamicquantizelinear/model.mlir index 5521df348..5bac5e14f 100644 --- a/iree_tests/onnx/node/generated/test_dynamicquantizelinear/model.mlir +++ b/iree_tests/onnx/node/generated/test_dynamicquantizelinear/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dynamicquantizelinear(%arg0: !torch.vtensor<[6],f32>) -> (!torch.vtensor<[6],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.DynamicQuantizeLinear"(%arg0) : (!torch.vtensor<[6],f32>) -> (!torch.vtensor<[6],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.DynamicQuantizeLinear"(%arg0) : (!torch.vtensor<[6],f32>) -> (!torch.vtensor<[6],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) return %0#0, %0#1, %0#2 : !torch.vtensor<[6],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_dynamicquantizelinear_expanded/model.mlir b/iree_tests/onnx/node/generated/test_dynamicquantizelinear_expanded/model.mlir index 41a6f0b98..93053fc65 100644 --- a/iree_tests/onnx/node/generated/test_dynamicquantizelinear_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_dynamicquantizelinear_expanded/model.mlir @@ -1,21 +1,22 @@ module { func.func @test_dynamicquantizelinear_expanded(%arg0: !torch.vtensor<[6],f32>) -> (!torch.vtensor<[6],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %1 = torch.vtensor.literal(dense<2.550000e+02> : tensor) : !torch.vtensor<[],f32> - %2 = torch.operator "onnx.ReduceMin"(%arg0) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[6],f32>) -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.Min"(%2, %0) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[6],f32>) -> !torch.vtensor<[],f32> - %5 = torch.operator "onnx.Max"(%4, %0) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %6 = torch.operator "onnx.Sub"(%5, %3) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Div"(%6, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %8 = torch.operator "onnx.Div"(%3, %7) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %9 = torch.operator "onnx.Sub"(%0, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %10 = torch.operator "onnx.Clip"(%9, %0, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %11 = torch.operator "onnx.Round"(%10) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %12 = torch.operator "onnx.Cast"(%11) {torch.onnx.to = 2 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],ui8> - %13 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %14 = torch.operator "onnx.Identity"(%12) : (!torch.vtensor<[],ui8>) -> !torch.vtensor<[],ui8> - %15 = torch.operator "onnx.QuantizeLinear"(%arg0, %7, %12) : (!torch.vtensor<[6],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) -> !torch.vtensor<[6],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2.550000e+02> : tensor} : () -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.ReduceMin"(%arg0) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[6],f32>) -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Min"(%2, %0) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[6],f32>) -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.Max"(%4, %0) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Sub"(%5, %3) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Div"(%6, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.Div"(%3, %7) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %9 = torch.operator "onnx.Sub"(%0, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %10 = torch.operator "onnx.Clip"(%9, %0, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.Round"(%10) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %12 = torch.operator "onnx.Cast"(%11) {torch.onnx.to = 2 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],ui8> + %13 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %14 = torch.operator "onnx.Identity"(%12) : (!torch.vtensor<[],ui8>) -> !torch.vtensor<[],ui8> + %15 = torch.operator "onnx.QuantizeLinear"(%arg0, %7, %12) : (!torch.vtensor<[6],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) -> !torch.vtensor<[6],ui8> return %15, %13, %14 : !torch.vtensor<[6],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_dynamicquantizelinear_max_adjusted/model.mlir b/iree_tests/onnx/node/generated/test_dynamicquantizelinear_max_adjusted/model.mlir index efbf1fd2f..24856c272 100644 --- a/iree_tests/onnx/node/generated/test_dynamicquantizelinear_max_adjusted/model.mlir +++ b/iree_tests/onnx/node/generated/test_dynamicquantizelinear_max_adjusted/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dynamicquantizelinear_max_adjusted(%arg0: !torch.vtensor<[6],f32>) -> (!torch.vtensor<[6],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.DynamicQuantizeLinear"(%arg0) : (!torch.vtensor<[6],f32>) -> (!torch.vtensor<[6],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.DynamicQuantizeLinear"(%arg0) : (!torch.vtensor<[6],f32>) -> (!torch.vtensor<[6],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) return %0#0, %0#1, %0#2 : !torch.vtensor<[6],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_dynamicquantizelinear_max_adjusted_expanded/model.mlir b/iree_tests/onnx/node/generated/test_dynamicquantizelinear_max_adjusted_expanded/model.mlir index 6ac65a5a6..d2c07d823 100644 --- a/iree_tests/onnx/node/generated/test_dynamicquantizelinear_max_adjusted_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_dynamicquantizelinear_max_adjusted_expanded/model.mlir @@ -1,21 +1,22 @@ module { func.func @test_dynamicquantizelinear_max_adjusted_expanded(%arg0: !torch.vtensor<[6],f32>) -> (!torch.vtensor<[6],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %1 = torch.vtensor.literal(dense<2.550000e+02> : tensor) : !torch.vtensor<[],f32> - %2 = torch.operator "onnx.ReduceMin"(%arg0) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[6],f32>) -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.Min"(%2, %0) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[6],f32>) -> !torch.vtensor<[],f32> - %5 = torch.operator "onnx.Max"(%4, %0) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %6 = torch.operator "onnx.Sub"(%5, %3) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Div"(%6, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %8 = torch.operator "onnx.Div"(%3, %7) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %9 = torch.operator "onnx.Sub"(%0, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %10 = torch.operator "onnx.Clip"(%9, %0, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %11 = torch.operator "onnx.Round"(%10) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %12 = torch.operator "onnx.Cast"(%11) {torch.onnx.to = 2 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],ui8> - %13 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %14 = torch.operator "onnx.Identity"(%12) : (!torch.vtensor<[],ui8>) -> !torch.vtensor<[],ui8> - %15 = torch.operator "onnx.QuantizeLinear"(%arg0, %7, %12) : (!torch.vtensor<[6],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) -> !torch.vtensor<[6],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2.550000e+02> : tensor} : () -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.ReduceMin"(%arg0) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[6],f32>) -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Min"(%2, %0) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[6],f32>) -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.Max"(%4, %0) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Sub"(%5, %3) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Div"(%6, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.Div"(%3, %7) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %9 = torch.operator "onnx.Sub"(%0, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %10 = torch.operator "onnx.Clip"(%9, %0, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.Round"(%10) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %12 = torch.operator "onnx.Cast"(%11) {torch.onnx.to = 2 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],ui8> + %13 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %14 = torch.operator "onnx.Identity"(%12) : (!torch.vtensor<[],ui8>) -> !torch.vtensor<[],ui8> + %15 = torch.operator "onnx.QuantizeLinear"(%arg0, %7, %12) : (!torch.vtensor<[6],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) -> !torch.vtensor<[6],ui8> return %15, %13, %14 : !torch.vtensor<[6],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_dynamicquantizelinear_min_adjusted/model.mlir b/iree_tests/onnx/node/generated/test_dynamicquantizelinear_min_adjusted/model.mlir index 245b65dac..a2d07627e 100644 --- a/iree_tests/onnx/node/generated/test_dynamicquantizelinear_min_adjusted/model.mlir +++ b/iree_tests/onnx/node/generated/test_dynamicquantizelinear_min_adjusted/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_dynamicquantizelinear_min_adjusted(%arg0: !torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.DynamicQuantizeLinear"(%arg0) : (!torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.DynamicQuantizeLinear"(%arg0) : (!torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) return %0#0, %0#1, %0#2 : !torch.vtensor<[3,4],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_dynamicquantizelinear_min_adjusted_expanded/model.mlir b/iree_tests/onnx/node/generated/test_dynamicquantizelinear_min_adjusted_expanded/model.mlir index 45612c6c5..2798b5df9 100644 --- a/iree_tests/onnx/node/generated/test_dynamicquantizelinear_min_adjusted_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_dynamicquantizelinear_min_adjusted_expanded/model.mlir @@ -1,21 +1,22 @@ module { func.func @test_dynamicquantizelinear_min_adjusted_expanded(%arg0: !torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %1 = torch.vtensor.literal(dense<2.550000e+02> : tensor) : !torch.vtensor<[],f32> - %2 = torch.operator "onnx.ReduceMin"(%arg0) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.Min"(%2, %0) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[],f32> - %5 = torch.operator "onnx.Max"(%4, %0) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %6 = torch.operator "onnx.Sub"(%5, %3) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Div"(%6, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %8 = torch.operator "onnx.Div"(%3, %7) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %9 = torch.operator "onnx.Sub"(%0, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %10 = torch.operator "onnx.Clip"(%9, %0, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %11 = torch.operator "onnx.Round"(%10) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %12 = torch.operator "onnx.Cast"(%11) {torch.onnx.to = 2 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],ui8> - %13 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %14 = torch.operator "onnx.Identity"(%12) : (!torch.vtensor<[],ui8>) -> !torch.vtensor<[],ui8> - %15 = torch.operator "onnx.QuantizeLinear"(%arg0, %7, %12) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) -> !torch.vtensor<[3,4],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2.550000e+02> : tensor} : () -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.ReduceMin"(%arg0) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Min"(%2, %0) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.Max"(%4, %0) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Sub"(%5, %3) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Div"(%6, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.Div"(%3, %7) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %9 = torch.operator "onnx.Sub"(%0, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %10 = torch.operator "onnx.Clip"(%9, %0, %1) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.Round"(%10) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %12 = torch.operator "onnx.Cast"(%11) {torch.onnx.to = 2 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],ui8> + %13 = torch.operator "onnx.Identity"(%7) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %14 = torch.operator "onnx.Identity"(%12) : (!torch.vtensor<[],ui8>) -> !torch.vtensor<[],ui8> + %15 = torch.operator "onnx.QuantizeLinear"(%arg0, %7, %12) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) -> !torch.vtensor<[3,4],ui8> return %15, %13, %14 : !torch.vtensor<[3,4],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_edge_pad/model.mlir b/iree_tests/onnx/node/generated/test_edge_pad/model.mlir index 0fec9bc80..3cdad1a6f 100644 --- a/iree_tests/onnx/node/generated/test_edge_pad/model.mlir +++ b/iree_tests/onnx/node/generated/test_edge_pad/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_edge_pad(%arg0: !torch.vtensor<[1,3,4,5],si32>, %arg1: !torch.vtensor<[8],si64>) -> !torch.vtensor<[1,3,6,7],si32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pad"(%arg0, %arg1) {torch.onnx.mode = "edge"} : (!torch.vtensor<[1,3,4,5],si32>, !torch.vtensor<[8],si64>) -> !torch.vtensor<[1,3,6,7],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.Pad"(%arg0, %arg1) {torch.onnx.mode = "edge"} : (!torch.vtensor<[1,3,4,5],si32>, !torch.vtensor<[8],si64>) -> !torch.vtensor<[1,3,6,7],si32> return %0 : !torch.vtensor<[1,3,6,7],si32> } } diff --git a/iree_tests/onnx/node/generated/test_einsum_batch_diagonal/model.mlir b/iree_tests/onnx/node/generated/test_einsum_batch_diagonal/model.mlir index 80c09f00e..8d87726ed 100644 --- a/iree_tests/onnx/node/generated/test_einsum_batch_diagonal/model.mlir +++ b/iree_tests/onnx/node/generated/test_einsum_batch_diagonal/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_einsum_batch_diagonal(%arg0: !torch.vtensor<[3,5,5],f64>) -> !torch.vtensor<[3,5],f64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Einsum"(%arg0) {torch.onnx.equation = "...ii ->...i"} : (!torch.vtensor<[3,5,5],f64>) -> !torch.vtensor<[3,5],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Einsum"(%arg0) {torch.onnx.equation = "...ii ->...i"} : (!torch.vtensor<[3,5,5],f64>) -> !torch.vtensor<[3,5],f64> return %0 : !torch.vtensor<[3,5],f64> } } diff --git a/iree_tests/onnx/node/generated/test_einsum_batch_matmul/model.mlir b/iree_tests/onnx/node/generated/test_einsum_batch_matmul/model.mlir index e114dce39..72c507286 100644 --- a/iree_tests/onnx/node/generated/test_einsum_batch_matmul/model.mlir +++ b/iree_tests/onnx/node/generated/test_einsum_batch_matmul/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_einsum_batch_matmul(%arg0: !torch.vtensor<[5,2,3],f64>, %arg1: !torch.vtensor<[5,3,4],f64>) -> !torch.vtensor<[5,2,4],f64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Einsum"(%arg0, %arg1) {torch.onnx.equation = "bij, bjk -> bik"} : (!torch.vtensor<[5,2,3],f64>, !torch.vtensor<[5,3,4],f64>) -> !torch.vtensor<[5,2,4],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Einsum"(%arg0, %arg1) {torch.onnx.equation = "bij, bjk -> bik"} : (!torch.vtensor<[5,2,3],f64>, !torch.vtensor<[5,3,4],f64>) -> !torch.vtensor<[5,2,4],f64> return %0 : !torch.vtensor<[5,2,4],f64> } } diff --git a/iree_tests/onnx/node/generated/test_einsum_inner_prod/model.mlir b/iree_tests/onnx/node/generated/test_einsum_inner_prod/model.mlir index a6bae50fa..91881e69e 100644 --- a/iree_tests/onnx/node/generated/test_einsum_inner_prod/model.mlir +++ b/iree_tests/onnx/node/generated/test_einsum_inner_prod/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_einsum_inner_prod(%arg0: !torch.vtensor<[5],f64>, %arg1: !torch.vtensor<[5],f64>) -> !torch.vtensor<[],f64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Einsum"(%arg0, %arg1) {torch.onnx.equation = "i,i"} : (!torch.vtensor<[5],f64>, !torch.vtensor<[5],f64>) -> !torch.vtensor<[],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Einsum"(%arg0, %arg1) {torch.onnx.equation = "i,i"} : (!torch.vtensor<[5],f64>, !torch.vtensor<[5],f64>) -> !torch.vtensor<[],f64> return %0 : !torch.vtensor<[],f64> } } diff --git a/iree_tests/onnx/node/generated/test_einsum_sum/model.mlir b/iree_tests/onnx/node/generated/test_einsum_sum/model.mlir index 62899de7a..4e86092e5 100644 --- a/iree_tests/onnx/node/generated/test_einsum_sum/model.mlir +++ b/iree_tests/onnx/node/generated/test_einsum_sum/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_einsum_sum(%arg0: !torch.vtensor<[3,4],f64>) -> !torch.vtensor<[3],f64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Einsum"(%arg0) {torch.onnx.equation = "ij->i"} : (!torch.vtensor<[3,4],f64>) -> !torch.vtensor<[3],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Einsum"(%arg0) {torch.onnx.equation = "ij->i"} : (!torch.vtensor<[3,4],f64>) -> !torch.vtensor<[3],f64> return %0 : !torch.vtensor<[3],f64> } } diff --git a/iree_tests/onnx/node/generated/test_einsum_transpose/model.mlir b/iree_tests/onnx/node/generated/test_einsum_transpose/model.mlir index 3da5db747..8a3059b21 100644 --- a/iree_tests/onnx/node/generated/test_einsum_transpose/model.mlir +++ b/iree_tests/onnx/node/generated/test_einsum_transpose/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_einsum_transpose(%arg0: !torch.vtensor<[3,4],f64>) -> !torch.vtensor<[4,3],f64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Einsum"(%arg0) {torch.onnx.equation = "ij->ji"} : (!torch.vtensor<[3,4],f64>) -> !torch.vtensor<[4,3],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Einsum"(%arg0) {torch.onnx.equation = "ij->ji"} : (!torch.vtensor<[3,4],f64>) -> !torch.vtensor<[4,3],f64> return %0 : !torch.vtensor<[4,3],f64> } } diff --git a/iree_tests/onnx/node/generated/test_elu/model.mlir b/iree_tests/onnx/node/generated/test_elu/model.mlir index d1ee2040f..b69f64eb7 100644 --- a/iree_tests/onnx/node/generated/test_elu/model.mlir +++ b/iree_tests/onnx/node/generated/test_elu/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_elu(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 6 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Elu"(%arg0) {torch.onnx.alpha = 2.000000e+00 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Elu"(%arg0) {torch.onnx.alpha = 2.000000e+00 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_elu_default/model.mlir b/iree_tests/onnx/node/generated/test_elu_default/model.mlir index fbe0eb7f8..9ef9fa26b 100644 --- a/iree_tests/onnx/node/generated/test_elu_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_elu_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_elu_default(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 6 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Elu"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Elu"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_elu_default_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_elu_default_expanded_ver18/model.mlir index f9704d80f..8b91e46f9 100644 --- a/iree_tests/onnx/node/generated/test_elu_default_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_elu_default_expanded_ver18/model.mlir @@ -1,16 +1,17 @@ module { func.func @test_elu_default_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.000000e+00 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %6 = torch.operator "onnx.Less"(%arg0, %3) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> - %7 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %8 = torch.operator "onnx.Sub"(%7, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> - %9 = torch.operator "onnx.Mul"(%1, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %10 = torch.operator "onnx.Where"(%6, %9, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.000000e+00 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Less"(%arg0, %3) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> + %7 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %8 = torch.operator "onnx.Sub"(%7, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %9 = torch.operator "onnx.Mul"(%1, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %10 = torch.operator "onnx.Where"(%6, %9, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %10 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_elu_example/model.mlir b/iree_tests/onnx/node/generated/test_elu_example/model.mlir index 72e21420d..b71e2cff7 100644 --- a/iree_tests/onnx/node/generated/test_elu_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_elu_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_elu_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 6 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Elu"(%arg0) {torch.onnx.alpha = 2.000000e+00 : f32} : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Elu"(%arg0) {torch.onnx.alpha = 2.000000e+00 : f32} : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_elu_example_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_elu_example_expanded_ver18/model.mlir index 6dda83798..b68995bc3 100644 --- a/iree_tests/onnx/node/generated/test_elu_example_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_elu_example_expanded_ver18/model.mlir @@ -1,16 +1,17 @@ module { func.func @test_elu_example_expanded_ver18(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 2.000000e+00 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %6 = torch.operator "onnx.Less"(%arg0, %3) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],i1> - %7 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %8 = torch.operator "onnx.Sub"(%7, %5) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> - %9 = torch.operator "onnx.Mul"(%1, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %10 = torch.operator "onnx.Where"(%6, %9, %arg0) : (!torch.vtensor<[3],i1>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 2.000000e+00 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Less"(%arg0, %3) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],i1> + %7 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %8 = torch.operator "onnx.Sub"(%7, %5) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> + %9 = torch.operator "onnx.Mul"(%1, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %10 = torch.operator "onnx.Where"(%6, %9, %arg0) : (!torch.vtensor<[3],i1>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %10 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_elu_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_elu_expanded_ver18/model.mlir index 0fd0703b6..484151aa7 100644 --- a/iree_tests/onnx/node/generated/test_elu_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_elu_expanded_ver18/model.mlir @@ -1,16 +1,17 @@ module { func.func @test_elu_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 2.000000e+00 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %6 = torch.operator "onnx.Less"(%arg0, %3) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> - %7 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %8 = torch.operator "onnx.Sub"(%7, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> - %9 = torch.operator "onnx.Mul"(%1, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %10 = torch.operator "onnx.Where"(%6, %9, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 2.000000e+00 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Less"(%arg0, %3) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> + %7 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %8 = torch.operator "onnx.Sub"(%7, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %9 = torch.operator "onnx.Mul"(%1, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %10 = torch.operator "onnx.Where"(%6, %9, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %10 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_equal/model.mlir b/iree_tests/onnx/node/generated/test_equal/model.mlir index 69561bd77..a37c5a0db 100644 --- a/iree_tests/onnx/node/generated/test_equal/model.mlir +++ b/iree_tests/onnx/node/generated/test_equal/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_equal(%arg0: !torch.vtensor<[3,4,5],si32>, %arg1: !torch.vtensor<[3,4,5],si32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Equal"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],si32>, !torch.vtensor<[3,4,5],si32>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Equal"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],si32>, !torch.vtensor<[3,4,5],si32>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_equal_bcast/model.mlir b/iree_tests/onnx/node/generated/test_equal_bcast/model.mlir index bdec8eba8..4fe00deb8 100644 --- a/iree_tests/onnx/node/generated/test_equal_bcast/model.mlir +++ b/iree_tests/onnx/node/generated/test_equal_bcast/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_equal_bcast(%arg0: !torch.vtensor<[3,4,5],si32>, %arg1: !torch.vtensor<[5],si32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Equal"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],si32>, !torch.vtensor<[5],si32>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Equal"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],si32>, !torch.vtensor<[5],si32>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_equal_string/input_0.npy b/iree_tests/onnx/node/generated/test_equal_string/input_0.npy new file mode 100644 index 000000000..ef6b9be09 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_equal_string/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_equal_string/input_1.npy b/iree_tests/onnx/node/generated/test_equal_string/input_1.npy new file mode 100644 index 000000000..688e95558 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_equal_string/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_equal_string/model.mlir b/iree_tests/onnx/node/generated/test_equal_string/model.mlir new file mode 100644 index 000000000..20697b9b9 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_equal_string/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_equal_string(%arg0: !torch.vtensor<[2],!torch.str>, %arg1: !torch.vtensor<[2],!torch.str>) -> !torch.vtensor<[2],i1> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Equal"(%arg0, %arg1) : (!torch.vtensor<[2],!torch.str>, !torch.vtensor<[2],!torch.str>) -> !torch.vtensor<[2],i1> + return %0 : !torch.vtensor<[2],i1> + } +} + diff --git a/iree_tests/onnx/node/generated/test_equal_string/output_0.npy b/iree_tests/onnx/node/generated/test_equal_string/output_0.npy new file mode 100644 index 000000000..cf617f2cf Binary files /dev/null and b/iree_tests/onnx/node/generated/test_equal_string/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_equal_string/test_data_flags.txt b/iree_tests/onnx/node/generated/test_equal_string/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_equal_string/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_equal_string_broadcast/input_0.npy b/iree_tests/onnx/node/generated/test_equal_string_broadcast/input_0.npy new file mode 100644 index 000000000..ef6b9be09 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_equal_string_broadcast/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_equal_string_broadcast/input_1.npy b/iree_tests/onnx/node/generated/test_equal_string_broadcast/input_1.npy new file mode 100644 index 000000000..2c336cc4f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_equal_string_broadcast/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_equal_string_broadcast/model.mlir b/iree_tests/onnx/node/generated/test_equal_string_broadcast/model.mlir new file mode 100644 index 000000000..0128554c2 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_equal_string_broadcast/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_equal_string_broadcast(%arg0: !torch.vtensor<[2],!torch.str>, %arg1: !torch.vtensor<[1],!torch.str>) -> !torch.vtensor<[2],i1> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Equal"(%arg0, %arg1) : (!torch.vtensor<[2],!torch.str>, !torch.vtensor<[1],!torch.str>) -> !torch.vtensor<[2],i1> + return %0 : !torch.vtensor<[2],i1> + } +} + diff --git a/iree_tests/onnx/node/generated/test_equal_string_broadcast/output_0.npy b/iree_tests/onnx/node/generated/test_equal_string_broadcast/output_0.npy new file mode 100644 index 000000000..cf617f2cf Binary files /dev/null and b/iree_tests/onnx/node/generated/test_equal_string_broadcast/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_equal_string_broadcast/test_data_flags.txt b/iree_tests/onnx/node/generated/test_equal_string_broadcast/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_equal_string_broadcast/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_erf/model.mlir b/iree_tests/onnx/node/generated/test_erf/model.mlir index 4352188cb..5d33db016 100644 --- a/iree_tests/onnx/node/generated/test_erf/model.mlir +++ b/iree_tests/onnx/node/generated/test_erf/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_erf(%arg0: !torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Erf"(%arg0) : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Erf"(%arg0) : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> return %0 : !torch.vtensor<[1,3,32,32],f32> } } diff --git a/iree_tests/onnx/node/generated/test_exp/model.mlir b/iree_tests/onnx/node/generated/test_exp/model.mlir index a9facb8ce..4f7446aa8 100644 --- a/iree_tests/onnx/node/generated/test_exp/model.mlir +++ b/iree_tests/onnx/node/generated/test_exp/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_exp(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_exp_example/model.mlir b/iree_tests/onnx/node/generated/test_exp_example/model.mlir index 8466cae40..d93ef0d4f 100644 --- a/iree_tests/onnx/node/generated/test_exp_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_exp_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_exp_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_expand_dim_changed/model.mlir b/iree_tests/onnx/node/generated/test_expand_dim_changed/model.mlir index 15acdfbd0..e0e4f35a7 100644 --- a/iree_tests/onnx/node/generated/test_expand_dim_changed/model.mlir +++ b/iree_tests/onnx/node/generated/test_expand_dim_changed/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_expand_dim_changed(%arg0: !torch.vtensor<[3,1],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,6],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Expand"(%arg0, %arg1) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,6],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Expand"(%arg0, %arg1) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,6],f32> return %0 : !torch.vtensor<[2,3,6],f32> } } diff --git a/iree_tests/onnx/node/generated/test_expand_dim_unchanged/model.mlir b/iree_tests/onnx/node/generated/test_expand_dim_unchanged/model.mlir index a31b202aa..da78a0564 100644 --- a/iree_tests/onnx/node/generated/test_expand_dim_unchanged/model.mlir +++ b/iree_tests/onnx/node/generated/test_expand_dim_unchanged/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_expand_dim_unchanged(%arg0: !torch.vtensor<[3,1],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Expand"(%arg0, %arg1) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Expand"(%arg0, %arg1) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,4],f32> return %0 : !torch.vtensor<[3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_eyelike_populate_off_main_diagonal/model.mlir b/iree_tests/onnx/node/generated/test_eyelike_populate_off_main_diagonal/model.mlir index cf258f7b0..c6a5caf35 100644 --- a/iree_tests/onnx/node/generated/test_eyelike_populate_off_main_diagonal/model.mlir +++ b/iree_tests/onnx/node/generated/test_eyelike_populate_off_main_diagonal/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_eyelike_populate_off_main_diagonal(%arg0: !torch.vtensor<[4,5],si32>) -> !torch.vtensor<[4,5],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.EyeLike"(%arg0) {torch.onnx.dtype = 1 : si64, torch.onnx.k = 1 : si64} : (!torch.vtensor<[4,5],si32>) -> !torch.vtensor<[4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.EyeLike"(%arg0) {torch.onnx.dtype = 1 : si64, torch.onnx.k = 1 : si64} : (!torch.vtensor<[4,5],si32>) -> !torch.vtensor<[4,5],f32> return %0 : !torch.vtensor<[4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_eyelike_with_dtype/model.mlir b/iree_tests/onnx/node/generated/test_eyelike_with_dtype/model.mlir index 4af9c9806..441ca94b3 100644 --- a/iree_tests/onnx/node/generated/test_eyelike_with_dtype/model.mlir +++ b/iree_tests/onnx/node/generated/test_eyelike_with_dtype/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_eyelike_with_dtype(%arg0: !torch.vtensor<[3,4],si32>) -> !torch.vtensor<[3,4],f64> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.EyeLike"(%arg0) {torch.onnx.dtype = 11 : si64} : (!torch.vtensor<[3,4],si32>) -> !torch.vtensor<[3,4],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.EyeLike"(%arg0) {torch.onnx.dtype = 11 : si64} : (!torch.vtensor<[3,4],si32>) -> !torch.vtensor<[3,4],f64> return %0 : !torch.vtensor<[3,4],f64> } } diff --git a/iree_tests/onnx/node/generated/test_eyelike_without_dtype/model.mlir b/iree_tests/onnx/node/generated/test_eyelike_without_dtype/model.mlir index e2dbd714c..50e76ca88 100644 --- a/iree_tests/onnx/node/generated/test_eyelike_without_dtype/model.mlir +++ b/iree_tests/onnx/node/generated/test_eyelike_without_dtype/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_eyelike_without_dtype(%arg0: !torch.vtensor<[4,4],si32>) -> !torch.vtensor<[4,4],si32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.EyeLike"(%arg0) : (!torch.vtensor<[4,4],si32>) -> !torch.vtensor<[4,4],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.EyeLike"(%arg0) : (!torch.vtensor<[4,4],si32>) -> !torch.vtensor<[4,4],si32> return %0 : !torch.vtensor<[4,4],si32> } } diff --git a/iree_tests/onnx/node/generated/test_flatten_axis0/model.mlir b/iree_tests/onnx/node/generated/test_flatten_axis0/model.mlir index 4ae553488..2bc61e5be 100644 --- a/iree_tests/onnx/node/generated/test_flatten_axis0/model.mlir +++ b/iree_tests/onnx/node/generated/test_flatten_axis0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_flatten_axis0(%arg0: !torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> return %0 : !torch.vtensor<[1,120],f32> } } diff --git a/iree_tests/onnx/node/generated/test_flatten_axis1/model.mlir b/iree_tests/onnx/node/generated/test_flatten_axis1/model.mlir index b496044e0..0c3039ee2 100644 --- a/iree_tests/onnx/node/generated/test_flatten_axis1/model.mlir +++ b/iree_tests/onnx/node/generated/test_flatten_axis1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_flatten_axis1(%arg0: !torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[2,60],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[2,60],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[2,60],f32> return %0 : !torch.vtensor<[2,60],f32> } } diff --git a/iree_tests/onnx/node/generated/test_flatten_axis2/model.mlir b/iree_tests/onnx/node/generated/test_flatten_axis2/model.mlir index b3c706860..b1560a191 100644 --- a/iree_tests/onnx/node/generated/test_flatten_axis2/model.mlir +++ b/iree_tests/onnx/node/generated/test_flatten_axis2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_flatten_axis2(%arg0: !torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[6,20],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[6,20],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[6,20],f32> return %0 : !torch.vtensor<[6,20],f32> } } diff --git a/iree_tests/onnx/node/generated/test_flatten_axis3/model.mlir b/iree_tests/onnx/node/generated/test_flatten_axis3/model.mlir index 8aaf3d3e9..2683fdc2c 100644 --- a/iree_tests/onnx/node/generated/test_flatten_axis3/model.mlir +++ b/iree_tests/onnx/node/generated/test_flatten_axis3/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_flatten_axis3(%arg0: !torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[24,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 3 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[24,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 3 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[24,5],f32> return %0 : !torch.vtensor<[24,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_flatten_default_axis/model.mlir b/iree_tests/onnx/node/generated/test_flatten_default_axis/model.mlir index a2c16d144..4a5b49397 100644 --- a/iree_tests/onnx/node/generated/test_flatten_default_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_flatten_default_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_flatten_default_axis(%arg0: !torch.vtensor<[5,4,3,2],f32>) -> !torch.vtensor<[5,24],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Flatten"(%arg0) : (!torch.vtensor<[5,4,3,2],f32>) -> !torch.vtensor<[5,24],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Flatten"(%arg0) : (!torch.vtensor<[5,4,3,2],f32>) -> !torch.vtensor<[5,24],f32> return %0 : !torch.vtensor<[5,24],f32> } } diff --git a/iree_tests/onnx/node/generated/test_flatten_negative_axis1/model.mlir b/iree_tests/onnx/node/generated/test_flatten_negative_axis1/model.mlir index dd513212d..a3546fc4f 100644 --- a/iree_tests/onnx/node/generated/test_flatten_negative_axis1/model.mlir +++ b/iree_tests/onnx/node/generated/test_flatten_negative_axis1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_flatten_negative_axis1(%arg0: !torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[24,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[24,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[24,5],f32> return %0 : !torch.vtensor<[24,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_flatten_negative_axis2/model.mlir b/iree_tests/onnx/node/generated/test_flatten_negative_axis2/model.mlir index 1f7f0839e..099ef7e65 100644 --- a/iree_tests/onnx/node/generated/test_flatten_negative_axis2/model.mlir +++ b/iree_tests/onnx/node/generated/test_flatten_negative_axis2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_flatten_negative_axis2(%arg0: !torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[6,20],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[6,20],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[6,20],f32> return %0 : !torch.vtensor<[6,20],f32> } } diff --git a/iree_tests/onnx/node/generated/test_flatten_negative_axis3/model.mlir b/iree_tests/onnx/node/generated/test_flatten_negative_axis3/model.mlir index 98240a242..39c4de95a 100644 --- a/iree_tests/onnx/node/generated/test_flatten_negative_axis3/model.mlir +++ b/iree_tests/onnx/node/generated/test_flatten_negative_axis3/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_flatten_negative_axis3(%arg0: !torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[2,60],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -3 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[2,60],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -3 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[2,60],f32> return %0 : !torch.vtensor<[2,60],f32> } } diff --git a/iree_tests/onnx/node/generated/test_flatten_negative_axis4/model.mlir b/iree_tests/onnx/node/generated/test_flatten_negative_axis4/model.mlir index 44c4b3af8..11037a7f7 100644 --- a/iree_tests/onnx/node/generated/test_flatten_negative_axis4/model.mlir +++ b/iree_tests/onnx/node/generated/test_flatten_negative_axis4/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_flatten_negative_axis4(%arg0: !torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -4 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -4 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> return %0 : !torch.vtensor<[1,120],f32> } } diff --git a/iree_tests/onnx/node/generated/test_floor/model.mlir b/iree_tests/onnx/node/generated/test_floor/model.mlir index 9295ca2d0..edf07030a 100644 --- a/iree_tests/onnx/node/generated/test_floor/model.mlir +++ b/iree_tests/onnx/node/generated/test_floor/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_floor(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Floor"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Floor"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_floor_example/model.mlir b/iree_tests/onnx/node/generated/test_floor_example/model.mlir index aab527033..28a0c1a8f 100644 --- a/iree_tests/onnx/node/generated/test_floor_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_floor_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_floor_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Floor"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Floor"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gather_0/model.mlir b/iree_tests/onnx/node/generated/test_gather_0/model.mlir index 2d37ebc1e..330c10595 100644 --- a/iree_tests/onnx/node/generated/test_gather_0/model.mlir +++ b/iree_tests/onnx/node/generated/test_gather_0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gather_0(%arg0: !torch.vtensor<[5,4,3,2],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,4,3,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gather"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5,4,3,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,4,3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gather"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5,4,3,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,4,3,2],f32> return %0 : !torch.vtensor<[3,4,3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gather_1/model.mlir b/iree_tests/onnx/node/generated/test_gather_1/model.mlir index 87c7fa68e..cbe9e0c33 100644 --- a/iree_tests/onnx/node/generated/test_gather_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_gather_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gather_1(%arg0: !torch.vtensor<[5,4,3,2],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[5,3,3,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gather"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[5,4,3,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[5,3,3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gather"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[5,4,3,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[5,3,3,2],f32> return %0 : !torch.vtensor<[5,3,3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gather_2d_indices/model.mlir b/iree_tests/onnx/node/generated/test_gather_2d_indices/model.mlir index 60cc6f77e..dc4526565 100644 --- a/iree_tests/onnx/node/generated/test_gather_2d_indices/model.mlir +++ b/iree_tests/onnx/node/generated/test_gather_2d_indices/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gather_2d_indices(%arg0: !torch.vtensor<[3,3],f32>, %arg1: !torch.vtensor<[1,2],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gather"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,3],f32>, !torch.vtensor<[1,2],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gather"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,3],f32>, !torch.vtensor<[1,2],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gather_elements_0/model.mlir b/iree_tests/onnx/node/generated/test_gather_elements_0/model.mlir index e4e9d6809..5242133b6 100644 --- a/iree_tests/onnx/node/generated/test_gather_elements_0/model.mlir +++ b/iree_tests/onnx/node/generated/test_gather_elements_0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gather_elements_0(%arg0: !torch.vtensor<[2,2],f32>, %arg1: !torch.vtensor<[2,2],si64>) -> !torch.vtensor<[2,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GatherElements"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2,2],si64>) -> !torch.vtensor<[2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GatherElements"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2,2],si64>) -> !torch.vtensor<[2,2],f32> return %0 : !torch.vtensor<[2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gather_elements_1/model.mlir b/iree_tests/onnx/node/generated/test_gather_elements_1/model.mlir index 80482f933..c372abdc0 100644 --- a/iree_tests/onnx/node/generated/test_gather_elements_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_gather_elements_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gather_elements_1(%arg0: !torch.vtensor<[3,3],f32>, %arg1: !torch.vtensor<[2,3],si64>) -> !torch.vtensor<[2,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GatherElements"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,3],f32>, !torch.vtensor<[2,3],si64>) -> !torch.vtensor<[2,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GatherElements"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,3],f32>, !torch.vtensor<[2,3],si64>) -> !torch.vtensor<[2,3],f32> return %0 : !torch.vtensor<[2,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gather_elements_negative_indices/model.mlir b/iree_tests/onnx/node/generated/test_gather_elements_negative_indices/model.mlir index dfdee543b..290e0db95 100644 --- a/iree_tests/onnx/node/generated/test_gather_elements_negative_indices/model.mlir +++ b/iree_tests/onnx/node/generated/test_gather_elements_negative_indices/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gather_elements_negative_indices(%arg0: !torch.vtensor<[3,3],f32>, %arg1: !torch.vtensor<[2,3],si64>) -> !torch.vtensor<[2,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GatherElements"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,3],f32>, !torch.vtensor<[2,3],si64>) -> !torch.vtensor<[2,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GatherElements"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,3],f32>, !torch.vtensor<[2,3],si64>) -> !torch.vtensor<[2,3],f32> return %0 : !torch.vtensor<[2,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gather_negative_indices/model.mlir b/iree_tests/onnx/node/generated/test_gather_negative_indices/model.mlir index 637bf469c..6f7b60f07 100644 --- a/iree_tests/onnx/node/generated/test_gather_negative_indices/model.mlir +++ b/iree_tests/onnx/node/generated/test_gather_negative_indices/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gather_negative_indices(%arg0: !torch.vtensor<[10],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gather"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[10],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gather"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[10],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gathernd_example_float32/model.mlir b/iree_tests/onnx/node/generated/test_gathernd_example_float32/model.mlir index c9098159f..03b1188ac 100644 --- a/iree_tests/onnx/node/generated/test_gathernd_example_float32/model.mlir +++ b/iree_tests/onnx/node/generated/test_gathernd_example_float32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gathernd_example_float32(%arg0: !torch.vtensor<[2,2,2],f32>, %arg1: !torch.vtensor<[2,1,2],si64>) -> !torch.vtensor<[2,1,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GatherND"(%arg0, %arg1) : (!torch.vtensor<[2,2,2],f32>, !torch.vtensor<[2,1,2],si64>) -> !torch.vtensor<[2,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GatherND"(%arg0, %arg1) : (!torch.vtensor<[2,2,2],f32>, !torch.vtensor<[2,1,2],si64>) -> !torch.vtensor<[2,1,2],f32> return %0 : !torch.vtensor<[2,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gathernd_example_int32/model.mlir b/iree_tests/onnx/node/generated/test_gathernd_example_int32/model.mlir index d330959e7..f6e3ca6a8 100644 --- a/iree_tests/onnx/node/generated/test_gathernd_example_int32/model.mlir +++ b/iree_tests/onnx/node/generated/test_gathernd_example_int32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gathernd_example_int32(%arg0: !torch.vtensor<[2,2],si32>, %arg1: !torch.vtensor<[2,2],si64>) -> !torch.vtensor<[2],si32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GatherND"(%arg0, %arg1) : (!torch.vtensor<[2,2],si32>, !torch.vtensor<[2,2],si64>) -> !torch.vtensor<[2],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.GatherND"(%arg0, %arg1) : (!torch.vtensor<[2,2],si32>, !torch.vtensor<[2,2],si64>) -> !torch.vtensor<[2],si32> return %0 : !torch.vtensor<[2],si32> } } diff --git a/iree_tests/onnx/node/generated/test_gathernd_example_int32_batch_dim1/model.mlir b/iree_tests/onnx/node/generated/test_gathernd_example_int32_batch_dim1/model.mlir index 91c53dd9a..09b2f3560 100644 --- a/iree_tests/onnx/node/generated/test_gathernd_example_int32_batch_dim1/model.mlir +++ b/iree_tests/onnx/node/generated/test_gathernd_example_int32_batch_dim1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gathernd_example_int32_batch_dim1(%arg0: !torch.vtensor<[2,2,2],si32>, %arg1: !torch.vtensor<[2,1],si64>) -> !torch.vtensor<[2,2],si32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GatherND"(%arg0, %arg1) {torch.onnx.batch_dims = 1 : si64} : (!torch.vtensor<[2,2,2],si32>, !torch.vtensor<[2,1],si64>) -> !torch.vtensor<[2,2],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.GatherND"(%arg0, %arg1) {torch.onnx.batch_dims = 1 : si64} : (!torch.vtensor<[2,2,2],si32>, !torch.vtensor<[2,1],si64>) -> !torch.vtensor<[2,2],si32> return %0 : !torch.vtensor<[2,2],si32> } } diff --git a/iree_tests/onnx/node/generated/test_gelu_default_1/model.mlir b/iree_tests/onnx/node/generated/test_gelu_default_1/model.mlir index 7ab5964ed..53225e7dc 100644 --- a/iree_tests/onnx/node/generated/test_gelu_default_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_gelu_default_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gelu_default_1(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gelu"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gelu"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gelu_default_1_expanded/model.mlir b/iree_tests/onnx/node/generated/test_gelu_default_1_expanded/model.mlir index bb53f9a0c..b3e161386 100644 --- a/iree_tests/onnx/node/generated/test_gelu_default_1_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_gelu_default_1_expanded/model.mlir @@ -1,17 +1,18 @@ module { func.func @test_gelu_default_1_expanded(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<5.000000e-01> : tensor) : !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<2.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %6 = torch.operator "onnx.Sqrt"(%5) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Div"(%arg0, %6) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> - %8 = torch.operator "onnx.Erf"(%7) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %9 = torch.operator "onnx.Sum"(%3, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %10 = torch.operator "onnx.Mul"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %11 = torch.operator "onnx.Mul"(%10, %9) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<5.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Sqrt"(%5) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Div"(%arg0, %6) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> + %8 = torch.operator "onnx.Erf"(%7) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %9 = torch.operator "onnx.Sum"(%3, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %10 = torch.operator "onnx.Mul"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %11 = torch.operator "onnx.Mul"(%10, %9) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %11 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gelu_default_2/model.mlir b/iree_tests/onnx/node/generated/test_gelu_default_2/model.mlir index 34aa43408..0e1595fa4 100644 --- a/iree_tests/onnx/node/generated/test_gelu_default_2/model.mlir +++ b/iree_tests/onnx/node/generated/test_gelu_default_2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gelu_default_2(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gelu"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gelu"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gelu_default_2_expanded/model.mlir b/iree_tests/onnx/node/generated/test_gelu_default_2_expanded/model.mlir index 79d3feac4..fba1f82f3 100644 --- a/iree_tests/onnx/node/generated/test_gelu_default_2_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_gelu_default_2_expanded/model.mlir @@ -1,17 +1,18 @@ module { func.func @test_gelu_default_2_expanded(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<5.000000e-01> : tensor) : !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<2.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %6 = torch.operator "onnx.Sqrt"(%5) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Div"(%arg0, %6) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> - %8 = torch.operator "onnx.Erf"(%7) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %9 = torch.operator "onnx.Sum"(%3, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %10 = torch.operator "onnx.Mul"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %11 = torch.operator "onnx.Mul"(%10, %9) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<5.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Sqrt"(%5) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Div"(%arg0, %6) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %8 = torch.operator "onnx.Erf"(%7) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %9 = torch.operator "onnx.Sum"(%3, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %10 = torch.operator "onnx.Mul"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %11 = torch.operator "onnx.Mul"(%10, %9) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %11 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gelu_tanh_1/model.mlir b/iree_tests/onnx/node/generated/test_gelu_tanh_1/model.mlir index 63785e4a2..c5b9b19cb 100644 --- a/iree_tests/onnx/node/generated/test_gelu_tanh_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_gelu_tanh_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gelu_tanh_1(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gelu"(%arg0) {torch.onnx.approximate = "tanh"} : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gelu"(%arg0) {torch.onnx.approximate = "tanh"} : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gelu_tanh_1_expanded/model.mlir b/iree_tests/onnx/node/generated/test_gelu_tanh_1_expanded/model.mlir index 19f13bb99..2ff42c232 100644 --- a/iree_tests/onnx/node/generated/test_gelu_tanh_1_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_gelu_tanh_1_expanded/model.mlir @@ -1,24 +1,25 @@ module { func.func @test_gelu_tanh_1_expanded(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<5.000000e-01> : tensor) : !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<0.636619746> : tensor) : !torch.vtensor<[],f32> - %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %6 = torch.vtensor.literal(dense<4.471500e-02> : tensor) : !torch.vtensor<[],f32> - %7 = torch.operator "onnx.CastLike"(%6, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %8 = torch.operator "onnx.Sqrt"(%5) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %9 = torch.vtensor.literal(dense<3.000000e+00> : tensor) : !torch.vtensor<[],f32> - %10 = torch.operator "onnx.CastLike"(%9, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %11 = torch.operator "onnx.Pow"(%arg0, %10) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> - %12 = torch.operator "onnx.Mul"(%7, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %13 = torch.operator "onnx.Sum"(%arg0, %12) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %14 = torch.operator "onnx.Mul"(%8, %13) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %15 = torch.operator "onnx.Tanh"(%14) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %16 = torch.operator "onnx.Sum"(%3, %15) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %17 = torch.operator "onnx.Mul"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<5.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.636619746> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<4.471500e-02> : tensor} : () -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.CastLike"(%6, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.Sqrt"(%5) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %9 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<3.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %10 = torch.operator "onnx.CastLike"(%9, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.Pow"(%arg0, %10) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> + %12 = torch.operator "onnx.Mul"(%7, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %13 = torch.operator "onnx.Sum"(%arg0, %12) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %14 = torch.operator "onnx.Mul"(%8, %13) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %15 = torch.operator "onnx.Tanh"(%14) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %16 = torch.operator "onnx.Sum"(%3, %15) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %17 = torch.operator "onnx.Mul"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %18 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gelu_tanh_2/model.mlir b/iree_tests/onnx/node/generated/test_gelu_tanh_2/model.mlir index 00d87ea34..822441a78 100644 --- a/iree_tests/onnx/node/generated/test_gelu_tanh_2/model.mlir +++ b/iree_tests/onnx/node/generated/test_gelu_tanh_2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gelu_tanh_2(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gelu"(%arg0) {torch.onnx.approximate = "tanh"} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gelu"(%arg0) {torch.onnx.approximate = "tanh"} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gelu_tanh_2_expanded/model.mlir b/iree_tests/onnx/node/generated/test_gelu_tanh_2_expanded/model.mlir index 3fee102f2..b48fef21d 100644 --- a/iree_tests/onnx/node/generated/test_gelu_tanh_2_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_gelu_tanh_2_expanded/model.mlir @@ -1,24 +1,25 @@ module { func.func @test_gelu_tanh_2_expanded(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<5.000000e-01> : tensor) : !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<0.636619746> : tensor) : !torch.vtensor<[],f32> - %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %6 = torch.vtensor.literal(dense<4.471500e-02> : tensor) : !torch.vtensor<[],f32> - %7 = torch.operator "onnx.CastLike"(%6, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %8 = torch.operator "onnx.Sqrt"(%5) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %9 = torch.vtensor.literal(dense<3.000000e+00> : tensor) : !torch.vtensor<[],f32> - %10 = torch.operator "onnx.CastLike"(%9, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %11 = torch.operator "onnx.Pow"(%arg0, %10) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> - %12 = torch.operator "onnx.Mul"(%7, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %13 = torch.operator "onnx.Sum"(%arg0, %12) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %14 = torch.operator "onnx.Mul"(%8, %13) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %15 = torch.operator "onnx.Tanh"(%14) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %16 = torch.operator "onnx.Sum"(%3, %15) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %17 = torch.operator "onnx.Mul"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<5.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.636619746> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<4.471500e-02> : tensor} : () -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.CastLike"(%6, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.Sqrt"(%5) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %9 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<3.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %10 = torch.operator "onnx.CastLike"(%9, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.Pow"(%arg0, %10) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %12 = torch.operator "onnx.Mul"(%7, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %13 = torch.operator "onnx.Sum"(%arg0, %12) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %14 = torch.operator "onnx.Mul"(%8, %13) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %15 = torch.operator "onnx.Tanh"(%14) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %16 = torch.operator "onnx.Sum"(%3, %15) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %17 = torch.operator "onnx.Mul"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %18 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gemm_all_attributes/model.mlir b/iree_tests/onnx/node/generated/test_gemm_all_attributes/model.mlir index f41c0ddb3..3ade5bc0b 100644 --- a/iree_tests/onnx/node/generated/test_gemm_all_attributes/model.mlir +++ b/iree_tests/onnx/node/generated/test_gemm_all_attributes/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gemm_all_attributes(%arg0: !torch.vtensor<[4,3],f32>, %arg1: !torch.vtensor<[5,4],f32>, %arg2: !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[3,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) {torch.onnx.alpha = 2.500000e-01 : f32, torch.onnx.beta = 3.500000e-01 : f32, torch.onnx.transA = 1 : si64, torch.onnx.transB = 1 : si64} : (!torch.vtensor<[4,3],f32>, !torch.vtensor<[5,4],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[3,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) {torch.onnx.alpha = 2.500000e-01 : f32, torch.onnx.beta = 3.500000e-01 : f32, torch.onnx.transA = 1 : si64, torch.onnx.transB = 1 : si64} : (!torch.vtensor<[4,3],f32>, !torch.vtensor<[5,4],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[3,5],f32> return %0 : !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gemm_alpha/model.mlir b/iree_tests/onnx/node/generated/test_gemm_alpha/model.mlir index 2b6db3807..59c0bdafe 100644 --- a/iree_tests/onnx/node/generated/test_gemm_alpha/model.mlir +++ b/iree_tests/onnx/node/generated/test_gemm_alpha/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gemm_alpha(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[5,4],f32>, %arg2: !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) {torch.onnx.alpha = 5.000000e-01 : f32} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[5,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) {torch.onnx.alpha = 5.000000e-01 : f32} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[5,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> return %0 : !torch.vtensor<[3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gemm_beta/model.mlir b/iree_tests/onnx/node/generated/test_gemm_beta/model.mlir index 0b229201b..8174c7471 100644 --- a/iree_tests/onnx/node/generated/test_gemm_beta/model.mlir +++ b/iree_tests/onnx/node/generated/test_gemm_beta/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gemm_beta(%arg0: !torch.vtensor<[2,7],f32>, %arg1: !torch.vtensor<[7,4],f32>, %arg2: !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[2,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) {torch.onnx.beta = 5.000000e-01 : f32} : (!torch.vtensor<[2,7],f32>, !torch.vtensor<[7,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) {torch.onnx.beta = 5.000000e-01 : f32} : (!torch.vtensor<[2,7],f32>, !torch.vtensor<[7,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[2,4],f32> return %0 : !torch.vtensor<[2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gemm_default_matrix_bias/model.mlir b/iree_tests/onnx/node/generated/test_gemm_default_matrix_bias/model.mlir index d844f7a5b..145952791 100644 --- a/iree_tests/onnx/node/generated/test_gemm_default_matrix_bias/model.mlir +++ b/iree_tests/onnx/node/generated/test_gemm_default_matrix_bias/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gemm_default_matrix_bias(%arg0: !torch.vtensor<[3,6],f32>, %arg1: !torch.vtensor<[6,4],f32>, %arg2: !torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3,6],f32>, !torch.vtensor<[6,4],f32>, !torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3,6],f32>, !torch.vtensor<[6,4],f32>, !torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> return %0 : !torch.vtensor<[3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gemm_default_no_bias/model.mlir b/iree_tests/onnx/node/generated/test_gemm_default_no_bias/model.mlir index 07f14d057..6ea6e6f2e 100644 --- a/iree_tests/onnx/node/generated/test_gemm_default_no_bias/model.mlir +++ b/iree_tests/onnx/node/generated/test_gemm_default_no_bias/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gemm_default_no_bias(%arg0: !torch.vtensor<[2,10],f32>, %arg1: !torch.vtensor<[10,3],f32>) -> !torch.vtensor<[2,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gemm"(%arg0, %arg1) : (!torch.vtensor<[2,10],f32>, !torch.vtensor<[10,3],f32>) -> !torch.vtensor<[2,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gemm"(%arg0, %arg1) : (!torch.vtensor<[2,10],f32>, !torch.vtensor<[10,3],f32>) -> !torch.vtensor<[2,3],f32> return %0 : !torch.vtensor<[2,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gemm_default_scalar_bias/model.mlir b/iree_tests/onnx/node/generated/test_gemm_default_scalar_bias/model.mlir index e86f55d65..29a0280c2 100644 --- a/iree_tests/onnx/node/generated/test_gemm_default_scalar_bias/model.mlir +++ b/iree_tests/onnx/node/generated/test_gemm_default_scalar_bias/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gemm_default_scalar_bias(%arg0: !torch.vtensor<[2,3],f32>, %arg1: !torch.vtensor<[3,4],f32>, %arg2: !torch.vtensor<[],f32>) -> !torch.vtensor<[2,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) : (!torch.vtensor<[2,3],f32>, !torch.vtensor<[3,4],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) : (!torch.vtensor<[2,3],f32>, !torch.vtensor<[3,4],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[2,4],f32> return %0 : !torch.vtensor<[2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gemm_default_single_elem_vector_bias/model.mlir b/iree_tests/onnx/node/generated/test_gemm_default_single_elem_vector_bias/model.mlir index b8c6fd213..5a91ed965 100644 --- a/iree_tests/onnx/node/generated/test_gemm_default_single_elem_vector_bias/model.mlir +++ b/iree_tests/onnx/node/generated/test_gemm_default_single_elem_vector_bias/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gemm_default_single_elem_vector_bias(%arg0: !torch.vtensor<[3,7],f32>, %arg1: !torch.vtensor<[7,3],f32>, %arg2: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3,7],f32>, !torch.vtensor<[7,3],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3,7],f32>, !torch.vtensor<[7,3],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,3],f32> return %0 : !torch.vtensor<[3,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gemm_default_vector_bias/model.mlir b/iree_tests/onnx/node/generated/test_gemm_default_vector_bias/model.mlir index b97b6dd74..14ea25053 100644 --- a/iree_tests/onnx/node/generated/test_gemm_default_vector_bias/model.mlir +++ b/iree_tests/onnx/node/generated/test_gemm_default_vector_bias/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gemm_default_vector_bias(%arg0: !torch.vtensor<[2,7],f32>, %arg1: !torch.vtensor<[7,4],f32>, %arg2: !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[2,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) : (!torch.vtensor<[2,7],f32>, !torch.vtensor<[7,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) : (!torch.vtensor<[2,7],f32>, !torch.vtensor<[7,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[2,4],f32> return %0 : !torch.vtensor<[2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gemm_default_zero_bias/model.mlir b/iree_tests/onnx/node/generated/test_gemm_default_zero_bias/model.mlir index 7a77a70f8..5ce77ece9 100644 --- a/iree_tests/onnx/node/generated/test_gemm_default_zero_bias/model.mlir +++ b/iree_tests/onnx/node/generated/test_gemm_default_zero_bias/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gemm_default_zero_bias(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[5,4],f32>, %arg2: !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[5,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[5,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> return %0 : !torch.vtensor<[3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gemm_transposeA/model.mlir b/iree_tests/onnx/node/generated/test_gemm_transposeA/model.mlir index dee0306d3..798929091 100644 --- a/iree_tests/onnx/node/generated/test_gemm_transposeA/model.mlir +++ b/iree_tests/onnx/node/generated/test_gemm_transposeA/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gemm_transposeA(%arg0: !torch.vtensor<[6,3],f32>, %arg1: !torch.vtensor<[6,4],f32>, %arg2: !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) {torch.onnx.transA = 1 : si64} : (!torch.vtensor<[6,3],f32>, !torch.vtensor<[6,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) {torch.onnx.transA = 1 : si64} : (!torch.vtensor<[6,3],f32>, !torch.vtensor<[6,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> return %0 : !torch.vtensor<[3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gemm_transposeB/model.mlir b/iree_tests/onnx/node/generated/test_gemm_transposeB/model.mlir index 0750ececc..ca3322496 100644 --- a/iree_tests/onnx/node/generated/test_gemm_transposeB/model.mlir +++ b/iree_tests/onnx/node/generated/test_gemm_transposeB/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gemm_transposeB(%arg0: !torch.vtensor<[3,6],f32>, %arg1: !torch.vtensor<[4,6],f32>, %arg2: !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) {torch.onnx.transB = 1 : si64} : (!torch.vtensor<[3,6],f32>, !torch.vtensor<[4,6],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Gemm"(%arg0, %arg1, %arg2) {torch.onnx.transB = 1 : si64} : (!torch.vtensor<[3,6],f32>, !torch.vtensor<[4,6],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> return %0 : !torch.vtensor<[3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_globalaveragepool/model.mlir b/iree_tests/onnx/node/generated/test_globalaveragepool/model.mlir index f4977a987..19e70f898 100644 --- a/iree_tests/onnx/node/generated/test_globalaveragepool/model.mlir +++ b/iree_tests/onnx/node/generated/test_globalaveragepool/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_globalaveragepool(%arg0: !torch.vtensor<[1,3,5,5],f32>) -> !torch.vtensor<[1,3,1,1],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 1 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GlobalAveragePool"(%arg0) : (!torch.vtensor<[1,3,5,5],f32>) -> !torch.vtensor<[1,3,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GlobalAveragePool"(%arg0) : (!torch.vtensor<[1,3,5,5],f32>) -> !torch.vtensor<[1,3,1,1],f32> return %0 : !torch.vtensor<[1,3,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_globalaveragepool_precomputed/model.mlir b/iree_tests/onnx/node/generated/test_globalaveragepool_precomputed/model.mlir index 83c91ed7b..5a5477770 100644 --- a/iree_tests/onnx/node/generated/test_globalaveragepool_precomputed/model.mlir +++ b/iree_tests/onnx/node/generated/test_globalaveragepool_precomputed/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_globalaveragepool_precomputed(%arg0: !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,1,1],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 1 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GlobalAveragePool"(%arg0) : (!torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GlobalAveragePool"(%arg0) : (!torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,1,1],f32> return %0 : !torch.vtensor<[1,1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_globalmaxpool/model.mlir b/iree_tests/onnx/node/generated/test_globalmaxpool/model.mlir index 3553f24c0..e8e813662 100644 --- a/iree_tests/onnx/node/generated/test_globalmaxpool/model.mlir +++ b/iree_tests/onnx/node/generated/test_globalmaxpool/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_globalmaxpool(%arg0: !torch.vtensor<[1,3,5,5],f32>) -> !torch.vtensor<[1,3,1,1],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 1 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GlobalMaxPool"(%arg0) : (!torch.vtensor<[1,3,5,5],f32>) -> !torch.vtensor<[1,3,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GlobalMaxPool"(%arg0) : (!torch.vtensor<[1,3,5,5],f32>) -> !torch.vtensor<[1,3,1,1],f32> return %0 : !torch.vtensor<[1,3,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_globalmaxpool_precomputed/model.mlir b/iree_tests/onnx/node/generated/test_globalmaxpool_precomputed/model.mlir index 8682e91ad..84e500b02 100644 --- a/iree_tests/onnx/node/generated/test_globalmaxpool_precomputed/model.mlir +++ b/iree_tests/onnx/node/generated/test_globalmaxpool_precomputed/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_globalmaxpool_precomputed(%arg0: !torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,1,1],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 1 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GlobalMaxPool"(%arg0) : (!torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GlobalMaxPool"(%arg0) : (!torch.vtensor<[1,1,3,3],f32>) -> !torch.vtensor<[1,1,1,1],f32> return %0 : !torch.vtensor<[1,1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_greater/model.mlir b/iree_tests/onnx/node/generated/test_greater/model.mlir index 183dcf6eb..83d8cdff1 100644 --- a/iree_tests/onnx/node/generated/test_greater/model.mlir +++ b/iree_tests/onnx/node/generated/test_greater/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_greater(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Greater"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Greater"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_greater_bcast/model.mlir b/iree_tests/onnx/node/generated/test_greater_bcast/model.mlir index 4dfdda410..08e2a8d03 100644 --- a/iree_tests/onnx/node/generated/test_greater_bcast/model.mlir +++ b/iree_tests/onnx/node/generated/test_greater_bcast/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_greater_bcast(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Greater"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Greater"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_greater_equal/model.mlir b/iree_tests/onnx/node/generated/test_greater_equal/model.mlir index 73604759e..1b6001022 100644 --- a/iree_tests/onnx/node/generated/test_greater_equal/model.mlir +++ b/iree_tests/onnx/node/generated/test_greater_equal/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_greater_equal(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GreaterOrEqual"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.GreaterOrEqual"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_greater_equal_bcast/model.mlir b/iree_tests/onnx/node/generated/test_greater_equal_bcast/model.mlir index 2550748c3..43ad2c9f8 100644 --- a/iree_tests/onnx/node/generated/test_greater_equal_bcast/model.mlir +++ b/iree_tests/onnx/node/generated/test_greater_equal_bcast/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_greater_equal_bcast(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GreaterOrEqual"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.GreaterOrEqual"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_greater_equal_bcast_expanded/model.mlir b/iree_tests/onnx/node/generated/test_greater_equal_bcast_expanded/model.mlir index 895901854..0b6e1de76 100644 --- a/iree_tests/onnx/node/generated/test_greater_equal_bcast_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_greater_equal_bcast_expanded/model.mlir @@ -1,8 +1,9 @@ module { func.func @test_greater_equal_bcast_expanded(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Greater"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> - %1 = torch.operator "onnx.Equal"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> - %2 = torch.operator "onnx.Or"(%0, %1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Greater"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> + %1 = torch.operator "onnx.Equal"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> + %2 = torch.operator "onnx.Or"(%0, %1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> return %2 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_greater_equal_expanded/model.mlir b/iree_tests/onnx/node/generated/test_greater_equal_expanded/model.mlir index d09c499b7..60ffd3273 100644 --- a/iree_tests/onnx/node/generated/test_greater_equal_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_greater_equal_expanded/model.mlir @@ -1,8 +1,9 @@ module { func.func @test_greater_equal_expanded(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Greater"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> - %1 = torch.operator "onnx.Equal"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> - %2 = torch.operator "onnx.Or"(%0, %1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Greater"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> + %1 = torch.operator "onnx.Equal"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> + %2 = torch.operator "onnx.Or"(%0, %1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> return %2 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample/model.mlir b/iree_tests/onnx/node/generated/test_gridsample/model.mlir index b3e7ee3c3..c3a07eb4f 100644 --- a/iree_tests/onnx/node/generated/test_gridsample/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[1,6,6,2],f32>) -> !torch.vtensor<[1,1,6,6],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 0 : si64, torch.onnx.mode = "linear", torch.onnx.padding_mode = "zeros"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.vtensor<[1,6,6,2],f32>) -> !torch.vtensor<[1,1,6,6],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 0 : si64, torch.onnx.mode = "linear", torch.onnx.padding_mode = "zeros"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.vtensor<[1,6,6,2],f32>) -> !torch.vtensor<[1,1,6,6],f32> return %0 : !torch.vtensor<[1,1,6,6],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_aligncorners_true/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_aligncorners_true/model.mlir index f7f0c3d3c..82d047b8a 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_aligncorners_true/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_aligncorners_true/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_aligncorners_true(%arg0: !torch.vtensor<[1,1,3,2],f32>, %arg1: !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 1 : si64, torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 1 : si64, torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> return %0 : !torch.vtensor<[1,1,2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_bicubic/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_bicubic/model.mlir index 534e0fc90..87a1bfe8a 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_bicubic/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_bicubic/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_bicubic(%arg0: !torch.vtensor<[1,1,3,2],f32>, %arg1: !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> return %0 : !torch.vtensor<[1,1,2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_bicubic_align_corners_0_additional_1/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_bicubic_align_corners_0_additional_1/model.mlir index aa451db02..fb7f1344c 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_bicubic_align_corners_0_additional_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_bicubic_align_corners_0_additional_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_bicubic_align_corners_0_additional_1(%arg0: !torch.vtensor<[1,1,3,2],f32>, %arg1: !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 0 : si64, torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 0 : si64, torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> return %0 : !torch.vtensor<[1,1,2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_bicubic_align_corners_1_additional_1/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_bicubic_align_corners_1_additional_1/model.mlir index f1335d937..8c249524a 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_bicubic_align_corners_1_additional_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_bicubic_align_corners_1_additional_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_bicubic_align_corners_1_additional_1(%arg0: !torch.vtensor<[1,1,3,2],f32>, %arg1: !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 1 : si64, torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 1 : si64, torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> return %0 : !torch.vtensor<[1,1,2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_bilinear/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_bilinear/model.mlir index e9048b729..760504401 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_bilinear/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_bilinear/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_bilinear(%arg0: !torch.vtensor<[1,1,3,2],f32>, %arg1: !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> return %0 : !torch.vtensor<[1,1,2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_bilinear_align_corners_0_additional_1/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_bilinear_align_corners_0_additional_1/model.mlir index 8288e1f90..3dcefb9fe 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_bilinear_align_corners_0_additional_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_bilinear_align_corners_0_additional_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_bilinear_align_corners_0_additional_1(%arg0: !torch.vtensor<[1,1,3,2],f32>, %arg1: !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 0 : si64, torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 0 : si64, torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> return %0 : !torch.vtensor<[1,1,2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_bilinear_align_corners_1_additional_1/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_bilinear_align_corners_1_additional_1/model.mlir index ed13e9e7f..2ebcdb278 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_bilinear_align_corners_1_additional_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_bilinear_align_corners_1_additional_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_bilinear_align_corners_1_additional_1(%arg0: !torch.vtensor<[1,1,3,2],f32>, %arg1: !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 1 : si64, torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 1 : si64, torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> return %0 : !torch.vtensor<[1,1,2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_border_padding/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_border_padding/model.mlir index 2e03138e3..395fa8bdb 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_border_padding/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_border_padding/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_border_padding(%arg0: !torch.vtensor<[1,1,3,2],f32>, %arg1: !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.padding_mode = "border"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.padding_mode = "border"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> return %0 : !torch.vtensor<[1,1,2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_nearest/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_nearest/model.mlir index 131c7e4d0..b7858e514 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_nearest/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_nearest/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_nearest(%arg0: !torch.vtensor<[1,1,3,2],f32>, %arg1: !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> return %0 : !torch.vtensor<[1,1,2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_nearest_align_corners_0_additional_1/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_nearest_align_corners_0_additional_1/model.mlir index 49e0c6a9d..f8d8d51fd 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_nearest_align_corners_0_additional_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_nearest_align_corners_0_additional_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_nearest_align_corners_0_additional_1(%arg0: !torch.vtensor<[1,1,3,2],f32>, %arg1: !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 0 : si64, torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 0 : si64, torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> return %0 : !torch.vtensor<[1,1,2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_nearest_align_corners_1_additional_1/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_nearest_align_corners_1_additional_1/model.mlir index f48aac226..860b9cc1e 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_nearest_align_corners_1_additional_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_nearest_align_corners_1_additional_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_nearest_align_corners_1_additional_1(%arg0: !torch.vtensor<[1,1,3,2],f32>, %arg1: !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 1 : si64, torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 1 : si64, torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> return %0 : !torch.vtensor<[1,1,2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_reflection_padding/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_reflection_padding/model.mlir index f617d5d5d..7914b5f0c 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_reflection_padding/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_reflection_padding/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_reflection_padding(%arg0: !torch.vtensor<[1,1,3,2],f32>, %arg1: !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.padding_mode = "reflection"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.padding_mode = "reflection"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> return %0 : !torch.vtensor<[1,1,2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_volumetric_bilinear_align_corners_0/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_volumetric_bilinear_align_corners_0/model.mlir index d35913f2c..df237ccaf 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_volumetric_bilinear_align_corners_0/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_volumetric_bilinear_align_corners_0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_volumetric_bilinear_align_corners_0(%arg0: !torch.vtensor<[1,1,3,2,2],f32>, %arg1: !torch.vtensor<[1,2,4,2,3],f32>) -> !torch.vtensor<[1,1,2,4,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 0 : si64, torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,3,2,2],f32>, !torch.vtensor<[1,2,4,2,3],f32>) -> !torch.vtensor<[1,1,2,4,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 0 : si64, torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,3,2,2],f32>, !torch.vtensor<[1,2,4,2,3],f32>) -> !torch.vtensor<[1,1,2,4,2],f32> return %0 : !torch.vtensor<[1,1,2,4,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_volumetric_bilinear_align_corners_1/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_volumetric_bilinear_align_corners_1/model.mlir index 38566158d..8c96bc261 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_volumetric_bilinear_align_corners_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_volumetric_bilinear_align_corners_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_volumetric_bilinear_align_corners_1(%arg0: !torch.vtensor<[1,1,3,2,2],f32>, %arg1: !torch.vtensor<[1,2,4,2,3],f32>) -> !torch.vtensor<[1,1,2,4,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 1 : si64, torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,3,2,2],f32>, !torch.vtensor<[1,2,4,2,3],f32>) -> !torch.vtensor<[1,1,2,4,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 1 : si64, torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,3,2,2],f32>, !torch.vtensor<[1,2,4,2,3],f32>) -> !torch.vtensor<[1,1,2,4,2],f32> return %0 : !torch.vtensor<[1,1,2,4,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_volumetric_nearest_align_corners_0/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_volumetric_nearest_align_corners_0/model.mlir index c8741cc96..1a602a9ea 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_volumetric_nearest_align_corners_0/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_volumetric_nearest_align_corners_0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_volumetric_nearest_align_corners_0(%arg0: !torch.vtensor<[1,1,3,2,2],f32>, %arg1: !torch.vtensor<[1,2,4,2,3],f32>) -> !torch.vtensor<[1,1,2,4,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 0 : si64, torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,3,2,2],f32>, !torch.vtensor<[1,2,4,2,3],f32>) -> !torch.vtensor<[1,1,2,4,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 0 : si64, torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,3,2,2],f32>, !torch.vtensor<[1,2,4,2,3],f32>) -> !torch.vtensor<[1,1,2,4,2],f32> return %0 : !torch.vtensor<[1,1,2,4,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_volumetric_nearest_align_corners_1/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_volumetric_nearest_align_corners_1/model.mlir index 69dfe4143..18067e962 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_volumetric_nearest_align_corners_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_volumetric_nearest_align_corners_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_volumetric_nearest_align_corners_1(%arg0: !torch.vtensor<[1,1,3,2,2],f32>, %arg1: !torch.vtensor<[1,2,4,2,3],f32>) -> !torch.vtensor<[1,1,2,4,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 1 : si64, torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,3,2,2],f32>, !torch.vtensor<[1,2,4,2,3],f32>) -> !torch.vtensor<[1,1,2,4,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.align_corners = 1 : si64, torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,3,2,2],f32>, !torch.vtensor<[1,2,4,2,3],f32>) -> !torch.vtensor<[1,1,2,4,2],f32> return %0 : !torch.vtensor<[1,1,2,4,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gridsample_zeros_padding/model.mlir b/iree_tests/onnx/node/generated/test_gridsample_zeros_padding/model.mlir index b6884f692..4ac48cd3a 100644 --- a/iree_tests/onnx/node/generated/test_gridsample_zeros_padding/model.mlir +++ b/iree_tests/onnx/node/generated/test_gridsample_zeros_padding/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gridsample_zeros_padding(%arg0: !torch.vtensor<[1,1,3,2],f32>, %arg1: !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.padding_mode = "zeros"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GridSample"(%arg0, %arg1) {torch.onnx.padding_mode = "zeros"} : (!torch.vtensor<[1,1,3,2],f32>, !torch.vtensor<[1,2,4,2],f32>) -> !torch.vtensor<[1,1,2,4],f32> return %0 : !torch.vtensor<[1,1,2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_group_normalization_epsilon/model.mlir b/iree_tests/onnx/node/generated/test_group_normalization_epsilon/model.mlir index a8be9f355..4174e08f1 100644 --- a/iree_tests/onnx/node/generated/test_group_normalization_epsilon/model.mlir +++ b/iree_tests/onnx/node/generated/test_group_normalization_epsilon/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_group_normalization_epsilon(%arg0: !torch.vtensor<[3,4,2,2],f32>, %arg1: !torch.vtensor<[4],f32>, %arg2: !torch.vtensor<[4],f32>) -> !torch.vtensor<[3,4,2,2],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GroupNormalization"(%arg0, %arg1, %arg2) {torch.onnx.epsilon = 0.00999999977 : f32, torch.onnx.num_groups = 2 : si64} : (!torch.vtensor<[3,4,2,2],f32>, !torch.vtensor<[4],f32>, !torch.vtensor<[4],f32>) -> !torch.vtensor<[3,4,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GroupNormalization"(%arg0, %arg1, %arg2) {torch.onnx.epsilon = 0.00999999977 : f32, torch.onnx.num_groups = 2 : si64} : (!torch.vtensor<[3,4,2,2],f32>, !torch.vtensor<[4],f32>, !torch.vtensor<[4],f32>) -> !torch.vtensor<[3,4,2,2],f32> return %0 : !torch.vtensor<[3,4,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_group_normalization_epsilon_expanded/model.mlir b/iree_tests/onnx/node/generated/test_group_normalization_epsilon_expanded/model.mlir index 95140c0c2..2e788b874 100644 --- a/iree_tests/onnx/node/generated/test_group_normalization_epsilon_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_group_normalization_epsilon_expanded/model.mlir @@ -1,39 +1,40 @@ module { func.func @test_group_normalization_epsilon_expanded(%arg0: !torch.vtensor<[3,4,2,2],f32>, %arg1: !torch.vtensor<[4],f32>, %arg2: !torch.vtensor<[4],f32>) -> !torch.vtensor<[3,4,2,2],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0.00999999977> : tensor<1xf32>) : !torch.vtensor<[1],f32> - %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> - %2 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[3,4,2,2],f32> - %3 = torch.operator "onnx.Shape"(%2) : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[4],si64> - %4 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = 2 : si64, torch.onnx.start = 1 : si64} : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[1],si64> - %5 = torch.vtensor.literal(dense<2> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %6 = torch.operator "onnx.Div"(%4, %5) : (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> - %7 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = 1 : si64, torch.onnx.start = 0 : si64} : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[1],si64> - %8 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.start = 2 : si64} : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[2],si64> - %9 = torch.operator "onnx.Concat"(%7, %5, %6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[5],si64> - %10 = torch.operator "onnx.Reshape"(%2, %9) : (!torch.vtensor<[3,4,2,2],f32>, !torch.vtensor<[5],si64>) -> !torch.vtensor<[?,?,?,?,?],f32> - %11 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [0 : si64, 0 : si64, -1 : si64]} : () -> !torch.vtensor<[3],si64> - %12 = torch.operator "onnx.Reshape"(%10, %11) : (!torch.vtensor<[?,?,?,?,?],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[?,?,?],f32> - %13 = torch.vtensor.literal(dense<2> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %14 = torch.operator "onnx.ReduceMean"(%12, %13) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?,?,1],f32> - %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> - %16 = torch.operator "onnx.ReduceMean"(%15, %13) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?,?,1],f32> - %17 = torch.operator "onnx.Mul"(%14, %14) : (!torch.vtensor<[?,?,1],f32>, !torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,1],f32> - %18 = torch.operator "onnx.Sub"(%16, %17) : (!torch.vtensor<[?,?,1],f32>, !torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,1],f32> - %19 = torch.operator "onnx.Add"(%18, %1) : (!torch.vtensor<[?,?,1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[?,?,1],f32> - %20 = torch.operator "onnx.Sqrt"(%19) : (!torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,1],f32> - %21 = torch.operator "onnx.Sub"(%12, %14) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,?],f32> - %22 = torch.operator "onnx.Div"(%21, %20) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,?],f32> - %23 = torch.operator "onnx.Reshape"(%22, %3) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[?,?,?,?],f32> - %24 = torch.operator "onnx.Reshape"(%23, %11) : (!torch.vtensor<[?,?,?,?],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[?,?,?],f32> - %25 = torch.operator "onnx.Cast"(%24) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> - %26 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [1 : si64, -1 : si64, 1 : si64]} : () -> !torch.vtensor<[3],si64> - %27 = torch.operator "onnx.Cast"(%arg1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[4],f32> - %28 = torch.operator "onnx.Cast"(%arg2) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[4],f32> - %29 = torch.operator "onnx.Reshape"(%27, %26) : (!torch.vtensor<[4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[1,4,1],f32> - %30 = torch.operator "onnx.Reshape"(%28, %26) : (!torch.vtensor<[4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[1,4,1],f32> - %31 = torch.operator "onnx.Mul"(%29, %25) : (!torch.vtensor<[1,4,1],f32>, !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,4,?],f32> - %32 = torch.operator "onnx.Add"(%31, %30) : (!torch.vtensor<[?,4,?],f32>, !torch.vtensor<[1,4,1],f32>) -> !torch.vtensor<[?,4,?],f32> - %33 = torch.operator "onnx.Reshape"(%32, %3) : (!torch.vtensor<[?,4,?],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[3,4,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.00999999977> : tensor<1xf32>} : () -> !torch.vtensor<[1],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + %2 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[3,4,2,2],f32> + %3 = torch.operator "onnx.Shape"(%2) : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[4],si64> + %4 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = 2 : si64, torch.onnx.start = 1 : si64} : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Div"(%4, %5) : (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %7 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = 1 : si64, torch.onnx.start = 0 : si64} : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.start = 2 : si64} : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[2],si64> + %9 = torch.operator "onnx.Concat"(%7, %5, %6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[5],si64> + %10 = torch.operator "onnx.Reshape"(%2, %9) : (!torch.vtensor<[3,4,2,2],f32>, !torch.vtensor<[5],si64>) -> !torch.vtensor<[?,?,?,?,?],f32> + %11 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [0 : si64, 0 : si64, -1 : si64]} : () -> !torch.vtensor<[3],si64> + %12 = torch.operator "onnx.Reshape"(%10, %11) : (!torch.vtensor<[?,?,?,?,?],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[?,?,?],f32> + %13 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %14 = torch.operator "onnx.ReduceMean"(%12, %13) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?,?,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> + %16 = torch.operator "onnx.ReduceMean"(%15, %13) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?,?,1],f32> + %17 = torch.operator "onnx.Mul"(%14, %14) : (!torch.vtensor<[?,?,1],f32>, !torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,1],f32> + %18 = torch.operator "onnx.Sub"(%16, %17) : (!torch.vtensor<[?,?,1],f32>, !torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,1],f32> + %19 = torch.operator "onnx.Add"(%18, %1) : (!torch.vtensor<[?,?,1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[?,?,1],f32> + %20 = torch.operator "onnx.Sqrt"(%19) : (!torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,1],f32> + %21 = torch.operator "onnx.Sub"(%12, %14) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,?],f32> + %22 = torch.operator "onnx.Div"(%21, %20) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,?],f32> + %23 = torch.operator "onnx.Reshape"(%22, %3) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[?,?,?,?],f32> + %24 = torch.operator "onnx.Reshape"(%23, %11) : (!torch.vtensor<[?,?,?,?],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[?,?,?],f32> + %25 = torch.operator "onnx.Cast"(%24) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> + %26 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [1 : si64, -1 : si64, 1 : si64]} : () -> !torch.vtensor<[3],si64> + %27 = torch.operator "onnx.Cast"(%arg1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[4],f32> + %28 = torch.operator "onnx.Cast"(%arg2) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[4],f32> + %29 = torch.operator "onnx.Reshape"(%27, %26) : (!torch.vtensor<[4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[1,4,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %26) : (!torch.vtensor<[4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[1,4,1],f32> + %31 = torch.operator "onnx.Mul"(%29, %25) : (!torch.vtensor<[1,4,1],f32>, !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,4,?],f32> + %32 = torch.operator "onnx.Add"(%31, %30) : (!torch.vtensor<[?,4,?],f32>, !torch.vtensor<[1,4,1],f32>) -> !torch.vtensor<[?,4,?],f32> + %33 = torch.operator "onnx.Reshape"(%32, %3) : (!torch.vtensor<[?,4,?],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[3,4,2,2],f32> return %33 : !torch.vtensor<[3,4,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_group_normalization_example/model.mlir b/iree_tests/onnx/node/generated/test_group_normalization_example/model.mlir index 781b64777..ffc8cd10f 100644 --- a/iree_tests/onnx/node/generated/test_group_normalization_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_group_normalization_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_group_normalization_example(%arg0: !torch.vtensor<[3,4,2,2],f32>, %arg1: !torch.vtensor<[4],f32>, %arg2: !torch.vtensor<[4],f32>) -> !torch.vtensor<[3,4,2,2],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.GroupNormalization"(%arg0, %arg1, %arg2) {torch.onnx.num_groups = 2 : si64} : (!torch.vtensor<[3,4,2,2],f32>, !torch.vtensor<[4],f32>, !torch.vtensor<[4],f32>) -> !torch.vtensor<[3,4,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.GroupNormalization"(%arg0, %arg1, %arg2) {torch.onnx.num_groups = 2 : si64} : (!torch.vtensor<[3,4,2,2],f32>, !torch.vtensor<[4],f32>, !torch.vtensor<[4],f32>) -> !torch.vtensor<[3,4,2,2],f32> return %0 : !torch.vtensor<[3,4,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_group_normalization_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_group_normalization_example_expanded/model.mlir index 2780211a2..1718ecab6 100644 --- a/iree_tests/onnx/node/generated/test_group_normalization_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_group_normalization_example_expanded/model.mlir @@ -1,39 +1,40 @@ module { func.func @test_group_normalization_example_expanded(%arg0: !torch.vtensor<[3,4,2,2],f32>, %arg1: !torch.vtensor<[4],f32>, %arg2: !torch.vtensor<[4],f32>) -> !torch.vtensor<[3,4,2,2],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<9.99999974E-6> : tensor<1xf32>) : !torch.vtensor<[1],f32> - %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> - %2 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[3,4,2,2],f32> - %3 = torch.operator "onnx.Shape"(%2) : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[4],si64> - %4 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = 2 : si64, torch.onnx.start = 1 : si64} : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[1],si64> - %5 = torch.vtensor.literal(dense<2> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %6 = torch.operator "onnx.Div"(%4, %5) : (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> - %7 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = 1 : si64, torch.onnx.start = 0 : si64} : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[1],si64> - %8 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.start = 2 : si64} : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[2],si64> - %9 = torch.operator "onnx.Concat"(%7, %5, %6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[5],si64> - %10 = torch.operator "onnx.Reshape"(%2, %9) : (!torch.vtensor<[3,4,2,2],f32>, !torch.vtensor<[5],si64>) -> !torch.vtensor<[?,?,?,?,?],f32> - %11 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [0 : si64, 0 : si64, -1 : si64]} : () -> !torch.vtensor<[3],si64> - %12 = torch.operator "onnx.Reshape"(%10, %11) : (!torch.vtensor<[?,?,?,?,?],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[?,?,?],f32> - %13 = torch.vtensor.literal(dense<2> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %14 = torch.operator "onnx.ReduceMean"(%12, %13) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?,?,1],f32> - %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> - %16 = torch.operator "onnx.ReduceMean"(%15, %13) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?,?,1],f32> - %17 = torch.operator "onnx.Mul"(%14, %14) : (!torch.vtensor<[?,?,1],f32>, !torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,1],f32> - %18 = torch.operator "onnx.Sub"(%16, %17) : (!torch.vtensor<[?,?,1],f32>, !torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,1],f32> - %19 = torch.operator "onnx.Add"(%18, %1) : (!torch.vtensor<[?,?,1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[?,?,1],f32> - %20 = torch.operator "onnx.Sqrt"(%19) : (!torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,1],f32> - %21 = torch.operator "onnx.Sub"(%12, %14) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,?],f32> - %22 = torch.operator "onnx.Div"(%21, %20) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,?],f32> - %23 = torch.operator "onnx.Reshape"(%22, %3) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[?,?,?,?],f32> - %24 = torch.operator "onnx.Reshape"(%23, %11) : (!torch.vtensor<[?,?,?,?],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[?,?,?],f32> - %25 = torch.operator "onnx.Cast"(%24) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> - %26 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [1 : si64, -1 : si64, 1 : si64]} : () -> !torch.vtensor<[3],si64> - %27 = torch.operator "onnx.Cast"(%arg1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[4],f32> - %28 = torch.operator "onnx.Cast"(%arg2) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[4],f32> - %29 = torch.operator "onnx.Reshape"(%27, %26) : (!torch.vtensor<[4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[1,4,1],f32> - %30 = torch.operator "onnx.Reshape"(%28, %26) : (!torch.vtensor<[4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[1,4,1],f32> - %31 = torch.operator "onnx.Mul"(%29, %25) : (!torch.vtensor<[1,4,1],f32>, !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,4,?],f32> - %32 = torch.operator "onnx.Add"(%31, %30) : (!torch.vtensor<[?,4,?],f32>, !torch.vtensor<[1,4,1],f32>) -> !torch.vtensor<[?,4,?],f32> - %33 = torch.operator "onnx.Reshape"(%32, %3) : (!torch.vtensor<[?,4,?],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[3,4,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor<1xf32>} : () -> !torch.vtensor<[1],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + %2 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[3,4,2,2],f32> + %3 = torch.operator "onnx.Shape"(%2) : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[4],si64> + %4 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = 2 : si64, torch.onnx.start = 1 : si64} : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Div"(%4, %5) : (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %7 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = 1 : si64, torch.onnx.start = 0 : si64} : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.start = 2 : si64} : (!torch.vtensor<[3,4,2,2],f32>) -> !torch.vtensor<[2],si64> + %9 = torch.operator "onnx.Concat"(%7, %5, %6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[5],si64> + %10 = torch.operator "onnx.Reshape"(%2, %9) : (!torch.vtensor<[3,4,2,2],f32>, !torch.vtensor<[5],si64>) -> !torch.vtensor<[?,?,?,?,?],f32> + %11 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [0 : si64, 0 : si64, -1 : si64]} : () -> !torch.vtensor<[3],si64> + %12 = torch.operator "onnx.Reshape"(%10, %11) : (!torch.vtensor<[?,?,?,?,?],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[?,?,?],f32> + %13 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %14 = torch.operator "onnx.ReduceMean"(%12, %13) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?,?,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> + %16 = torch.operator "onnx.ReduceMean"(%15, %13) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?,?,1],f32> + %17 = torch.operator "onnx.Mul"(%14, %14) : (!torch.vtensor<[?,?,1],f32>, !torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,1],f32> + %18 = torch.operator "onnx.Sub"(%16, %17) : (!torch.vtensor<[?,?,1],f32>, !torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,1],f32> + %19 = torch.operator "onnx.Add"(%18, %1) : (!torch.vtensor<[?,?,1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[?,?,1],f32> + %20 = torch.operator "onnx.Sqrt"(%19) : (!torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,1],f32> + %21 = torch.operator "onnx.Sub"(%12, %14) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,?],f32> + %22 = torch.operator "onnx.Div"(%21, %20) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,1],f32>) -> !torch.vtensor<[?,?,?],f32> + %23 = torch.operator "onnx.Reshape"(%22, %3) : (!torch.vtensor<[?,?,?],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[?,?,?,?],f32> + %24 = torch.operator "onnx.Reshape"(%23, %11) : (!torch.vtensor<[?,?,?,?],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[?,?,?],f32> + %25 = torch.operator "onnx.Cast"(%24) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> + %26 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [1 : si64, -1 : si64, 1 : si64]} : () -> !torch.vtensor<[3],si64> + %27 = torch.operator "onnx.Cast"(%arg1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[4],f32> + %28 = torch.operator "onnx.Cast"(%arg2) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[4],f32> + %29 = torch.operator "onnx.Reshape"(%27, %26) : (!torch.vtensor<[4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[1,4,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %26) : (!torch.vtensor<[4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[1,4,1],f32> + %31 = torch.operator "onnx.Mul"(%29, %25) : (!torch.vtensor<[1,4,1],f32>, !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,4,?],f32> + %32 = torch.operator "onnx.Add"(%31, %30) : (!torch.vtensor<[?,4,?],f32>, !torch.vtensor<[1,4,1],f32>) -> !torch.vtensor<[?,4,?],f32> + %33 = torch.operator "onnx.Reshape"(%32, %3) : (!torch.vtensor<[?,4,?],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[3,4,2,2],f32> return %33 : !torch.vtensor<[3,4,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gru_batchwise/model.mlir b/iree_tests/onnx/node/generated/test_gru_batchwise/model.mlir index 6ba24c8ca..16c483275 100644 --- a/iree_tests/onnx/node/generated/test_gru_batchwise/model.mlir +++ b/iree_tests/onnx/node/generated/test_gru_batchwise/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_gru_batchwise(%arg0: !torch.vtensor<[3,1,2],f32>, %arg1: !torch.vtensor<[1,18,2],f32>, %arg2: !torch.vtensor<[1,18,6],f32>) -> (!torch.vtensor<[3,1,1,6],f32>, !torch.vtensor<[3,1,6],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.GRU"(%arg0, %arg1, %arg2) {torch.onnx.hidden_size = 6 : si64, torch.onnx.layout = 1 : si64} : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1,18,2],f32>, !torch.vtensor<[1,18,6],f32>) -> (!torch.vtensor<[3,1,1,6],f32>, !torch.vtensor<[3,1,6],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.GRU"(%arg0, %arg1, %arg2) {torch.onnx.hidden_size = 6 : si64, torch.onnx.layout = 1 : si64} : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1,18,2],f32>, !torch.vtensor<[1,18,6],f32>) -> (!torch.vtensor<[3,1,1,6],f32>, !torch.vtensor<[3,1,6],f32>) return %0#0, %0#1 : !torch.vtensor<[3,1,1,6],f32>, !torch.vtensor<[3,1,6],f32> } } diff --git a/iree_tests/onnx/node/generated/test_gru_defaults/input_0.npy b/iree_tests/onnx/node/generated/test_gru_defaults/input_0.npy new file mode 100644 index 000000000..05b4233c9 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_gru_defaults/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_gru_defaults/input_1.npy b/iree_tests/onnx/node/generated/test_gru_defaults/input_1.npy new file mode 100644 index 000000000..1dda54d91 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_gru_defaults/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_gru_defaults/input_2.npy b/iree_tests/onnx/node/generated/test_gru_defaults/input_2.npy new file mode 100644 index 000000000..9ac9bd6e4 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_gru_defaults/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_gru_defaults/model.mlir b/iree_tests/onnx/node/generated/test_gru_defaults/model.mlir new file mode 100644 index 000000000..8f58f7305 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_gru_defaults/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_gru_defaults(%arg0: !torch.vtensor<[1,3,2],f32>, %arg1: !torch.vtensor<[1,15,2],f32>, %arg2: !torch.vtensor<[1,15,5],f32>) -> !torch.vtensor<[1,3,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.GRU"(%arg0, %arg1, %arg2) {torch.onnx.hidden_size = 5 : si64} : (!torch.vtensor<[1,3,2],f32>, !torch.vtensor<[1,15,2],f32>, !torch.vtensor<[1,15,5],f32>) -> (!torch.none, !torch.vtensor<[1,3,5],f32>) + return %0#1 : !torch.vtensor<[1,3,5],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_gru_defaults/output_0.npy b/iree_tests/onnx/node/generated/test_gru_defaults/output_0.npy new file mode 100644 index 000000000..4cb4438a4 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_gru_defaults/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_gru_defaults/test_data_flags.txt b/iree_tests/onnx/node/generated/test_gru_defaults/test_data_flags.txt new file mode 100644 index 000000000..cb3b7ab77 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_gru_defaults/test_data_flags.txt @@ -0,0 +1,4 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_gru_seq_length/input_0.npy b/iree_tests/onnx/node/generated/test_gru_seq_length/input_0.npy new file mode 100644 index 000000000..1be3eac92 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_gru_seq_length/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_gru_seq_length/input_1.npy b/iree_tests/onnx/node/generated/test_gru_seq_length/input_1.npy new file mode 100644 index 000000000..30d1d62a8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_gru_seq_length/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_gru_seq_length/input_2.npy b/iree_tests/onnx/node/generated/test_gru_seq_length/input_2.npy new file mode 100644 index 000000000..34edfb6a7 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_gru_seq_length/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_gru_seq_length/input_3.npy b/iree_tests/onnx/node/generated/test_gru_seq_length/input_3.npy new file mode 100644 index 000000000..bd1f5f151 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_gru_seq_length/input_3.npy differ diff --git a/iree_tests/onnx/node/generated/test_gru_seq_length/model.mlir b/iree_tests/onnx/node/generated/test_gru_seq_length/model.mlir new file mode 100644 index 000000000..ba1317df4 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_gru_seq_length/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_gru_seq_length(%arg0: !torch.vtensor<[2,3,3],f32>, %arg1: !torch.vtensor<[1,15,3],f32>, %arg2: !torch.vtensor<[1,15,5],f32>, %arg3: !torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,3,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.GRU"(%arg0, %arg1, %arg2, %arg3) {torch.onnx.hidden_size = 5 : si64} : (!torch.vtensor<[2,3,3],f32>, !torch.vtensor<[1,15,3],f32>, !torch.vtensor<[1,15,5],f32>, !torch.vtensor<[1,30],f32>) -> (!torch.none, !torch.vtensor<[1,3,5],f32>) + return %0#1 : !torch.vtensor<[1,3,5],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_gru_seq_length/output_0.npy b/iree_tests/onnx/node/generated/test_gru_seq_length/output_0.npy new file mode 100644 index 000000000..837993be0 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_gru_seq_length/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_gru_seq_length/test_data_flags.txt b/iree_tests/onnx/node/generated/test_gru_seq_length/test_data_flags.txt new file mode 100644 index 000000000..fad7bbb82 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_gru_seq_length/test_data_flags.txt @@ -0,0 +1,5 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--input=@input_3.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_gru_with_initial_bias/input_0.npy b/iree_tests/onnx/node/generated/test_gru_with_initial_bias/input_0.npy new file mode 100644 index 000000000..b91e0ac1b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_gru_with_initial_bias/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_gru_with_initial_bias/input_1.npy b/iree_tests/onnx/node/generated/test_gru_with_initial_bias/input_1.npy new file mode 100644 index 000000000..7d9fc1ab9 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_gru_with_initial_bias/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_gru_with_initial_bias/input_2.npy b/iree_tests/onnx/node/generated/test_gru_with_initial_bias/input_2.npy new file mode 100644 index 000000000..7d9fc1ab9 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_gru_with_initial_bias/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_gru_with_initial_bias/input_3.npy b/iree_tests/onnx/node/generated/test_gru_with_initial_bias/input_3.npy new file mode 100644 index 000000000..805451eed Binary files /dev/null and b/iree_tests/onnx/node/generated/test_gru_with_initial_bias/input_3.npy differ diff --git a/iree_tests/onnx/node/generated/test_gru_with_initial_bias/model.mlir b/iree_tests/onnx/node/generated/test_gru_with_initial_bias/model.mlir new file mode 100644 index 000000000..7d67c4b46 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_gru_with_initial_bias/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_gru_with_initial_bias(%arg0: !torch.vtensor<[1,3,3],f32>, %arg1: !torch.vtensor<[1,9,3],f32>, %arg2: !torch.vtensor<[1,9,3],f32>, %arg3: !torch.vtensor<[1,18],f32>) -> !torch.vtensor<[1,3,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.GRU"(%arg0, %arg1, %arg2, %arg3) {torch.onnx.hidden_size = 3 : si64} : (!torch.vtensor<[1,3,3],f32>, !torch.vtensor<[1,9,3],f32>, !torch.vtensor<[1,9,3],f32>, !torch.vtensor<[1,18],f32>) -> (!torch.none, !torch.vtensor<[1,3,3],f32>) + return %0#1 : !torch.vtensor<[1,3,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_gru_with_initial_bias/output_0.npy b/iree_tests/onnx/node/generated/test_gru_with_initial_bias/output_0.npy new file mode 100644 index 000000000..3f279fa60 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_gru_with_initial_bias/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_gru_with_initial_bias/test_data_flags.txt b/iree_tests/onnx/node/generated/test_gru_with_initial_bias/test_data_flags.txt new file mode 100644 index 000000000..fad7bbb82 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_gru_with_initial_bias/test_data_flags.txt @@ -0,0 +1,5 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--input=@input_3.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_hammingwindow/model.mlir b/iree_tests/onnx/node/generated/test_hammingwindow/model.mlir index 57b8f0bef..d05e47b9b 100644 --- a/iree_tests/onnx/node/generated/test_hammingwindow/model.mlir +++ b/iree_tests/onnx/node/generated/test_hammingwindow/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_hammingwindow(%arg0: !torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.HammingWindow"(%arg0) : (!torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.HammingWindow"(%arg0) : (!torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> return %0 : !torch.vtensor<[10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hammingwindow_expanded/model.mlir b/iree_tests/onnx/node/generated/test_hammingwindow_expanded/model.mlir index be5421df0..6f2261887 100644 --- a/iree_tests/onnx/node/generated/test_hammingwindow_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_hammingwindow_expanded/model.mlir @@ -1,31 +1,32 @@ module { func.func @test_hammingwindow_expanded(%arg0: !torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0.543478251> : tensor) : !torch.vtensor<[],f32> - %1 = torch.vtensor.literal(dense<0.456521749> : tensor) : !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.vtensor.literal(dense<2.000000e+00> : tensor) : !torch.vtensor<[],f32> - %6 = torch.vtensor.literal(dense<6.28318548> : tensor) : !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[],f32> - %8 = torch.operator "onnx.Sub"(%7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %9 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 1 : si64} : () -> !torch.vtensor<[],si64> - %10 = torch.operator "onnx.Cast"(%9) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> - %11 = torch.operator "onnx.Sub"(%4, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %12 = torch.operator "onnx.Mul"(%7, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %13 = torch.operator "onnx.Mul"(%8, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %14 = torch.operator "onnx.Add"(%12, %13) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %15 = torch.operator "onnx.Div"(%6, %14) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %16 = torch.operator "onnx.Range"(%3, %7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %17 = torch.operator "onnx.Mul"(%16, %15) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %18 = torch.operator "onnx.Mul"(%17, %5) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %19 = torch.operator "onnx.Cos"(%18) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %20 = torch.operator "onnx.Mul"(%2, %19) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %21 = torch.operator "onnx.Cos"(%17) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %22 = torch.operator "onnx.Mul"(%1, %21) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %23 = torch.operator "onnx.Sub"(%0, %22) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %24 = torch.operator "onnx.Add"(%23, %20) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %25 = torch.operator "onnx.Cast"(%24) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.543478251> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.456521749> : tensor} : () -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<6.28318548> : tensor} : () -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.Sub"(%7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %9 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 1 : si64} : () -> !torch.vtensor<[],si64> + %10 = torch.operator "onnx.Cast"(%9) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.Sub"(%4, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %12 = torch.operator "onnx.Mul"(%7, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %13 = torch.operator "onnx.Mul"(%8, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %14 = torch.operator "onnx.Add"(%12, %13) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %15 = torch.operator "onnx.Div"(%6, %14) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %16 = torch.operator "onnx.Range"(%3, %7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %17 = torch.operator "onnx.Mul"(%16, %15) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %18 = torch.operator "onnx.Mul"(%17, %5) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %19 = torch.operator "onnx.Cos"(%18) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %20 = torch.operator "onnx.Mul"(%2, %19) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %21 = torch.operator "onnx.Cos"(%17) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %22 = torch.operator "onnx.Mul"(%1, %21) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %23 = torch.operator "onnx.Sub"(%0, %22) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %24 = torch.operator "onnx.Add"(%23, %20) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %25 = torch.operator "onnx.Cast"(%24) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[10],f32> return %25 : !torch.vtensor<[10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hammingwindow_symmetric/model.mlir b/iree_tests/onnx/node/generated/test_hammingwindow_symmetric/model.mlir index 40f69be70..1aa2a3dd4 100644 --- a/iree_tests/onnx/node/generated/test_hammingwindow_symmetric/model.mlir +++ b/iree_tests/onnx/node/generated/test_hammingwindow_symmetric/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_hammingwindow_symmetric(%arg0: !torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.HammingWindow"(%arg0) {torch.onnx.periodic = 0 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.HammingWindow"(%arg0) {torch.onnx.periodic = 0 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> return %0 : !torch.vtensor<[10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hammingwindow_symmetric_expanded/model.mlir b/iree_tests/onnx/node/generated/test_hammingwindow_symmetric_expanded/model.mlir index 29c35a376..7f1f6c409 100644 --- a/iree_tests/onnx/node/generated/test_hammingwindow_symmetric_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_hammingwindow_symmetric_expanded/model.mlir @@ -1,31 +1,32 @@ module { func.func @test_hammingwindow_symmetric_expanded(%arg0: !torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0.543478251> : tensor) : !torch.vtensor<[],f32> - %1 = torch.vtensor.literal(dense<0.456521749> : tensor) : !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.vtensor.literal(dense<2.000000e+00> : tensor) : !torch.vtensor<[],f32> - %6 = torch.vtensor.literal(dense<6.28318548> : tensor) : !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[],f32> - %8 = torch.operator "onnx.Sub"(%7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %9 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 0 : si64} : () -> !torch.vtensor<[],si64> - %10 = torch.operator "onnx.Cast"(%9) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> - %11 = torch.operator "onnx.Sub"(%4, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %12 = torch.operator "onnx.Mul"(%7, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %13 = torch.operator "onnx.Mul"(%8, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %14 = torch.operator "onnx.Add"(%12, %13) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %15 = torch.operator "onnx.Div"(%6, %14) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %16 = torch.operator "onnx.Range"(%3, %7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %17 = torch.operator "onnx.Mul"(%16, %15) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %18 = torch.operator "onnx.Mul"(%17, %5) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %19 = torch.operator "onnx.Cos"(%18) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %20 = torch.operator "onnx.Mul"(%2, %19) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %21 = torch.operator "onnx.Cos"(%17) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %22 = torch.operator "onnx.Mul"(%1, %21) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %23 = torch.operator "onnx.Sub"(%0, %22) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %24 = torch.operator "onnx.Add"(%23, %20) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %25 = torch.operator "onnx.Cast"(%24) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.543478251> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.456521749> : tensor} : () -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<6.28318548> : tensor} : () -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.Sub"(%7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %9 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 0 : si64} : () -> !torch.vtensor<[],si64> + %10 = torch.operator "onnx.Cast"(%9) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.Sub"(%4, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %12 = torch.operator "onnx.Mul"(%7, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %13 = torch.operator "onnx.Mul"(%8, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %14 = torch.operator "onnx.Add"(%12, %13) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %15 = torch.operator "onnx.Div"(%6, %14) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %16 = torch.operator "onnx.Range"(%3, %7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %17 = torch.operator "onnx.Mul"(%16, %15) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %18 = torch.operator "onnx.Mul"(%17, %5) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %19 = torch.operator "onnx.Cos"(%18) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %20 = torch.operator "onnx.Mul"(%2, %19) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %21 = torch.operator "onnx.Cos"(%17) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %22 = torch.operator "onnx.Mul"(%1, %21) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %23 = torch.operator "onnx.Sub"(%0, %22) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %24 = torch.operator "onnx.Add"(%23, %20) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %25 = torch.operator "onnx.Cast"(%24) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[10],f32> return %25 : !torch.vtensor<[10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hannwindow/model.mlir b/iree_tests/onnx/node/generated/test_hannwindow/model.mlir index 53920e96f..240a5ae85 100644 --- a/iree_tests/onnx/node/generated/test_hannwindow/model.mlir +++ b/iree_tests/onnx/node/generated/test_hannwindow/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_hannwindow(%arg0: !torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.HannWindow"(%arg0) : (!torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.HannWindow"(%arg0) : (!torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> return %0 : !torch.vtensor<[10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hannwindow_expanded/model.mlir b/iree_tests/onnx/node/generated/test_hannwindow_expanded/model.mlir index f2268bb67..e4b89a143 100644 --- a/iree_tests/onnx/node/generated/test_hannwindow_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_hannwindow_expanded/model.mlir @@ -1,31 +1,32 @@ module { func.func @test_hannwindow_expanded(%arg0: !torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<5.000000e-01> : tensor) : !torch.vtensor<[],f32> - %1 = torch.vtensor.literal(dense<5.000000e-01> : tensor) : !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.vtensor.literal(dense<2.000000e+00> : tensor) : !torch.vtensor<[],f32> - %6 = torch.vtensor.literal(dense<6.28318548> : tensor) : !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[],f32> - %8 = torch.operator "onnx.Sub"(%7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %9 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 1 : si64} : () -> !torch.vtensor<[],si64> - %10 = torch.operator "onnx.Cast"(%9) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> - %11 = torch.operator "onnx.Sub"(%4, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %12 = torch.operator "onnx.Mul"(%7, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %13 = torch.operator "onnx.Mul"(%8, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %14 = torch.operator "onnx.Add"(%12, %13) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %15 = torch.operator "onnx.Div"(%6, %14) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %16 = torch.operator "onnx.Range"(%3, %7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %17 = torch.operator "onnx.Mul"(%16, %15) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %18 = torch.operator "onnx.Mul"(%17, %5) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %19 = torch.operator "onnx.Cos"(%18) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %20 = torch.operator "onnx.Mul"(%2, %19) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %21 = torch.operator "onnx.Cos"(%17) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %22 = torch.operator "onnx.Mul"(%1, %21) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %23 = torch.operator "onnx.Sub"(%0, %22) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %24 = torch.operator "onnx.Add"(%23, %20) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %25 = torch.operator "onnx.Cast"(%24) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<5.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<5.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<6.28318548> : tensor} : () -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.Sub"(%7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %9 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 1 : si64} : () -> !torch.vtensor<[],si64> + %10 = torch.operator "onnx.Cast"(%9) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.Sub"(%4, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %12 = torch.operator "onnx.Mul"(%7, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %13 = torch.operator "onnx.Mul"(%8, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %14 = torch.operator "onnx.Add"(%12, %13) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %15 = torch.operator "onnx.Div"(%6, %14) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %16 = torch.operator "onnx.Range"(%3, %7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %17 = torch.operator "onnx.Mul"(%16, %15) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %18 = torch.operator "onnx.Mul"(%17, %5) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %19 = torch.operator "onnx.Cos"(%18) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %20 = torch.operator "onnx.Mul"(%2, %19) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %21 = torch.operator "onnx.Cos"(%17) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %22 = torch.operator "onnx.Mul"(%1, %21) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %23 = torch.operator "onnx.Sub"(%0, %22) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %24 = torch.operator "onnx.Add"(%23, %20) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %25 = torch.operator "onnx.Cast"(%24) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[10],f32> return %25 : !torch.vtensor<[10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hannwindow_symmetric/model.mlir b/iree_tests/onnx/node/generated/test_hannwindow_symmetric/model.mlir index b2c9be103..150ec8b00 100644 --- a/iree_tests/onnx/node/generated/test_hannwindow_symmetric/model.mlir +++ b/iree_tests/onnx/node/generated/test_hannwindow_symmetric/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_hannwindow_symmetric(%arg0: !torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.HannWindow"(%arg0) {torch.onnx.periodic = 0 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.HannWindow"(%arg0) {torch.onnx.periodic = 0 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> return %0 : !torch.vtensor<[10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hannwindow_symmetric_expanded/model.mlir b/iree_tests/onnx/node/generated/test_hannwindow_symmetric_expanded/model.mlir index 5aa806fe1..505378072 100644 --- a/iree_tests/onnx/node/generated/test_hannwindow_symmetric_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_hannwindow_symmetric_expanded/model.mlir @@ -1,31 +1,32 @@ module { func.func @test_hannwindow_symmetric_expanded(%arg0: !torch.vtensor<[],si32>) -> !torch.vtensor<[10],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<5.000000e-01> : tensor) : !torch.vtensor<[],f32> - %1 = torch.vtensor.literal(dense<5.000000e-01> : tensor) : !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.vtensor.literal(dense<2.000000e+00> : tensor) : !torch.vtensor<[],f32> - %6 = torch.vtensor.literal(dense<6.28318548> : tensor) : !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[],f32> - %8 = torch.operator "onnx.Sub"(%7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %9 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 0 : si64} : () -> !torch.vtensor<[],si64> - %10 = torch.operator "onnx.Cast"(%9) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> - %11 = torch.operator "onnx.Sub"(%4, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %12 = torch.operator "onnx.Mul"(%7, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %13 = torch.operator "onnx.Mul"(%8, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %14 = torch.operator "onnx.Add"(%12, %13) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %15 = torch.operator "onnx.Div"(%6, %14) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %16 = torch.operator "onnx.Range"(%3, %7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %17 = torch.operator "onnx.Mul"(%16, %15) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %18 = torch.operator "onnx.Mul"(%17, %5) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> - %19 = torch.operator "onnx.Cos"(%18) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %20 = torch.operator "onnx.Mul"(%2, %19) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %21 = torch.operator "onnx.Cos"(%17) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %22 = torch.operator "onnx.Mul"(%1, %21) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %23 = torch.operator "onnx.Sub"(%0, %22) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %24 = torch.operator "onnx.Add"(%23, %20) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> - %25 = torch.operator "onnx.Cast"(%24) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<5.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<5.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<6.28318548> : tensor} : () -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.Sub"(%7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %9 = torch.operator "onnx.Constant"() {torch.onnx.value_int = 0 : si64} : () -> !torch.vtensor<[],si64> + %10 = torch.operator "onnx.Cast"(%9) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si64>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.Sub"(%4, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %12 = torch.operator "onnx.Mul"(%7, %10) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %13 = torch.operator "onnx.Mul"(%8, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %14 = torch.operator "onnx.Add"(%12, %13) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %15 = torch.operator "onnx.Div"(%6, %14) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %16 = torch.operator "onnx.Range"(%3, %7, %4) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %17 = torch.operator "onnx.Mul"(%16, %15) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %18 = torch.operator "onnx.Mul"(%17, %5) : (!torch.vtensor<[?],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[?],f32> + %19 = torch.operator "onnx.Cos"(%18) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %20 = torch.operator "onnx.Mul"(%2, %19) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %21 = torch.operator "onnx.Cos"(%17) : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %22 = torch.operator "onnx.Mul"(%1, %21) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %23 = torch.operator "onnx.Sub"(%0, %22) : (!torch.vtensor<[],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %24 = torch.operator "onnx.Add"(%23, %20) : (!torch.vtensor<[?],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[?],f32> + %25 = torch.operator "onnx.Cast"(%24) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[?],f32>) -> !torch.vtensor<[10],f32> return %25 : !torch.vtensor<[10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hardmax_axis_0/model.mlir b/iree_tests/onnx/node/generated/test_hardmax_axis_0/model.mlir index 1e0acacb3..6661c6414 100644 --- a/iree_tests/onnx/node/generated/test_hardmax_axis_0/model.mlir +++ b/iree_tests/onnx/node/generated/test_hardmax_axis_0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_hardmax_axis_0(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Hardmax"(%arg0) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Hardmax"(%arg0) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hardmax_axis_1/model.mlir b/iree_tests/onnx/node/generated/test_hardmax_axis_1/model.mlir index 2555b688c..04da38a44 100644 --- a/iree_tests/onnx/node/generated/test_hardmax_axis_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_hardmax_axis_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_hardmax_axis_1(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Hardmax"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Hardmax"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hardmax_axis_2/model.mlir b/iree_tests/onnx/node/generated/test_hardmax_axis_2/model.mlir index 51539933b..78f789043 100644 --- a/iree_tests/onnx/node/generated/test_hardmax_axis_2/model.mlir +++ b/iree_tests/onnx/node/generated/test_hardmax_axis_2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_hardmax_axis_2(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Hardmax"(%arg0) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Hardmax"(%arg0) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hardmax_default_axis/model.mlir b/iree_tests/onnx/node/generated/test_hardmax_default_axis/model.mlir index 1c04ba842..3e34df19d 100644 --- a/iree_tests/onnx/node/generated/test_hardmax_default_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_hardmax_default_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_hardmax_default_axis(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Hardmax"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Hardmax"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hardmax_example/model.mlir b/iree_tests/onnx/node/generated/test_hardmax_example/model.mlir index 7ef8d8d2d..294fc830c 100644 --- a/iree_tests/onnx/node/generated/test_hardmax_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_hardmax_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_hardmax_example(%arg0: !torch.vtensor<[4,4],f32>) -> !torch.vtensor<[4,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Hardmax"(%arg0) : (!torch.vtensor<[4,4],f32>) -> !torch.vtensor<[4,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Hardmax"(%arg0) : (!torch.vtensor<[4,4],f32>) -> !torch.vtensor<[4,4],f32> return %0 : !torch.vtensor<[4,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hardmax_negative_axis/model.mlir b/iree_tests/onnx/node/generated/test_hardmax_negative_axis/model.mlir index 46c3e78b8..620076947 100644 --- a/iree_tests/onnx/node/generated/test_hardmax_negative_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_hardmax_negative_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_hardmax_negative_axis(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Hardmax"(%arg0) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Hardmax"(%arg0) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hardmax_one_hot/model.mlir b/iree_tests/onnx/node/generated/test_hardmax_one_hot/model.mlir index 2d84d3a61..bd0e2cfa1 100644 --- a/iree_tests/onnx/node/generated/test_hardmax_one_hot/model.mlir +++ b/iree_tests/onnx/node/generated/test_hardmax_one_hot/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_hardmax_one_hot(%arg0: !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[1,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Hardmax"(%arg0) : (!torch.vtensor<[1,4],f32>) -> !torch.vtensor<[1,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Hardmax"(%arg0) : (!torch.vtensor<[1,4],f32>) -> !torch.vtensor<[1,4],f32> return %0 : !torch.vtensor<[1,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hardsigmoid/model.mlir b/iree_tests/onnx/node/generated/test_hardsigmoid/model.mlir index 2a2315162..4cfce7a80 100644 --- a/iree_tests/onnx/node/generated/test_hardsigmoid/model.mlir +++ b/iree_tests/onnx/node/generated/test_hardsigmoid/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_hardsigmoid(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 6 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.HardSigmoid"(%arg0) {torch.onnx.alpha = 5.000000e-01 : f32, torch.onnx.beta = 6.000000e-01 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.HardSigmoid"(%arg0) {torch.onnx.alpha = 5.000000e-01 : f32, torch.onnx.beta = 6.000000e-01 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hardsigmoid_default/model.mlir b/iree_tests/onnx/node/generated/test_hardsigmoid_default/model.mlir index 240056de1..0a73ebd99 100644 --- a/iree_tests/onnx/node/generated/test_hardsigmoid_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_hardsigmoid_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_hardsigmoid_default(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 6 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.HardSigmoid"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.HardSigmoid"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hardsigmoid_default_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_hardsigmoid_default_expanded_ver18/model.mlir index 50025e51d..7be8f52cd 100644 --- a/iree_tests/onnx/node/generated/test_hardsigmoid_default_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_hardsigmoid_default_expanded_ver18/model.mlir @@ -1,17 +1,18 @@ module { func.func @test_hardsigmoid_default_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 2.000000e-01 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 5.000000e-01 : f32} : () -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %6 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %7 = torch.operator "onnx.CastLike"(%6, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %8 = torch.operator "onnx.Mul"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> - %9 = torch.operator "onnx.Add"(%8, %3) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> - %10 = torch.operator "onnx.Min"(%9, %7) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> - %11 = torch.operator "onnx.Max"(%10, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 2.000000e-01 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 5.000000e-01 : f32} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.CastLike"(%6, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.Mul"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %9 = torch.operator "onnx.Add"(%8, %3) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %10 = torch.operator "onnx.Min"(%9, %7) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %11 = torch.operator "onnx.Max"(%10, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> return %11 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hardsigmoid_example/model.mlir b/iree_tests/onnx/node/generated/test_hardsigmoid_example/model.mlir index f1ae6baa7..f76e41665 100644 --- a/iree_tests/onnx/node/generated/test_hardsigmoid_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_hardsigmoid_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_hardsigmoid_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 6 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.HardSigmoid"(%arg0) {torch.onnx.alpha = 5.000000e-01 : f32, torch.onnx.beta = 6.000000e-01 : f32} : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.HardSigmoid"(%arg0) {torch.onnx.alpha = 5.000000e-01 : f32, torch.onnx.beta = 6.000000e-01 : f32} : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hardsigmoid_example_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_hardsigmoid_example_expanded_ver18/model.mlir index 5ce296bff..41dab233d 100644 --- a/iree_tests/onnx/node/generated/test_hardsigmoid_example_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_hardsigmoid_example_expanded_ver18/model.mlir @@ -1,17 +1,18 @@ module { func.func @test_hardsigmoid_example_expanded_ver18(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 5.000000e-01 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 6.000000e-01 : f32} : () -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %6 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %7 = torch.operator "onnx.CastLike"(%6, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %8 = torch.operator "onnx.Mul"(%arg0, %1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> - %9 = torch.operator "onnx.Add"(%8, %3) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> - %10 = torch.operator "onnx.Min"(%9, %7) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> - %11 = torch.operator "onnx.Max"(%10, %5) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 5.000000e-01 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 6.000000e-01 : f32} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.CastLike"(%6, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.Mul"(%arg0, %1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> + %9 = torch.operator "onnx.Add"(%8, %3) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> + %10 = torch.operator "onnx.Min"(%9, %7) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> + %11 = torch.operator "onnx.Max"(%10, %5) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> return %11 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hardsigmoid_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_hardsigmoid_expanded_ver18/model.mlir index 177e8c22a..c5bb1c7c1 100644 --- a/iree_tests/onnx/node/generated/test_hardsigmoid_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_hardsigmoid_expanded_ver18/model.mlir @@ -1,17 +1,18 @@ module { func.func @test_hardsigmoid_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 5.000000e-01 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 6.000000e-01 : f32} : () -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %6 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %7 = torch.operator "onnx.CastLike"(%6, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %8 = torch.operator "onnx.Mul"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> - %9 = torch.operator "onnx.Add"(%8, %3) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> - %10 = torch.operator "onnx.Min"(%9, %7) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> - %11 = torch.operator "onnx.Max"(%10, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 5.000000e-01 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 6.000000e-01 : f32} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.CastLike"(%6, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %8 = torch.operator "onnx.Mul"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %9 = torch.operator "onnx.Add"(%8, %3) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %10 = torch.operator "onnx.Min"(%9, %7) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %11 = torch.operator "onnx.Max"(%10, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> return %11 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hardswish/model.mlir b/iree_tests/onnx/node/generated/test_hardswish/model.mlir index a82db9b3c..b0e9623f9 100644 --- a/iree_tests/onnx/node/generated/test_hardswish/model.mlir +++ b/iree_tests/onnx/node/generated/test_hardswish/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_hardswish(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.HardSwish"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.HardSwish"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_hardswish_expanded/model.mlir b/iree_tests/onnx/node/generated/test_hardswish_expanded/model.mlir index 347a53e8f..ec7bcece2 100644 --- a/iree_tests/onnx/node/generated/test_hardswish_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_hardswish_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_hardswish_expanded(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.HardSigmoid"(%arg0) {torch.onnx.alpha = 0.166666672 : f32, torch.onnx.beta = 5.000000e-01 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %1 = torch.operator "onnx.Mul"(%arg0, %0) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.HardSigmoid"(%arg0) {torch.onnx.alpha = 0.166666672 : f32, torch.onnx.beta = 5.000000e-01 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %1 = torch.operator "onnx.Mul"(%arg0, %0) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %1 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_identity/model.mlir b/iree_tests/onnx/node/generated/test_identity/model.mlir index f218c03e7..9e8a4bde2 100644 --- a/iree_tests/onnx/node/generated/test_identity/model.mlir +++ b/iree_tests/onnx/node/generated/test_identity/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_identity(%arg0: !torch.vtensor<[1,1,2,2],f32>) -> !torch.vtensor<[1,1,2,2],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Identity"(%arg0) : (!torch.vtensor<[1,1,2,2],f32>) -> !torch.vtensor<[1,1,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Identity"(%arg0) : (!torch.vtensor<[1,1,2,2],f32>) -> !torch.vtensor<[1,1,2,2],f32> return %0 : !torch.vtensor<[1,1,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_if/input_0.npy b/iree_tests/onnx/node/generated/test_if/input_0.npy new file mode 100644 index 000000000..0917fd2fe Binary files /dev/null and b/iree_tests/onnx/node/generated/test_if/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_if/model.mlir b/iree_tests/onnx/node/generated/test_if/model.mlir new file mode 100644 index 000000000..8a68479cc --- /dev/null +++ b/iree_tests/onnx/node/generated/test_if/model.mlir @@ -0,0 +1,23 @@ +module { + func.func @test_if(%arg0: !torch.vtensor<[],i1>) -> !torch.vtensor<[5],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.If"(%arg0) : (!torch.vtensor<[],i1>) -> !torch.vtensor<[5],f32> { + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense_resource<_> : tensor<5xf32>} : () -> !torch.vtensor<[5],f32> + torch.operator_terminator %1 : !torch.vtensor<[5],f32> + }, { + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense_resource<__1> : tensor<5xf32>} : () -> !torch.vtensor<[5],f32> + torch.operator_terminator %1 : !torch.vtensor<[5],f32> + } + return %0 : !torch.vtensor<[5],f32> + } +} + +{-# + dialect_resources: { + builtin: { + _: "0x080000000000A0400000804000004040000000400000803F", + __1: "0x080000000000803F0000004000004040000080400000A040" + } + } +#-} + diff --git a/iree_tests/onnx/node/generated/test_if/output_0.npy b/iree_tests/onnx/node/generated/test_if/output_0.npy new file mode 100644 index 000000000..cb66fd5a4 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_if/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_if/test_data_flags.txt b/iree_tests/onnx/node/generated/test_if/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_if/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_image_decoder_decode_bmp_rgb/model.mlir b/iree_tests/onnx/node/generated/test_image_decoder_decode_bmp_rgb/model.mlir index 08f2c0848..021869932 100644 --- a/iree_tests/onnx/node/generated/test_image_decoder_decode_bmp_rgb/model.mlir +++ b/iree_tests/onnx/node/generated/test_image_decoder_decode_bmp_rgb/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_image_decoder_decode_bmp_rgb(%arg0: !torch.vtensor<[3126],ui8>) -> !torch.vtensor<[32,32,3],ui8> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "RGB"} : (!torch.vtensor<[3126],ui8>) -> !torch.vtensor<[32,32,3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "RGB"} : (!torch.vtensor<[3126],ui8>) -> !torch.vtensor<[32,32,3],ui8> return %0 : !torch.vtensor<[32,32,3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_image_decoder_decode_jpeg2k_rgb/model.mlir b/iree_tests/onnx/node/generated/test_image_decoder_decode_jpeg2k_rgb/model.mlir index 0c49359a2..8343dbb3d 100644 --- a/iree_tests/onnx/node/generated/test_image_decoder_decode_jpeg2k_rgb/model.mlir +++ b/iree_tests/onnx/node/generated/test_image_decoder_decode_jpeg2k_rgb/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_image_decoder_decode_jpeg2k_rgb(%arg0: !torch.vtensor<[1887],ui8>) -> !torch.vtensor<[32,32,3],ui8> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "RGB"} : (!torch.vtensor<[1887],ui8>) -> !torch.vtensor<[32,32,3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "RGB"} : (!torch.vtensor<[1887],ui8>) -> !torch.vtensor<[32,32,3],ui8> return %0 : !torch.vtensor<[32,32,3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_image_decoder_decode_jpeg_bgr/model.mlir b/iree_tests/onnx/node/generated/test_image_decoder_decode_jpeg_bgr/model.mlir index c29ddd1e5..698568cf2 100644 --- a/iree_tests/onnx/node/generated/test_image_decoder_decode_jpeg_bgr/model.mlir +++ b/iree_tests/onnx/node/generated/test_image_decoder_decode_jpeg_bgr/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_image_decoder_decode_jpeg_bgr(%arg0: !torch.vtensor<[1058],ui8>) -> !torch.vtensor<[32,32,3],ui8> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "BGR"} : (!torch.vtensor<[1058],ui8>) -> !torch.vtensor<[32,32,3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "BGR"} : (!torch.vtensor<[1058],ui8>) -> !torch.vtensor<[32,32,3],ui8> return %0 : !torch.vtensor<[32,32,3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_image_decoder_decode_jpeg_grayscale/model.mlir b/iree_tests/onnx/node/generated/test_image_decoder_decode_jpeg_grayscale/model.mlir index 51579e047..4c11614f3 100644 --- a/iree_tests/onnx/node/generated/test_image_decoder_decode_jpeg_grayscale/model.mlir +++ b/iree_tests/onnx/node/generated/test_image_decoder_decode_jpeg_grayscale/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_image_decoder_decode_jpeg_grayscale(%arg0: !torch.vtensor<[1058],ui8>) -> !torch.vtensor<[32,32,1],ui8> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "Grayscale"} : (!torch.vtensor<[1058],ui8>) -> !torch.vtensor<[32,32,1],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "Grayscale"} : (!torch.vtensor<[1058],ui8>) -> !torch.vtensor<[32,32,1],ui8> return %0 : !torch.vtensor<[32,32,1],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_image_decoder_decode_jpeg_rgb/model.mlir b/iree_tests/onnx/node/generated/test_image_decoder_decode_jpeg_rgb/model.mlir index 1ea69a74c..b6d020365 100644 --- a/iree_tests/onnx/node/generated/test_image_decoder_decode_jpeg_rgb/model.mlir +++ b/iree_tests/onnx/node/generated/test_image_decoder_decode_jpeg_rgb/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_image_decoder_decode_jpeg_rgb(%arg0: !torch.vtensor<[1058],ui8>) -> !torch.vtensor<[32,32,3],ui8> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "RGB"} : (!torch.vtensor<[1058],ui8>) -> !torch.vtensor<[32,32,3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "RGB"} : (!torch.vtensor<[1058],ui8>) -> !torch.vtensor<[32,32,3],ui8> return %0 : !torch.vtensor<[32,32,3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_image_decoder_decode_png_rgb/model.mlir b/iree_tests/onnx/node/generated/test_image_decoder_decode_png_rgb/model.mlir index 609888e8a..9357f86e6 100644 --- a/iree_tests/onnx/node/generated/test_image_decoder_decode_png_rgb/model.mlir +++ b/iree_tests/onnx/node/generated/test_image_decoder_decode_png_rgb/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_image_decoder_decode_png_rgb(%arg0: !torch.vtensor<[312],ui8>) -> !torch.vtensor<[32,32,3],ui8> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "RGB"} : (!torch.vtensor<[312],ui8>) -> !torch.vtensor<[32,32,3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "RGB"} : (!torch.vtensor<[312],ui8>) -> !torch.vtensor<[32,32,3],ui8> return %0 : !torch.vtensor<[32,32,3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_image_decoder_decode_pnm_rgb/model.mlir b/iree_tests/onnx/node/generated/test_image_decoder_decode_pnm_rgb/model.mlir index f4eaf9adc..79cf12ac1 100644 --- a/iree_tests/onnx/node/generated/test_image_decoder_decode_pnm_rgb/model.mlir +++ b/iree_tests/onnx/node/generated/test_image_decoder_decode_pnm_rgb/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_image_decoder_decode_pnm_rgb(%arg0: !torch.vtensor<[3085],ui8>) -> !torch.vtensor<[32,32,3],ui8> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "RGB"} : (!torch.vtensor<[3085],ui8>) -> !torch.vtensor<[32,32,3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "RGB"} : (!torch.vtensor<[3085],ui8>) -> !torch.vtensor<[32,32,3],ui8> return %0 : !torch.vtensor<[32,32,3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_image_decoder_decode_tiff_rgb/model.mlir b/iree_tests/onnx/node/generated/test_image_decoder_decode_tiff_rgb/model.mlir index a2eff91bd..6a972991f 100644 --- a/iree_tests/onnx/node/generated/test_image_decoder_decode_tiff_rgb/model.mlir +++ b/iree_tests/onnx/node/generated/test_image_decoder_decode_tiff_rgb/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_image_decoder_decode_tiff_rgb(%arg0: !torch.vtensor<[3212],ui8>) -> !torch.vtensor<[32,32,3],ui8> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "RGB"} : (!torch.vtensor<[3212],ui8>) -> !torch.vtensor<[32,32,3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "RGB"} : (!torch.vtensor<[3212],ui8>) -> !torch.vtensor<[32,32,3],ui8> return %0 : !torch.vtensor<[32,32,3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_image_decoder_decode_webp_rgb/model.mlir b/iree_tests/onnx/node/generated/test_image_decoder_decode_webp_rgb/model.mlir index 2980ac24f..960cfe765 100644 --- a/iree_tests/onnx/node/generated/test_image_decoder_decode_webp_rgb/model.mlir +++ b/iree_tests/onnx/node/generated/test_image_decoder_decode_webp_rgb/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_image_decoder_decode_webp_rgb(%arg0: !torch.vtensor<[552],ui8>) -> !torch.vtensor<[32,32,3],ui8> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "RGB"} : (!torch.vtensor<[552],ui8>) -> !torch.vtensor<[32,32,3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.ImageDecoder"(%arg0) {torch.onnx.pixel_format = "RGB"} : (!torch.vtensor<[552],ui8>) -> !torch.vtensor<[32,32,3],ui8> return %0 : !torch.vtensor<[32,32,3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_instancenorm_epsilon/model.mlir b/iree_tests/onnx/node/generated/test_instancenorm_epsilon/model.mlir index c5a03a430..1828962c7 100644 --- a/iree_tests/onnx/node/generated/test_instancenorm_epsilon/model.mlir +++ b/iree_tests/onnx/node/generated/test_instancenorm_epsilon/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_instancenorm_epsilon(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[3],f32>, %arg2: !torch.vtensor<[3],f32>) -> !torch.vtensor<[2,3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 6 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.InstanceNormalization"(%arg0, %arg1, %arg2) {torch.onnx.epsilon = 0.00999999977 : f32} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[2,3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.InstanceNormalization"(%arg0, %arg1, %arg2) {torch.onnx.epsilon = 0.00999999977 : f32} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[2,3,4,5],f32> return %0 : !torch.vtensor<[2,3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_instancenorm_example/model.mlir b/iree_tests/onnx/node/generated/test_instancenorm_example/model.mlir index 28a3f6b91..ab1a6f7a6 100644 --- a/iree_tests/onnx/node/generated/test_instancenorm_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_instancenorm_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_instancenorm_example(%arg0: !torch.vtensor<[1,2,1,3],f32>, %arg1: !torch.vtensor<[2],f32>, %arg2: !torch.vtensor<[2],f32>) -> !torch.vtensor<[1,2,1,3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 6 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.InstanceNormalization"(%arg0, %arg1, %arg2) : (!torch.vtensor<[1,2,1,3],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) -> !torch.vtensor<[1,2,1,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.InstanceNormalization"(%arg0, %arg1, %arg2) : (!torch.vtensor<[1,2,1,3],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) -> !torch.vtensor<[1,2,1,3],f32> return %0 : !torch.vtensor<[1,2,1,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_isinf/model.mlir b/iree_tests/onnx/node/generated/test_isinf/model.mlir index 5bf10ba42..c9c579637 100644 --- a/iree_tests/onnx/node/generated/test_isinf/model.mlir +++ b/iree_tests/onnx/node/generated/test_isinf/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_isinf(%arg0: !torch.vtensor<[6],f32>) -> !torch.vtensor<[6],i1> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.IsInf"(%arg0) : (!torch.vtensor<[6],f32>) -> !torch.vtensor<[6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.IsInf"(%arg0) : (!torch.vtensor<[6],f32>) -> !torch.vtensor<[6],i1> return %0 : !torch.vtensor<[6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_isinf_float16/model.mlir b/iree_tests/onnx/node/generated/test_isinf_float16/model.mlir index 36da6f73b..5a3f91c5b 100644 --- a/iree_tests/onnx/node/generated/test_isinf_float16/model.mlir +++ b/iree_tests/onnx/node/generated/test_isinf_float16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_isinf_float16(%arg0: !torch.vtensor<[6],f16>) -> !torch.vtensor<[6],i1> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.IsInf"(%arg0) : (!torch.vtensor<[6],f16>) -> !torch.vtensor<[6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.IsInf"(%arg0) : (!torch.vtensor<[6],f16>) -> !torch.vtensor<[6],i1> return %0 : !torch.vtensor<[6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_isinf_negative/model.mlir b/iree_tests/onnx/node/generated/test_isinf_negative/model.mlir index 95b4ac498..4c9507a59 100644 --- a/iree_tests/onnx/node/generated/test_isinf_negative/model.mlir +++ b/iree_tests/onnx/node/generated/test_isinf_negative/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_isinf_negative(%arg0: !torch.vtensor<[6],f32>) -> !torch.vtensor<[6],i1> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.IsInf"(%arg0) {torch.onnx.detect_positive = 0 : si64} : (!torch.vtensor<[6],f32>) -> !torch.vtensor<[6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.IsInf"(%arg0) {torch.onnx.detect_positive = 0 : si64} : (!torch.vtensor<[6],f32>) -> !torch.vtensor<[6],i1> return %0 : !torch.vtensor<[6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_isinf_positive/model.mlir b/iree_tests/onnx/node/generated/test_isinf_positive/model.mlir index 403ad5755..52fe93bc2 100644 --- a/iree_tests/onnx/node/generated/test_isinf_positive/model.mlir +++ b/iree_tests/onnx/node/generated/test_isinf_positive/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_isinf_positive(%arg0: !torch.vtensor<[6],f32>) -> !torch.vtensor<[6],i1> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.IsInf"(%arg0) {torch.onnx.detect_negative = 0 : si64} : (!torch.vtensor<[6],f32>) -> !torch.vtensor<[6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.IsInf"(%arg0) {torch.onnx.detect_negative = 0 : si64} : (!torch.vtensor<[6],f32>) -> !torch.vtensor<[6],i1> return %0 : !torch.vtensor<[6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_isnan/model.mlir b/iree_tests/onnx/node/generated/test_isnan/model.mlir index 88510fe1b..fc6b99ece 100644 --- a/iree_tests/onnx/node/generated/test_isnan/model.mlir +++ b/iree_tests/onnx/node/generated/test_isnan/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_isnan(%arg0: !torch.vtensor<[6],f32>) -> !torch.vtensor<[6],i1> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.IsNaN"(%arg0) : (!torch.vtensor<[6],f32>) -> !torch.vtensor<[6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.IsNaN"(%arg0) : (!torch.vtensor<[6],f32>) -> !torch.vtensor<[6],i1> return %0 : !torch.vtensor<[6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_isnan_float16/model.mlir b/iree_tests/onnx/node/generated/test_isnan_float16/model.mlir index f1224b547..56c7a63d7 100644 --- a/iree_tests/onnx/node/generated/test_isnan_float16/model.mlir +++ b/iree_tests/onnx/node/generated/test_isnan_float16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_isnan_float16(%arg0: !torch.vtensor<[6],f16>) -> !torch.vtensor<[6],i1> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.IsNaN"(%arg0) : (!torch.vtensor<[6],f16>) -> !torch.vtensor<[6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.IsNaN"(%arg0) : (!torch.vtensor<[6],f16>) -> !torch.vtensor<[6],i1> return %0 : !torch.vtensor<[6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0/model.mlir index 2731340cc..023c6d419 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_2d_axis0(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[3,4],f32>, %arg2: !torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,4],f32>, !torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,4],f32>, !torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[3,4],f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/input_0.npy new file mode 100644 index 000000000..df2bb67f8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/input_1.npy new file mode 100644 index 000000000..7956a7d40 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/input_2.npy new file mode 100644 index 000000000..c21a50402 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/model.mlir new file mode 100644 index 000000000..d4d09357b --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_2d_axis0_expanded(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[3,4],f32>, %arg2: !torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[2],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[2],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[2],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[0],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[0],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[1,12],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,12],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,12],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[1,12],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[1,12],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,4],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1],f32> + return %26, %28, %29 : !torch.vtensor<[3,4],f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/output_0.npy new file mode 100644 index 000000000..80fa1ac82 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/output_1.npy new file mode 100644 index 000000000..c654eccf6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/output_2.npy new file mode 100644 index 000000000..7d01cd9de Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/input_0.npy new file mode 100644 index 000000000..df2bb67f8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/input_1.npy new file mode 100644 index 000000000..7956a7d40 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/input_2.npy new file mode 100644 index 000000000..c21a50402 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/model.mlir new file mode 100644 index 000000000..5123153e9 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_2d_axis0_expanded_ver18(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[3,4],f32>, %arg2: !torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[2],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[2],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[2],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[0],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[0],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[1,12],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,12],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,12],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[1,12],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[1,12],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,4],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1],f32> + return %27, %29, %30 : !torch.vtensor<[3,4],f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/output_0.npy new file mode 100644 index 000000000..80fa1ac82 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/output_1.npy new file mode 100644 index 000000000..c654eccf6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/output_2.npy new file mode 100644 index 000000000..7d01cd9de Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis0_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1/model.mlir index 7999575f6..ed9edd74d 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_2d_axis1(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[4],f32>, %arg2: !torch.vtensor<[4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[4],f32>, !torch.vtensor<[4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[4],f32>, !torch.vtensor<[4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/input_0.npy new file mode 100644 index 000000000..df2bb67f8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/input_1.npy new file mode 100644 index 000000000..91e22e650 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/input_2.npy new file mode 100644 index 000000000..5d7d52980 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/model.mlir new file mode 100644 index 000000000..76134be00 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_2d_axis1_expanded(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[4],f32>, %arg2: !torch.vtensor<[4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[2],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[2],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[2],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,4],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,4],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[1,4],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[1,4],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,4],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[3,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[3,1],f32> + return %26, %28, %29 : !torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/output_0.npy new file mode 100644 index 000000000..c428a62ec Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/output_1.npy new file mode 100644 index 000000000..16530b1aa Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/output_2.npy new file mode 100644 index 000000000..d434d7fbe Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/input_0.npy new file mode 100644 index 000000000..df2bb67f8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/input_1.npy new file mode 100644 index 000000000..91e22e650 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/input_2.npy new file mode 100644 index 000000000..5d7d52980 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/model.mlir new file mode 100644 index 000000000..2503c2c5e --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_2d_axis1_expanded_ver18(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[4],f32>, %arg2: !torch.vtensor<[4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[2],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[2],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[2],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,4],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,4],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[1,4],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[1,4],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,4],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[3,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[3,1],f32> + return %27, %29, %30 : !torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/output_0.npy new file mode 100644 index 000000000..c428a62ec Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/output_1.npy new file mode 100644 index 000000000..16530b1aa Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/output_2.npy new file mode 100644 index 000000000..d434d7fbe Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis1_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1/model.mlir index 02a9d6f36..0f6706ce1 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_2d_axis_negative_1(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[4],f32>, %arg2: !torch.vtensor<[4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[4],f32>, !torch.vtensor<[4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[4],f32>, !torch.vtensor<[4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/input_0.npy new file mode 100644 index 000000000..df2bb67f8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/input_1.npy new file mode 100644 index 000000000..f1a17b380 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/input_2.npy new file mode 100644 index 000000000..002e5010e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/model.mlir new file mode 100644 index 000000000..8d4e76a93 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_2d_axis_negative_1_expanded(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[4],f32>, %arg2: !torch.vtensor<[4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[2],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[2],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[2],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,4],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,4],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[1,4],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[1,4],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,4],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[3,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[3,1],f32> + return %26, %28, %29 : !torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/output_0.npy new file mode 100644 index 000000000..72afa14bf Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/output_1.npy new file mode 100644 index 000000000..16530b1aa Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/output_2.npy new file mode 100644 index 000000000..d434d7fbe Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/input_0.npy new file mode 100644 index 000000000..df2bb67f8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/input_1.npy new file mode 100644 index 000000000..f1a17b380 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/input_2.npy new file mode 100644 index 000000000..002e5010e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/model.mlir new file mode 100644 index 000000000..3b6ff0732 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_2d_axis_negative_1_expanded_ver18(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[4],f32>, %arg2: !torch.vtensor<[4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[2],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[2],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[2],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,4],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,4],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[1,4],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[1,4],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,4],f32>) -> !torch.vtensor<[3,4],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,4],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[3,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[3,1],f32> + return %27, %29, %30 : !torch.vtensor<[3,4],f32>, !torch.vtensor<[3,1],f32>, !torch.vtensor<[3,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/output_0.npy new file mode 100644 index 000000000..72afa14bf Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/output_1.npy new file mode 100644 index 000000000..16530b1aa Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/output_2.npy new file mode 100644 index 000000000..d434d7fbe Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_1_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2/model.mlir index 7f8326687..256b3aa67 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_2d_axis_negative_2(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[3,4],f32>, %arg2: !torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,4],f32>, !torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,4],f32>, !torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[3,4],f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/input_0.npy new file mode 100644 index 000000000..df2bb67f8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/input_1.npy new file mode 100644 index 000000000..771e2e8fc Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/input_2.npy new file mode 100644 index 000000000..b214faecf Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/model.mlir new file mode 100644 index 000000000..eddeacfa6 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_2d_axis_negative_2_expanded(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[3,4],f32>, %arg2: !torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[2],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[2],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[2],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[0],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[0],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[1,12],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,12],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,12],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[1,12],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[1,12],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,4],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1],f32> + return %26, %28, %29 : !torch.vtensor<[3,4],f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/output_0.npy new file mode 100644 index 000000000..f0788bf1d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/output_1.npy new file mode 100644 index 000000000..c654eccf6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/output_2.npy new file mode 100644 index 000000000..7d01cd9de Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/input_0.npy new file mode 100644 index 000000000..df2bb67f8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/input_1.npy new file mode 100644 index 000000000..771e2e8fc Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/input_2.npy new file mode 100644 index 000000000..b214faecf Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/model.mlir new file mode 100644 index 000000000..26f3dc59f --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_2d_axis_negative_2_expanded_ver18(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[3,4],f32>, %arg2: !torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[2],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[2],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[2],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[0],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[0],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[1,12],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,12],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,12],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[1,12],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[1,12],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[1,12],f32>) -> !torch.vtensor<[1,12],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[1,12],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,4],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1],f32> + return %27, %29, %30 : !torch.vtensor<[3,4],f32>, !torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/output_0.npy new file mode 100644 index 000000000..f0788bf1d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/output_1.npy new file mode 100644 index 000000000..c654eccf6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/output_2.npy new file mode 100644 index 000000000..7d01cd9de Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_2d_axis_negative_2_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon/model.mlir index 33daa2a58..a2d38c1eb 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_3d_axis0_epsilon(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[2,3,5],f32>, %arg2: !torch.vtensor<[2,3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 0 : si64, torch.onnx.epsilon = 1.000000e-01 : f32} : (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1,1,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 0 : si64, torch.onnx.epsilon = 1.000000e-01 : f32} : (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1,1,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/input_0.npy new file mode 100644 index 000000000..97890311d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/input_1.npy new file mode 100644 index 000000000..a512f9f88 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/input_2.npy new file mode 100644 index 000000000..80f4c66e1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/model.mlir new file mode 100644 index 000000000..f2316cd6d --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_3d_axis0_epsilon_expanded(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[2,3,5],f32>, %arg2: !torch.vtensor<[2,3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[3],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[0],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[0],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[1,30],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,30],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,30],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[1,30],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[1,30],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,5],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1,1],f32> + return %26, %28, %29 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/output_0.npy new file mode 100644 index 000000000..cfdec1c82 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/output_1.npy new file mode 100644 index 000000000..411169aab Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/output_2.npy new file mode 100644 index 000000000..b587cb1d8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/input_0.npy new file mode 100644 index 000000000..97890311d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/input_1.npy new file mode 100644 index 000000000..a512f9f88 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/input_2.npy new file mode 100644 index 000000000..80f4c66e1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/model.mlir new file mode 100644 index 000000000..fc8c92eed --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_3d_axis0_epsilon_expanded_ver18(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[2,3,5],f32>, %arg2: !torch.vtensor<[2,3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[3],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[0],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[0],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[1,30],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,30],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,30],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[1,30],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[1,30],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,5],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1,1],f32> + return %27, %29, %30 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/output_0.npy new file mode 100644 index 000000000..cfdec1c82 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/output_1.npy new file mode 100644 index 000000000..411169aab Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/output_2.npy new file mode 100644 index 000000000..b587cb1d8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis0_epsilon_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon/model.mlir index 0ef0ec61a..9cdcd7220 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_3d_axis1_epsilon(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[3,5],f32>, %arg2: !torch.vtensor<[3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,1,1],f32>, !torch.vtensor<[2,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64, torch.onnx.epsilon = 1.000000e-01 : f32} : (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[3,5],f32>, !torch.vtensor<[3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,1,1],f32>, !torch.vtensor<[2,1,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64, torch.onnx.epsilon = 1.000000e-01 : f32} : (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[3,5],f32>, !torch.vtensor<[3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,1,1],f32>, !torch.vtensor<[2,1,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,1,1],f32>, !torch.vtensor<[2,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/input_0.npy new file mode 100644 index 000000000..97890311d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/input_1.npy new file mode 100644 index 000000000..dbd013fa3 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/input_2.npy new file mode 100644 index 000000000..3e3dd874a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/model.mlir new file mode 100644 index 000000000..0513dd123 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_3d_axis1_epsilon_expanded(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[3,5],f32>, %arg2: !torch.vtensor<[3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,1,1],f32>, !torch.vtensor<[2,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[3],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[2,15],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[2,15],f32>) -> !torch.vtensor<[2,15],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[2,15],f32>) -> !torch.vtensor<[2,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[2,15],f32>) -> !torch.vtensor<[2,15],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[2,15],f32>) -> !torch.vtensor<[2,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[2,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,15],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,15],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[2,15],f32>) -> !torch.vtensor<[2,15],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[1,15],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[1,15],f32>) -> !torch.vtensor<[2,15],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[1,15],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[1,15],f32>) -> !torch.vtensor<[2,15],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,5],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,1,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,1,1],f32> + return %26, %28, %29 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,1,1],f32>, !torch.vtensor<[2,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/output_0.npy new file mode 100644 index 000000000..bd56e8c5c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/output_1.npy new file mode 100644 index 000000000..43c2bf3d1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/output_2.npy new file mode 100644 index 000000000..1b7c500b6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/input_0.npy new file mode 100644 index 000000000..97890311d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/input_1.npy new file mode 100644 index 000000000..dbd013fa3 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/input_2.npy new file mode 100644 index 000000000..3e3dd874a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/model.mlir new file mode 100644 index 000000000..35afd9b74 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_3d_axis1_epsilon_expanded_ver18(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[3,5],f32>, %arg2: !torch.vtensor<[3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,1,1],f32>, !torch.vtensor<[2,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[3],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[2,15],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[2,15],f32>) -> !torch.vtensor<[2,15],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[2,15],f32>) -> !torch.vtensor<[2,15],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[2,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,15],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,15],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[2,15],f32>) -> !torch.vtensor<[2,15],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[1,15],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[1,15],f32>) -> !torch.vtensor<[2,15],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[1,15],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[1,15],f32>) -> !torch.vtensor<[2,15],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,5],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,1,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,1,1],f32> + return %27, %29, %30 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,1,1],f32>, !torch.vtensor<[2,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/output_0.npy new file mode 100644 index 000000000..bd56e8c5c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/output_1.npy new file mode 100644 index 000000000..43c2bf3d1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/output_2.npy new file mode 100644 index 000000000..1b7c500b6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis1_epsilon_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon/model.mlir index c1e882513..a04963e02 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_3d_axis2_epsilon(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[5],f32>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,1],f32>, !torch.vtensor<[2,3,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 2 : si64, torch.onnx.epsilon = 1.000000e-01 : f32} : (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[5],f32>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,1],f32>, !torch.vtensor<[2,3,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 2 : si64, torch.onnx.epsilon = 1.000000e-01 : f32} : (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[5],f32>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,1],f32>, !torch.vtensor<[2,3,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,1],f32>, !torch.vtensor<[2,3,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded/input_0.npy new file mode 100644 index 000000000..97890311d 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b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded/model.mlir new file mode 100644 index 000000000..96ea9a1c9 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_3d_axis2_epsilon_expanded(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[5],f32>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,1],f32>, !torch.vtensor<[2,3,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[3],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[6,5],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[6,5],f32>) -> !torch.vtensor<[6,5],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[6,5],f32>) -> !torch.vtensor<[6,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[6,5],f32>) -> !torch.vtensor<[6,5],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[6,5],f32>) -> !torch.vtensor<[6,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[6,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,5],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,5],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[6,5],f32>) -> !torch.vtensor<[6,5],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[6,5],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[6,5],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,5],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,1],f32> + return %26, %28, %29 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,1],f32>, !torch.vtensor<[2,3,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded/output_0.npy new file mode 100644 index 000000000..04e751211 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded/output_1.npy new file mode 100644 index 000000000..f05fcd500 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded/output_2.npy new file mode 100644 index 000000000..e932fca06 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/input_0.npy new file mode 100644 index 000000000..97890311d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/input_1.npy new file mode 100644 index 000000000..256b87882 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/input_2.npy new file mode 100644 index 000000000..f80f77a6f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/model.mlir new file mode 100644 index 000000000..c17e7ea2d --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_3d_axis2_epsilon_expanded_ver18(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[5],f32>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,1],f32>, !torch.vtensor<[2,3,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[3],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[6,5],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[6,5],f32>) -> !torch.vtensor<[6,5],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[6,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[6,5],f32>) -> !torch.vtensor<[6,5],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[6,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[6,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,5],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,5],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[6,5],f32>) -> !torch.vtensor<[6,5],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[6,5],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[6,5],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,5],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,1],f32> + return %27, %29, %30 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,1],f32>, !torch.vtensor<[2,3,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/output_0.npy new file mode 100644 index 000000000..04e751211 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/output_1.npy new file mode 100644 index 000000000..f05fcd500 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/output_2.npy new file mode 100644 index 000000000..e932fca06 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis2_epsilon_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon/model.mlir index 54a688913..2e69ab20b 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_3d_axis_negative_1_epsilon(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[5],f32>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,1],f32>, !torch.vtensor<[2,3,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -1 : si64, torch.onnx.epsilon = 1.000000e-01 : f32} : (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[5],f32>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,1],f32>, !torch.vtensor<[2,3,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -1 : si64, torch.onnx.epsilon = 1.000000e-01 : f32} : (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[5],f32>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,1],f32>, !torch.vtensor<[2,3,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,1],f32>, !torch.vtensor<[2,3,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/input_0.npy new file mode 100644 index 000000000..97890311d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/input_1.npy new file mode 100644 index 000000000..ab7a2d37c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/input_2.npy new file mode 100644 index 000000000..2813b4e3e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/model.mlir new file mode 100644 index 000000000..a2d102ee5 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_3d_axis_negative_1_epsilon_expanded(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[5],f32>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,1],f32>, !torch.vtensor<[2,3,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[3],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[6,5],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[6,5],f32>) -> !torch.vtensor<[6,5],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[6,5],f32>) -> !torch.vtensor<[6,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[6,5],f32>) -> !torch.vtensor<[6,5],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[6,5],f32>) -> !torch.vtensor<[6,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[6,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,5],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,5],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[6,5],f32>) -> !torch.vtensor<[6,5],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[6,5],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[6,5],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,5],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,1],f32> + return %26, %28, %29 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,1],f32>, !torch.vtensor<[2,3,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/output_0.npy new file mode 100644 index 000000000..fc1184c41 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/output_1.npy new file mode 100644 index 000000000..f05fcd500 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/output_2.npy new file mode 100644 index 000000000..e932fca06 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/input_0.npy new file mode 100644 index 000000000..97890311d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/input_1.npy new file mode 100644 index 000000000..ab7a2d37c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/input_2.npy new file mode 100644 index 000000000..2813b4e3e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/model.mlir new file mode 100644 index 000000000..f0f5a8d07 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[5],f32>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,1],f32>, !torch.vtensor<[2,3,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[3],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[6,5],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[6,5],f32>) -> !torch.vtensor<[6,5],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[6,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[6,5],f32>) -> !torch.vtensor<[6,5],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[6,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[6,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,5],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,5],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[6,5],f32>) -> !torch.vtensor<[6,5],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[6,5],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[6,5],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[6,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,5],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,1],f32> + return %27, %29, %30 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,1],f32>, !torch.vtensor<[2,3,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/output_0.npy new file mode 100644 index 000000000..fc1184c41 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/output_1.npy new file mode 100644 index 000000000..f05fcd500 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/output_2.npy new file mode 100644 index 000000000..e932fca06 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon/model.mlir index 8913dd016..d04c38489 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_3d_axis_negative_2_epsilon(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[3,5],f32>, %arg2: !torch.vtensor<[3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,1,1],f32>, !torch.vtensor<[2,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -2 : si64, torch.onnx.epsilon = 1.000000e-01 : f32} : (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[3,5],f32>, !torch.vtensor<[3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,1,1],f32>, !torch.vtensor<[2,1,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -2 : si64, torch.onnx.epsilon = 1.000000e-01 : f32} : (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[3,5],f32>, !torch.vtensor<[3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,1,1],f32>, !torch.vtensor<[2,1,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,1,1],f32>, !torch.vtensor<[2,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/input_0.npy new file mode 100644 index 000000000..97890311d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/input_1.npy new file mode 100644 index 000000000..adeda27ff Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/input_2.npy new file mode 100644 index 000000000..b80f2db3e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/model.mlir new file mode 100644 index 000000000..3b37f4dae --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_3d_axis_negative_2_epsilon_expanded(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[3,5],f32>, %arg2: !torch.vtensor<[3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,1,1],f32>, !torch.vtensor<[2,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[3],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[2,15],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[2,15],f32>) -> !torch.vtensor<[2,15],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[2,15],f32>) -> !torch.vtensor<[2,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[2,15],f32>) -> !torch.vtensor<[2,15],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[2,15],f32>) -> !torch.vtensor<[2,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[2,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,15],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,15],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[2,15],f32>) -> !torch.vtensor<[2,15],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[1,15],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[1,15],f32>) -> !torch.vtensor<[2,15],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[1,15],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[1,15],f32>) -> !torch.vtensor<[2,15],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,5],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,1,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,1,1],f32> + return %26, %28, %29 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,1,1],f32>, !torch.vtensor<[2,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/output_0.npy new file mode 100644 index 000000000..11544d1d5 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/output_1.npy new file mode 100644 index 000000000..43c2bf3d1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/output_2.npy new file mode 100644 index 000000000..1b7c500b6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/input_0.npy new file mode 100644 index 000000000..97890311d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/input_1.npy new file mode 100644 index 000000000..adeda27ff Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/input_2.npy new file mode 100644 index 000000000..b80f2db3e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/model.mlir new file mode 100644 index 000000000..0ba672399 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[3,5],f32>, %arg2: !torch.vtensor<[3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,1,1],f32>, !torch.vtensor<[2,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[3],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[2,15],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[2,15],f32>) -> !torch.vtensor<[2,15],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[2,15],f32>) -> !torch.vtensor<[2,15],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[2,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,15],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,15],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[2,15],f32>) -> !torch.vtensor<[2,15],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[1,15],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[1,15],f32>) -> !torch.vtensor<[2,15],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[1,15],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[1,15],f32>) -> !torch.vtensor<[2,15],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[2,15],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,5],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,1,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,1,1],f32> + return %27, %29, %30 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,1,1],f32>, !torch.vtensor<[2,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/output_0.npy new file mode 100644 index 000000000..11544d1d5 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/output_1.npy new file mode 100644 index 000000000..43c2bf3d1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/output_2.npy new file mode 100644 index 000000000..1b7c500b6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon/model.mlir index 362d21aeb..d83e7c7e6 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_3d_axis_negative_3_epsilon(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[2,3,5],f32>, %arg2: !torch.vtensor<[2,3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -3 : si64, torch.onnx.epsilon = 1.000000e-01 : f32} : (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1,1,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -3 : si64, torch.onnx.epsilon = 1.000000e-01 : f32} : (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[2,3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1,1,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/input_0.npy new file mode 100644 index 000000000..97890311d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/input_1.npy new file mode 100644 index 000000000..d7032a053 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/input_2.npy new file mode 100644 index 000000000..a0f5d9f42 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/model.mlir new file mode 100644 index 000000000..2a73a1b8c --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_3d_axis_negative_3_epsilon_expanded(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[2,3,5],f32>, %arg2: !torch.vtensor<[2,3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[3],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-3> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[0],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[0],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -3 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[1,30],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,30],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,30],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[1,30],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[1,30],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,5],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1,1],f32> + return %26, %28, %29 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/output_0.npy new file mode 100644 index 000000000..6c1b6b4e8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/output_1.npy new file mode 100644 index 000000000..411169aab Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/output_2.npy new file mode 100644 index 000000000..b587cb1d8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/input_0.npy new file mode 100644 index 000000000..97890311d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/input_1.npy new file mode 100644 index 000000000..d7032a053 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/input_2.npy new file mode 100644 index 000000000..a0f5d9f42 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/model.mlir new file mode 100644 index 000000000..d379c5448 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18(%arg0: !torch.vtensor<[2,3,5],f32>, %arg1: !torch.vtensor<[2,3,5],f32>, %arg2: !torch.vtensor<[2,3,5],f32>) -> (!torch.vtensor<[2,3,5],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e-01> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[3],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-3> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[0],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[0],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -3 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[1,30],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,30],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,30],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[1,30],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,5],f32>) -> !torch.vtensor<[1,30],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[1,30],f32>) -> !torch.vtensor<[1,30],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[1,30],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,5],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1,1],f32> + return %27, %29, %30 : !torch.vtensor<[2,3,5],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/output_0.npy new file mode 100644 index 000000000..6c1b6b4e8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/output_1.npy new file mode 100644 index 000000000..411169aab Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/output_2.npy new file mode 100644 index 000000000..b587cb1d8 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0/model.mlir index 66498404c..824c84d7d 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_4d_axis0(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[2,3,4,5],f32>, %arg2: !torch.vtensor<[2,3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[1,1,1,1],f32>, !torch.vtensor<[1,1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[1,1,1,1],f32>, !torch.vtensor<[1,1,1,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[1,1,1,1],f32>, !torch.vtensor<[1,1,1,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[1,1,1,1],f32>, !torch.vtensor<[1,1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/input_1.npy new file mode 100644 index 000000000..c4d9c6b85 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/input_2.npy new file mode 100644 index 000000000..4de266107 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/model.mlir new file mode 100644 index 000000000..b0b775369 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_4d_axis0_expanded(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[2,3,4,5],f32>, %arg2: !torch.vtensor<[2,3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[1,1,1,1],f32>, !torch.vtensor<[1,1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[0],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[0],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,120],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,120],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1,1,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1,1,1],f32> + return %26, %28, %29 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[1,1,1,1],f32>, !torch.vtensor<[1,1,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/output_0.npy new file mode 100644 index 000000000..1f2a2fe59 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/output_1.npy new file mode 100644 index 000000000..f83d05643 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/output_2.npy new file mode 100644 index 000000000..65ca46049 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/input_1.npy new file mode 100644 index 000000000..c4d9c6b85 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/input_2.npy new file mode 100644 index 000000000..4de266107 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/model.mlir new file mode 100644 index 000000000..77fca035f --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_4d_axis0_expanded_ver18(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[2,3,4,5],f32>, %arg2: !torch.vtensor<[2,3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[1,1,1,1],f32>, !torch.vtensor<[1,1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[0],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[0],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,120],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,120],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1,1,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1,1,1],f32> + return %27, %29, %30 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[1,1,1,1],f32>, !torch.vtensor<[1,1,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/output_0.npy new file mode 100644 index 000000000..1f2a2fe59 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/output_1.npy new file mode 100644 index 000000000..f83d05643 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/output_2.npy new file mode 100644 index 000000000..65ca46049 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis0_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1/model.mlir index eee7d0fd7..df56fff53 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_4d_axis1(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>, %arg2: !torch.vtensor<[3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,1,1,1],f32>, !torch.vtensor<[2,1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,1,1,1],f32>, !torch.vtensor<[2,1,1,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,1,1,1],f32>, !torch.vtensor<[2,1,1,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,1,1,1],f32>, !torch.vtensor<[2,1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/input_1.npy new file mode 100644 index 000000000..69677a639 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/input_2.npy new file mode 100644 index 000000000..00300b882 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/model.mlir new file mode 100644 index 000000000..45c5d829c --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_4d_axis1_expanded(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>, %arg2: !torch.vtensor<[3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,1,1,1],f32>, !torch.vtensor<[2,1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[2,60],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[2,60],f32>) -> !torch.vtensor<[2,60],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[2,60],f32>) -> !torch.vtensor<[2,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[2,60],f32>) -> !torch.vtensor<[2,60],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[2,60],f32>) -> !torch.vtensor<[2,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[2,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,60],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,60],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[2,60],f32>) -> !torch.vtensor<[2,60],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1,60],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[1,60],f32>) -> !torch.vtensor<[2,60],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1,60],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[1,60],f32>) -> !torch.vtensor<[2,60],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,1,1,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,1,1,1],f32> + return %26, %28, %29 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,1,1,1],f32>, !torch.vtensor<[2,1,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/output_0.npy new file mode 100644 index 000000000..d60819c2c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/output_1.npy new file mode 100644 index 000000000..fa7eee68a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/output_2.npy new file mode 100644 index 000000000..3b3bff7cc Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/input_1.npy new file mode 100644 index 000000000..69677a639 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/input_2.npy new file mode 100644 index 000000000..00300b882 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/model.mlir new file mode 100644 index 000000000..d459454b1 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_4d_axis1_expanded_ver18(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>, %arg2: !torch.vtensor<[3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,1,1,1],f32>, !torch.vtensor<[2,1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[2,60],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[2,60],f32>) -> !torch.vtensor<[2,60],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[2,60],f32>) -> !torch.vtensor<[2,60],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[2,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,60],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,60],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[2,60],f32>) -> !torch.vtensor<[2,60],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1,60],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[1,60],f32>) -> !torch.vtensor<[2,60],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1,60],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[1,60],f32>) -> !torch.vtensor<[2,60],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,1,1,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,1,1,1],f32> + return %27, %29, %30 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,1,1,1],f32>, !torch.vtensor<[2,1,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/output_0.npy new file mode 100644 index 000000000..d60819c2c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/output_1.npy new file mode 100644 index 000000000..fa7eee68a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/output_2.npy new file mode 100644 index 000000000..3b3bff7cc Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis1_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2/model.mlir index 9b8b63228..608bcda3f 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_4d_axis2(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[4,5],f32>, %arg2: !torch.vtensor<[4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,1,1],f32>, !torch.vtensor<[2,3,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[4,5],f32>, !torch.vtensor<[4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,1,1],f32>, !torch.vtensor<[2,3,1,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[4,5],f32>, !torch.vtensor<[4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,1,1],f32>, !torch.vtensor<[2,3,1,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,1,1],f32>, !torch.vtensor<[2,3,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/input_1.npy new file mode 100644 index 000000000..1f8914d6c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/input_2.npy new file mode 100644 index 000000000..2eabfa9b6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/model.mlir new file mode 100644 index 000000000..87e1865fc --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_4d_axis2_expanded(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[4,5],f32>, %arg2: !torch.vtensor<[4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,1,1],f32>, !torch.vtensor<[2,3,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[6,20],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[6,20],f32>) -> !torch.vtensor<[6,20],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[6,20],f32>) -> !torch.vtensor<[6,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[6,20],f32>) -> !torch.vtensor<[6,20],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[6,20],f32>) -> !torch.vtensor<[6,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[6,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,20],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,20],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[6,20],f32>) -> !torch.vtensor<[6,20],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[4,5],f32>) -> !torch.vtensor<[1,20],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[1,20],f32>) -> !torch.vtensor<[6,20],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[4,5],f32>) -> !torch.vtensor<[1,20],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[1,20],f32>) -> !torch.vtensor<[6,20],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,1,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,1,1],f32> + return %26, %28, %29 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,1,1],f32>, !torch.vtensor<[2,3,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/output_0.npy new file mode 100644 index 000000000..60c8b048f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/output_1.npy new file mode 100644 index 000000000..9988c1053 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/output_2.npy new file mode 100644 index 000000000..b8f5230b1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/input_1.npy new file mode 100644 index 000000000..1f8914d6c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/input_2.npy new file mode 100644 index 000000000..2eabfa9b6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/model.mlir new file mode 100644 index 000000000..3bea71a68 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_4d_axis2_expanded_ver18(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[4,5],f32>, %arg2: !torch.vtensor<[4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,1,1],f32>, !torch.vtensor<[2,3,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[6,20],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[6,20],f32>) -> !torch.vtensor<[6,20],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[6,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[6,20],f32>) -> !torch.vtensor<[6,20],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[6,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[6,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,20],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,20],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[6,20],f32>) -> !torch.vtensor<[6,20],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[4,5],f32>) -> !torch.vtensor<[1,20],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[1,20],f32>) -> !torch.vtensor<[6,20],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[4,5],f32>) -> !torch.vtensor<[1,20],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[1,20],f32>) -> !torch.vtensor<[6,20],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,1,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,1,1],f32> + return %27, %29, %30 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,1,1],f32>, !torch.vtensor<[2,3,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/output_0.npy new file mode 100644 index 000000000..60c8b048f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/output_1.npy new file mode 100644 index 000000000..9988c1053 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/output_2.npy new file mode 100644 index 000000000..b8f5230b1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis2_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3/model.mlir index 46304a8ca..3534b744b 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_4d_axis3(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 3 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[5],f32>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = 3 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[5],f32>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/input_1.npy new file mode 100644 index 000000000..bc1bf314d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/input_2.npy new file mode 100644 index 000000000..b7f6e436b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/model.mlir new file mode 100644 index 000000000..b7a1c04d6 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_4d_axis3_expanded(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<3> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 3 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[24,5],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[24,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,5],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,5],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[24,5],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[24,5],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,4,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,4,1],f32> + return %26, %28, %29 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/output_0.npy new file mode 100644 index 000000000..8775580ba Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/output_1.npy new file mode 100644 index 000000000..3277da12d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/output_2.npy new file mode 100644 index 000000000..296f8e9fd Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/input_1.npy new file mode 100644 index 000000000..bc1bf314d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/input_2.npy new file mode 100644 index 000000000..b7f6e436b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/model.mlir new file mode 100644 index 000000000..00a481537 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_4d_axis3_expanded_ver18(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<3> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> + %7 = torch.operator "onnx.Sub"(%3, %5) : (!torch.vtensor<[],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = 3 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[24,5],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[24,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[24,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[24,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,5],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,5],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[24,5],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[24,5],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,4,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,4,1],f32> + return %27, %29, %30 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/output_0.npy new file mode 100644 index 000000000..8775580ba Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/output_1.npy new file mode 100644 index 000000000..3277da12d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/output_2.npy new file mode 100644 index 000000000..296f8e9fd Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis3_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1/model.mlir index 171095042..2d3a22f0e 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_4d_axis_negative_1(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[5],f32>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[5],f32>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/input_1.npy new file mode 100644 index 000000000..bea2f425f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/input_2.npy new file mode 100644 index 000000000..8859c03ff Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/model.mlir new file mode 100644 index 000000000..3c3db1411 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_4d_axis_negative_1_expanded(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[24,5],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[24,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,5],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,5],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[24,5],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[24,5],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,4,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,4,1],f32> + return %26, %28, %29 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/output_0.npy new file mode 100644 index 000000000..37d634906 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/output_1.npy new file mode 100644 index 000000000..3277da12d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/output_2.npy new file mode 100644 index 000000000..296f8e9fd Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/input_1.npy new file mode 100644 index 000000000..bea2f425f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/input_2.npy new file mode 100644 index 000000000..8859c03ff Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/model.mlir new file mode 100644 index 000000000..b09c9bd6d --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_4d_axis_negative_1_expanded_ver18(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[24,5],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[24,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[24,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[24,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,5],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,5],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[24,5],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[24,5],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,4,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,4,1],f32> + return %27, %29, %30 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/output_0.npy new file mode 100644 index 000000000..37d634906 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/output_1.npy new file mode 100644 index 000000000..3277da12d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/output_2.npy new file mode 100644 index 000000000..296f8e9fd Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_1_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2/model.mlir index 1db4721b1..ef402b07b 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_4d_axis_negative_2(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[4,5],f32>, %arg2: !torch.vtensor<[4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,1,1],f32>, !torch.vtensor<[2,3,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[4,5],f32>, !torch.vtensor<[4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,1,1],f32>, !torch.vtensor<[2,3,1,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[4,5],f32>, !torch.vtensor<[4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,1,1],f32>, !torch.vtensor<[2,3,1,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,1,1],f32>, !torch.vtensor<[2,3,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/input_1.npy new file mode 100644 index 000000000..0e866258f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/input_2.npy new file mode 100644 index 000000000..35aa82928 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/model.mlir new file mode 100644 index 000000000..6d918e734 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_4d_axis_negative_2_expanded(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[4,5],f32>, %arg2: !torch.vtensor<[4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,1,1],f32>, !torch.vtensor<[2,3,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[6,20],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[6,20],f32>) -> !torch.vtensor<[6,20],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[6,20],f32>) -> !torch.vtensor<[6,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[6,20],f32>) -> !torch.vtensor<[6,20],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[6,20],f32>) -> !torch.vtensor<[6,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[6,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,20],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,20],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[6,20],f32>) -> !torch.vtensor<[6,20],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[4,5],f32>) -> !torch.vtensor<[1,20],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[1,20],f32>) -> !torch.vtensor<[6,20],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[4,5],f32>) -> !torch.vtensor<[1,20],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[1,20],f32>) -> !torch.vtensor<[6,20],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,1,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,1,1],f32> + return %26, %28, %29 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,1,1],f32>, !torch.vtensor<[2,3,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/output_0.npy new file mode 100644 index 000000000..12ec68fc4 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/output_1.npy new file mode 100644 index 000000000..9988c1053 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/output_2.npy new file mode 100644 index 000000000..b8f5230b1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/input_1.npy new file mode 100644 index 000000000..0e866258f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/input_2.npy new file mode 100644 index 000000000..35aa82928 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/model.mlir new file mode 100644 index 000000000..dc1f025c2 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_4d_axis_negative_2_expanded_ver18(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[4,5],f32>, %arg2: !torch.vtensor<[4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,1,1],f32>, !torch.vtensor<[2,3,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[6,20],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[6,20],f32>) -> !torch.vtensor<[6,20],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[6,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[6,20],f32>) -> !torch.vtensor<[6,20],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[6,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[6,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,20],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,20],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[6,20],f32>) -> !torch.vtensor<[6,20],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[4,5],f32>) -> !torch.vtensor<[1,20],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[1,20],f32>) -> !torch.vtensor<[6,20],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[4,5],f32>) -> !torch.vtensor<[1,20],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[1,20],f32>) -> !torch.vtensor<[6,20],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[6,20],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[6,1],f32>) -> !torch.vtensor<[6,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,1,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[6,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,1,1],f32> + return %27, %29, %30 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,1,1],f32>, !torch.vtensor<[2,3,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/output_0.npy new file mode 100644 index 000000000..12ec68fc4 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/output_1.npy new file mode 100644 index 000000000..9988c1053 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/output_2.npy new file mode 100644 index 000000000..b8f5230b1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_2_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3/model.mlir index 3d458a2e9..929cdfb98 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_4d_axis_negative_3(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>, %arg2: !torch.vtensor<[3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,1,1,1],f32>, !torch.vtensor<[2,1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -3 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,1,1,1],f32>, !torch.vtensor<[2,1,1,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -3 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,1,1,1],f32>, !torch.vtensor<[2,1,1,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,1,1,1],f32>, !torch.vtensor<[2,1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/input_1.npy new file mode 100644 index 000000000..aeb4382a3 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/input_2.npy new file mode 100644 index 000000000..655a6b58f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/model.mlir new file mode 100644 index 000000000..8abe4e1a3 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_4d_axis_negative_3_expanded(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>, %arg2: !torch.vtensor<[3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,1,1,1],f32>, !torch.vtensor<[2,1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-3> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -3 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[2,60],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[2,60],f32>) -> !torch.vtensor<[2,60],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[2,60],f32>) -> !torch.vtensor<[2,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[2,60],f32>) -> !torch.vtensor<[2,60],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[2,60],f32>) -> !torch.vtensor<[2,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[2,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,60],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,60],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[2,60],f32>) -> !torch.vtensor<[2,60],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1,60],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[1,60],f32>) -> !torch.vtensor<[2,60],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1,60],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[1,60],f32>) -> !torch.vtensor<[2,60],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,1,1,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,1,1,1],f32> + return %26, %28, %29 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,1,1,1],f32>, !torch.vtensor<[2,1,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/output_0.npy new file mode 100644 index 000000000..01bdaa939 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/output_1.npy new file mode 100644 index 000000000..fa7eee68a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/output_2.npy new file mode 100644 index 000000000..3b3bff7cc Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/input_1.npy new file mode 100644 index 000000000..aeb4382a3 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/input_2.npy new file mode 100644 index 000000000..655a6b58f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/model.mlir new file mode 100644 index 000000000..c68355169 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_4d_axis_negative_3_expanded_ver18(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>, %arg2: !torch.vtensor<[3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,1,1,1],f32>, !torch.vtensor<[2,1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-3> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[1],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -3 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[2,60],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[2,60],f32>) -> !torch.vtensor<[2,60],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[2,60],f32>) -> !torch.vtensor<[2,60],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[2,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,60],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,60],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[2,60],f32>) -> !torch.vtensor<[2,60],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1,60],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[1,60],f32>) -> !torch.vtensor<[2,60],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1,60],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[1,60],f32>) -> !torch.vtensor<[2,60],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[2,60],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,1,1,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[2,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,1,1,1],f32> + return %27, %29, %30 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,1,1,1],f32>, !torch.vtensor<[2,1,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/output_0.npy new file mode 100644 index 000000000..01bdaa939 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/output_1.npy new file mode 100644 index 000000000..fa7eee68a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/output_2.npy new file mode 100644 index 000000000..3b3bff7cc Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_3_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4/model.mlir index 36d6a07c9..364faa7c5 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_4d_axis_negative_4(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[2,3,4,5],f32>, %arg2: !torch.vtensor<[2,3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[1,1,1,1],f32>, !torch.vtensor<[1,1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -4 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[1,1,1,1],f32>, !torch.vtensor<[1,1,1,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) {torch.onnx.axis = -4 : si64} : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[1,1,1,1],f32>, !torch.vtensor<[1,1,1,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[1,1,1,1],f32>, !torch.vtensor<[1,1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/input_1.npy new file mode 100644 index 000000000..0e0eb72d6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/input_2.npy new file mode 100644 index 000000000..9aec1a136 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/model.mlir new file mode 100644 index 000000000..18b9b233b --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_4d_axis_negative_4_expanded(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[2,3,4,5],f32>, %arg2: !torch.vtensor<[2,3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[1,1,1,1],f32>, !torch.vtensor<[1,1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-4> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[0],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[0],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -4 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,120],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,120],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1,1,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1,1,1],f32> + return %26, %28, %29 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[1,1,1,1],f32>, !torch.vtensor<[1,1,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/output_0.npy new file mode 100644 index 000000000..6172a94f4 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/output_1.npy new file mode 100644 index 000000000..f83d05643 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/output_2.npy new file mode 100644 index 000000000..65ca46049 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/input_1.npy new file mode 100644 index 000000000..0e0eb72d6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/input_2.npy new file mode 100644 index 000000000..9aec1a136 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/model.mlir new file mode 100644 index 000000000..eedfe6015 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_4d_axis_negative_4_expanded_ver18(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[2,3,4,5],f32>, %arg2: !torch.vtensor<[2,3,4,5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[1,1,1,1],f32>, !torch.vtensor<[1,1,1,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-4> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[0],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[0],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -4 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,120],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,120],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[1,120],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[1,120],f32>) -> !torch.vtensor<[1,120],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[1,120],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1,1,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[1,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[1,1,1,1],f32> + return %27, %29, %30 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[1,1,1,1],f32>, !torch.vtensor<[1,1,1,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/output_0.npy new file mode 100644 index 000000000..6172a94f4 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/output_1.npy new file mode 100644 index 000000000..f83d05643 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/output_2.npy new file mode 100644 index 000000000..65ca46049 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_4d_axis_negative_4_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis/model.mlir index d32a1009e..46063881f 100644 --- a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_layer_normalization_default_axis(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[5],f32>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.LayerNormalization"(%arg0, %arg1, %arg2) : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[5],f32>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/input_1.npy new file mode 100644 index 000000000..5ac66e72e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/input_2.npy new file mode 100644 index 000000000..6dbd0f8e4 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/model.mlir new file mode 100644 index 000000000..712003172 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/model.mlir @@ -0,0 +1,37 @@ +module { + func.func @test_layer_normalization_default_axis_expanded(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[24,5],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %12 = torch.operator "onnx.ReduceMean"(%11) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,1],f32> + %13 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %14 = torch.operator "onnx.ReduceMean"(%13) {torch.onnx.axes = [1 : si64]} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,1],f32> + %15 = torch.operator "onnx.Mul"(%12, %12) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %16 = torch.operator "onnx.Sub"(%14, %15) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %17 = torch.operator "onnx.Add"(%16, %1) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[24,1],f32> + %18 = torch.operator "onnx.Sqrt"(%17) : (!torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %19 = torch.operator "onnx.Sub"(%11, %12) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,5],f32> + %20 = torch.operator "onnx.Div"(%19, %18) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,5],f32> + %21 = torch.operator "onnx.Cast"(%20) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %22 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %23 = torch.operator "onnx.Mul"(%21, %22) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[24,5],f32> + %24 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %25 = torch.operator "onnx.Add"(%23, %24) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[24,5],f32> + %26 = torch.operator "onnx.Reshape"(%25, %2) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %27 = torch.operator "onnx.Reciprocal"(%18) : (!torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %28 = torch.operator "onnx.Reshape"(%12, %9) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,4,1],f32> + %29 = torch.operator "onnx.Reshape"(%27, %9) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,4,1],f32> + return %26, %28, %29 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/output_0.npy new file mode 100644 index 000000000..8b062b767 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/output_1.npy new file mode 100644 index 000000000..3277da12d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/output_2.npy new file mode 100644 index 000000000..296f8e9fd Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/input_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/input_0.npy new file mode 100644 index 000000000..79e1ca896 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/input_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/input_1.npy new file mode 100644 index 000000000..5ac66e72e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/input_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/input_2.npy new file mode 100644 index 000000000..6dbd0f8e4 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/model.mlir new file mode 100644 index 000000000..7dee112fb --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/model.mlir @@ -0,0 +1,38 @@ +module { + func.func @test_layer_normalization_default_axis_expanded_ver18(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999974E-6> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[4],si64> + %3 = torch.operator "onnx.Size"(%2) : (!torch.vtensor<[4],si64>) -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Slice"(%2, %4, %5) : (!torch.vtensor<[4],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],si64> + %7 = torch.operator "onnx.Neg"(%5) : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[1],si64> + %8 = torch.operator "onnx.ConstantOfShape"(%7) {torch.onnx.value = dense<1> : tensor<1xsi64>} : (!torch.vtensor<[1],si64>) -> !torch.vtensor<[?],si64> + %9 = torch.operator "onnx.Concat"(%6, %8) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3],si64>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[?],si64> + %10 = torch.operator "onnx.Flatten"(%arg0) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[2,3,4,5],f32>) -> !torch.vtensor<[24,5],f32> + %11 = torch.operator "onnx.Cast"(%10) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %12 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %13 = torch.operator "onnx.ReduceMean"(%11, %12) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[24,1],f32> + %14 = torch.operator "onnx.Mul"(%11, %11) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %15 = torch.operator "onnx.ReduceMean"(%14, %12) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[24,1],f32> + %16 = torch.operator "onnx.Mul"(%13, %13) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %17 = torch.operator "onnx.Sub"(%15, %16) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %18 = torch.operator "onnx.Add"(%17, %1) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[24,1],f32> + %19 = torch.operator "onnx.Sqrt"(%18) : (!torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %20 = torch.operator "onnx.Sub"(%11, %13) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,5],f32> + %21 = torch.operator "onnx.Div"(%20, %19) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,5],f32> + %22 = torch.operator "onnx.Cast"(%21) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[24,5],f32>) -> !torch.vtensor<[24,5],f32> + %23 = torch.operator "onnx.Flatten"(%arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %24 = torch.operator "onnx.Mul"(%22, %23) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[24,5],f32> + %25 = torch.operator "onnx.Flatten"(%arg2) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[1,5],f32> + %26 = torch.operator "onnx.Add"(%24, %25) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[1,5],f32>) -> !torch.vtensor<[24,5],f32> + %27 = torch.operator "onnx.Reshape"(%26, %2) : (!torch.vtensor<[24,5],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,5],f32> + %28 = torch.operator "onnx.Reciprocal"(%19) : (!torch.vtensor<[24,1],f32>) -> !torch.vtensor<[24,1],f32> + %29 = torch.operator "onnx.Reshape"(%13, %9) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,4,1],f32> + %30 = torch.operator "onnx.Reshape"(%28, %9) : (!torch.vtensor<[24,1],f32>, !torch.vtensor<[?],si64>) -> !torch.vtensor<[2,3,4,1],f32> + return %27, %29, %30 : !torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[2,3,4,1],f32>, !torch.vtensor<[2,3,4,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/output_0.npy b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/output_0.npy new file mode 100644 index 000000000..8b062b767 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/output_1.npy b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/output_1.npy new file mode 100644 index 000000000..3277da12d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/output_2.npy b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/output_2.npy new file mode 100644 index 000000000..296f8e9fd Binary files /dev/null and b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/output_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/test_data_flags.txt b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/test_data_flags.txt new file mode 100644 index 000000000..6b51976e8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_layer_normalization_default_axis_expanded_ver18/test_data_flags.txt @@ -0,0 +1,6 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy +--expected_output=@output_2.npy diff --git a/iree_tests/onnx/node/generated/test_leakyrelu/model.mlir b/iree_tests/onnx/node/generated/test_leakyrelu/model.mlir index 429805209..41fa678e5 100644 --- a/iree_tests/onnx/node/generated/test_leakyrelu/model.mlir +++ b/iree_tests/onnx/node/generated/test_leakyrelu/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_leakyrelu(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LeakyRelu"(%arg0) {torch.onnx.alpha = 1.000000e-01 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LeakyRelu"(%arg0) {torch.onnx.alpha = 1.000000e-01 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_leakyrelu_default/model.mlir b/iree_tests/onnx/node/generated/test_leakyrelu_default/model.mlir index 4d4b7234e..b652c9942 100644 --- a/iree_tests/onnx/node/generated/test_leakyrelu_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_leakyrelu_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_leakyrelu_default(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LeakyRelu"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LeakyRelu"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_leakyrelu_default_expanded/model.mlir b/iree_tests/onnx/node/generated/test_leakyrelu_default_expanded/model.mlir index 2d3cc4af1..b388692f2 100644 --- a/iree_tests/onnx/node/generated/test_leakyrelu_default_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_leakyrelu_default_expanded/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_leakyrelu_default_expanded(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 0.00999999977 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.Less"(%arg0, %3) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> - %5 = torch.operator "onnx.Mul"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %6 = torch.operator "onnx.Where"(%4, %5, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 0.00999999977 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Less"(%arg0, %3) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> + %5 = torch.operator "onnx.Mul"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %6 = torch.operator "onnx.Where"(%4, %5, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %6 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_leakyrelu_example/model.mlir b/iree_tests/onnx/node/generated/test_leakyrelu_example/model.mlir index 9ff45bec7..b8afdd356 100644 --- a/iree_tests/onnx/node/generated/test_leakyrelu_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_leakyrelu_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_leakyrelu_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LeakyRelu"(%arg0) {torch.onnx.alpha = 1.000000e-01 : f32} : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LeakyRelu"(%arg0) {torch.onnx.alpha = 1.000000e-01 : f32} : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_leakyrelu_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_leakyrelu_example_expanded/model.mlir index 52af34e5e..6a6cc6658 100644 --- a/iree_tests/onnx/node/generated/test_leakyrelu_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_leakyrelu_example_expanded/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_leakyrelu_example_expanded(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.000000e-01 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.Less"(%arg0, %3) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],i1> - %5 = torch.operator "onnx.Mul"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %6 = torch.operator "onnx.Where"(%4, %5, %arg0) : (!torch.vtensor<[3],i1>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.000000e-01 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Less"(%arg0, %3) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],i1> + %5 = torch.operator "onnx.Mul"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %6 = torch.operator "onnx.Where"(%4, %5, %arg0) : (!torch.vtensor<[3],i1>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %6 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_leakyrelu_expanded/model.mlir b/iree_tests/onnx/node/generated/test_leakyrelu_expanded/model.mlir index 92804e008..e53e0025e 100644 --- a/iree_tests/onnx/node/generated/test_leakyrelu_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_leakyrelu_expanded/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_leakyrelu_expanded(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.000000e-01 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.Less"(%arg0, %3) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> - %5 = torch.operator "onnx.Mul"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %6 = torch.operator "onnx.Where"(%4, %5, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.000000e-01 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Less"(%arg0, %3) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> + %5 = torch.operator "onnx.Mul"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %6 = torch.operator "onnx.Where"(%4, %5, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %6 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_less/model.mlir b/iree_tests/onnx/node/generated/test_less/model.mlir index 4e1a31129..3dbf89077 100644 --- a/iree_tests/onnx/node/generated/test_less/model.mlir +++ b/iree_tests/onnx/node/generated/test_less/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_less(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_less_bcast/model.mlir b/iree_tests/onnx/node/generated/test_less_bcast/model.mlir index 5529eb646..806f29e85 100644 --- a/iree_tests/onnx/node/generated/test_less_bcast/model.mlir +++ b/iree_tests/onnx/node/generated/test_less_bcast/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_less_bcast(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_less_equal/model.mlir b/iree_tests/onnx/node/generated/test_less_equal/model.mlir index 1201d13a4..7a3b714ed 100644 --- a/iree_tests/onnx/node/generated/test_less_equal/model.mlir +++ b/iree_tests/onnx/node/generated/test_less_equal/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_less_equal(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LessOrEqual"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.LessOrEqual"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_less_equal_bcast/model.mlir b/iree_tests/onnx/node/generated/test_less_equal_bcast/model.mlir index 512cacf9d..742175ae9 100644 --- a/iree_tests/onnx/node/generated/test_less_equal_bcast/model.mlir +++ b/iree_tests/onnx/node/generated/test_less_equal_bcast/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_less_equal_bcast(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LessOrEqual"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.LessOrEqual"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_less_equal_bcast_expanded/model.mlir b/iree_tests/onnx/node/generated/test_less_equal_bcast_expanded/model.mlir index 169fcb0e4..5bdd8b3df 100644 --- a/iree_tests/onnx/node/generated/test_less_equal_bcast_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_less_equal_bcast_expanded/model.mlir @@ -1,8 +1,9 @@ module { func.func @test_less_equal_bcast_expanded(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> - %1 = torch.operator "onnx.Equal"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> - %2 = torch.operator "onnx.Or"(%0, %1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> + %1 = torch.operator "onnx.Equal"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],i1> + %2 = torch.operator "onnx.Or"(%0, %1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> return %2 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_less_equal_expanded/model.mlir b/iree_tests/onnx/node/generated/test_less_equal_expanded/model.mlir index 70b665f54..78b069b87 100644 --- a/iree_tests/onnx/node/generated/test_less_equal_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_less_equal_expanded/model.mlir @@ -1,8 +1,9 @@ module { func.func @test_less_equal_expanded(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> - %1 = torch.operator "onnx.Equal"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> - %2 = torch.operator "onnx.Or"(%0, %1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Less"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> + %1 = torch.operator "onnx.Equal"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> + %2 = torch.operator "onnx.Or"(%0, %1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> return %2 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_log/model.mlir b/iree_tests/onnx/node/generated/test_log/model.mlir index 7f6bff25a..f02616a3c 100644 --- a/iree_tests/onnx/node/generated/test_log/model.mlir +++ b/iree_tests/onnx/node/generated/test_log/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_log(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Log"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Log"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_log_example/model.mlir b/iree_tests/onnx/node/generated/test_log_example/model.mlir index 4a9f5c8e3..8e557039a 100644 --- a/iree_tests/onnx/node/generated/test_log_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_log_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_log_example(%arg0: !torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Log"(%arg0) : (!torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Log"(%arg0) : (!torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> return %0 : !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_axis_0/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_axis_0/model.mlir index 72f96cddb..2fce0a489 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_axis_0/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_axis_0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_logsoftmax_axis_0(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LogSoftmax"(%arg0) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LogSoftmax"(%arg0) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_axis_0_expanded/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_axis_0_expanded/model.mlir index 3d11b992c..06515d2c9 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_axis_0_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_axis_0_expanded/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_logsoftmax_axis_0_expanded(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [0 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1,4,5],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,4,5],f32> - %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[1,4,5],f32> - %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [0 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1,4,5],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,4,5],f32> + %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[1,4,5],f32> + %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %6 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_axis_0_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_axis_0_expanded_ver18/model.mlir index 1d4b1a575..7ca8f6aca 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_axis_0_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_axis_0_expanded_ver18/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_logsoftmax_axis_0_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,4,5],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,4,5],f32> - %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[1,4,5],f32> - %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,4,5],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,4,5],f32> + %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[1,4,5],f32> + %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %6 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_axis_1/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_axis_1/model.mlir index f67d8992a..ba33a2cea 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_axis_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_axis_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_logsoftmax_axis_1(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LogSoftmax"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LogSoftmax"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_axis_1_expanded/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_axis_1_expanded/model.mlir index 978f827e5..f2ca8d8b5 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_axis_1_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_axis_1_expanded/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_logsoftmax_axis_1_expanded(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,5],f32> - %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,5],f32> + %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %6 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_axis_1_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_axis_1_expanded_ver18/model.mlir index 8601a27a8..504cde92e 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_axis_1_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_axis_1_expanded_ver18/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_logsoftmax_axis_1_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,5],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,5],f32> - %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,5],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,5],f32> + %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %6 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_axis_2/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_axis_2/model.mlir index e28fe0ae5..5bfe49d8a 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_axis_2/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_axis_2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_logsoftmax_axis_2(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LogSoftmax"(%arg0) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LogSoftmax"(%arg0) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_axis_2_expanded/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_axis_2_expanded/model.mlir index 522529c12..d8d8f0b9b 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_axis_2_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_axis_2_expanded/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_logsoftmax_axis_2_expanded(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<2> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [2 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,1],f32> - %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [2 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,1],f32> + %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> return %6 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_axis_2_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_axis_2_expanded_ver18/model.mlir index fba32af6a..4430220da 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_axis_2_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_axis_2_expanded_ver18/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_logsoftmax_axis_2_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<2> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,1],f32> - %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,1],f32> + %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> return %6 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_default_axis/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_default_axis/model.mlir index bdc1ded0a..a302da0f4 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_default_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_default_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_logsoftmax_default_axis(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LogSoftmax"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LogSoftmax"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_default_axis_expanded/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_default_axis_expanded/model.mlir index 818f292e3..7a0f1730f 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_default_axis_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_default_axis_expanded/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_logsoftmax_default_axis_expanded(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [-1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,1],f32> - %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [-1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,1],f32> + %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> return %6 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_default_axis_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_default_axis_expanded_ver18/model.mlir index 2201bb529..62873f535 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_default_axis_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_default_axis_expanded_ver18/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_logsoftmax_default_axis_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,1],f32> - %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,1],f32> + %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> return %6 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_example_1/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_example_1/model.mlir index 037f0d02d..fd9ab81c8 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_example_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_example_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_logsoftmax_example_1(%arg0: !torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LogSoftmax"(%arg0) : (!torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LogSoftmax"(%arg0) : (!torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> return %0 : !torch.vtensor<[1,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_example_1_expanded/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_example_1_expanded/model.mlir index e4f9f1e61..db8d7dc1e 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_example_1_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_example_1_expanded/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_logsoftmax_example_1_expanded(%arg0: !torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [-1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,3],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> - %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> - %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [-1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,3],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,3],f32> return %6 : !torch.vtensor<[1,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_example_1_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_example_1_expanded_ver18/model.mlir index adbcf3d18..00a8e0105 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_example_1_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_example_1_expanded_ver18/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_logsoftmax_example_1_expanded_ver18(%arg0: !torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,3],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> - %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> - %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,3],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,1],f32> + %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,3],f32> return %6 : !torch.vtensor<[1,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_large_number/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_large_number/model.mlir index fe2fb4547..0166786a2 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_large_number/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_large_number/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_logsoftmax_large_number(%arg0: !torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LogSoftmax"(%arg0) : (!torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LogSoftmax"(%arg0) : (!torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> return %0 : !torch.vtensor<[2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_large_number_expanded/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_large_number_expanded/model.mlir index 53d01146b..9892f33ed 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_large_number_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_large_number_expanded/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_logsoftmax_large_number_expanded(%arg0: !torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [-1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,4],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> - %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> - %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [-1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,4],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> + %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,4],f32> return %6 : !torch.vtensor<[2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_large_number_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_large_number_expanded_ver18/model.mlir index e7a70c913..0e9604112 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_large_number_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_large_number_expanded_ver18/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_logsoftmax_large_number_expanded_ver18(%arg0: !torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,4],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> - %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> - %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,4],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> + %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,1],f32> + %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,4],f32> return %6 : !torch.vtensor<[2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_negative_axis/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_negative_axis/model.mlir index 66116acc1..fe2c57be9 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_negative_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_negative_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_logsoftmax_negative_axis(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LogSoftmax"(%arg0) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LogSoftmax"(%arg0) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_negative_axis_expanded/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_negative_axis_expanded/model.mlir index 94954ae76..0b929b447 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_negative_axis_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_negative_axis_expanded/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_logsoftmax_negative_axis_expanded(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [-1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,1],f32> - %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [-1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,1],f32> + %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> return %6 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_logsoftmax_negative_axis_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_logsoftmax_negative_axis_expanded_ver18/model.mlir index 217be908d..37c678e9b 100644 --- a/iree_tests/onnx/node/generated/test_logsoftmax_negative_axis_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_logsoftmax_negative_axis_expanded_ver18/model.mlir @@ -1,12 +1,13 @@ module { func.func @test_logsoftmax_negative_axis_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,1],f32> - %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %5 = torch.operator "onnx.Log"(%4) : (!torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,1],f32> + %6 = torch.operator "onnx.Sub"(%2, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> return %6 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_loop11/input_0.npy b/iree_tests/onnx/node/generated/test_loop11/input_0.npy new file mode 100644 index 000000000..ee2adbb4b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_loop11/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_loop11/input_1.npy b/iree_tests/onnx/node/generated/test_loop11/input_1.npy new file mode 100644 index 000000000..0917fd2fe Binary files /dev/null and b/iree_tests/onnx/node/generated/test_loop11/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_loop11/input_2.npy b/iree_tests/onnx/node/generated/test_loop11/input_2.npy new file mode 100644 index 000000000..67cb54127 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_loop11/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_loop11/model.mlir b/iree_tests/onnx/node/generated/test_loop11/model.mlir new file mode 100644 index 000000000..91f834771 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_loop11/model.mlir @@ -0,0 +1,20 @@ +module { + func.func @test_loop11(%arg0: !torch.vtensor<[],si64>, %arg1: !torch.vtensor<[],i1>, %arg2: !torch.vtensor<[1],f32>) -> (!torch.vtensor<[1],f32>, !torch.vtensor<[5,1],f32>) attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.Loop"(%arg0, %arg1, %arg2) : (!torch.vtensor<[],si64>, !torch.vtensor<[],i1>, !torch.vtensor<[1],f32>) -> (!torch.vtensor<[1],f32>, !torch.vtensor<[5,1],f32>) { + ^bb0(%arg3: !torch.vtensor<[],si64>, %arg4: !torch.vtensor<[],i1>, %arg5: !torch.vtensor<[1],f32>): + %1 = torch.operator "onnx.Identity"(%arg4) : (!torch.vtensor<[],i1>) -> !torch.vtensor<[],i1> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00, 5.000000e+00]> : tensor<5xf32>} : () -> !torch.vtensor<[5],f32> + %3 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor} : () -> !torch.vtensor<[],si64> + %4 = torch.operator "onnx.Add"(%arg3, %3) : (!torch.vtensor<[],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[],si64> + %5 = torch.operator "onnx.Unsqueeze"(%arg3) {torch.onnx.axes = [0 : si64]} : (!torch.vtensor<[],si64>) -> !torch.vtensor<[1],si64> + %6 = torch.operator "onnx.Unsqueeze"(%4) {torch.onnx.axes = [0 : si64]} : (!torch.vtensor<[],si64>) -> !torch.vtensor<[1],si64> + %7 = torch.operator "onnx.Slice"(%2, %5, %6) : (!torch.vtensor<[5],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[?],f32> + %8 = torch.operator "onnx.Add"(%arg5, %7) : (!torch.vtensor<[1],f32>, !torch.vtensor<[?],f32>) -> !torch.vtensor<[1],f32> + %9 = torch.operator "onnx.Identity"(%8) : (!torch.vtensor<[1],f32>) -> !torch.vtensor<[1],f32> + torch.operator_terminator %1, %8, %9 : !torch.vtensor<[],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32> + } + return %0#0, %0#1 : !torch.vtensor<[1],f32>, !torch.vtensor<[5,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_loop11/output_0.npy b/iree_tests/onnx/node/generated/test_loop11/output_0.npy new file mode 100644 index 000000000..b4d7b0f03 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_loop11/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_loop11/output_1.npy b/iree_tests/onnx/node/generated/test_loop11/output_1.npy new file mode 100644 index 000000000..c73b7d9c4 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_loop11/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_loop11/test_data_flags.txt b/iree_tests/onnx/node/generated/test_loop11/test_data_flags.txt new file mode 100644 index 000000000..7336c6314 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_loop11/test_data_flags.txt @@ -0,0 +1,5 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy diff --git a/iree_tests/onnx/node/generated/test_lppool_1d_default/model.mlir b/iree_tests/onnx/node/generated/test_lppool_1d_default/model.mlir index 2e819e4d4..7483f4357 100644 --- a/iree_tests/onnx/node/generated/test_lppool_1d_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_lppool_1d_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_lppool_1d_default(%arg0: !torch.vtensor<[1,3,32],f32>) -> !torch.vtensor<[1,3,31],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LpPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64], torch.onnx.p = 3 : si64, torch.onnx.strides = [1 : si64]} : (!torch.vtensor<[1,3,32],f32>) -> !torch.vtensor<[1,3,31],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LpPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64], torch.onnx.p = 3 : si64, torch.onnx.strides = [1 : si64]} : (!torch.vtensor<[1,3,32],f32>) -> !torch.vtensor<[1,3,31],f32> return %0 : !torch.vtensor<[1,3,31],f32> } } diff --git a/iree_tests/onnx/node/generated/test_lppool_2d_default/model.mlir b/iree_tests/onnx/node/generated/test_lppool_2d_default/model.mlir index 544e41af1..d9f1f7523 100644 --- a/iree_tests/onnx/node/generated/test_lppool_2d_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_lppool_2d_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_lppool_2d_default(%arg0: !torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,31,31],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LpPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.p = 4 : si64} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,31,31],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LpPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.p = 4 : si64} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,31,31],f32> return %0 : !torch.vtensor<[1,3,31,31],f32> } } diff --git a/iree_tests/onnx/node/generated/test_lppool_2d_dilations/model.mlir b/iree_tests/onnx/node/generated/test_lppool_2d_dilations/model.mlir index 5b5b038bb..38531256b 100644 --- a/iree_tests/onnx/node/generated/test_lppool_2d_dilations/model.mlir +++ b/iree_tests/onnx/node/generated/test_lppool_2d_dilations/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_lppool_2d_dilations(%arg0: !torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LpPool"(%arg0) {torch.onnx.dilations = [2 : si64, 2 : si64], torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.p = 2 : si64, torch.onnx.strides = [1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LpPool"(%arg0) {torch.onnx.dilations = [2 : si64, 2 : si64], torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.p = 2 : si64, torch.onnx.strides = [1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> return %0 : !torch.vtensor<[1,1,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_lppool_2d_pads/model.mlir b/iree_tests/onnx/node/generated/test_lppool_2d_pads/model.mlir index ec016ab17..fe836d66e 100644 --- a/iree_tests/onnx/node/generated/test_lppool_2d_pads/model.mlir +++ b/iree_tests/onnx/node/generated/test_lppool_2d_pads/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_lppool_2d_pads(%arg0: !torch.vtensor<[1,3,28,28],f32>) -> !torch.vtensor<[1,3,30,30],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LpPool"(%arg0) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.p = 3 : si64, torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,28,28],f32>) -> !torch.vtensor<[1,3,30,30],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LpPool"(%arg0) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.p = 3 : si64, torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,28,28],f32>) -> !torch.vtensor<[1,3,30,30],f32> return %0 : !torch.vtensor<[1,3,30,30],f32> } } diff --git a/iree_tests/onnx/node/generated/test_lppool_2d_same_lower/model.mlir b/iree_tests/onnx/node/generated/test_lppool_2d_same_lower/model.mlir index cfd88dffc..43f7e65d5 100644 --- a/iree_tests/onnx/node/generated/test_lppool_2d_same_lower/model.mlir +++ b/iree_tests/onnx/node/generated/test_lppool_2d_same_lower/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_lppool_2d_same_lower(%arg0: !torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LpPool"(%arg0) {torch.onnx.auto_pad = "SAME_LOWER", torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.p = 4 : si64} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LpPool"(%arg0) {torch.onnx.auto_pad = "SAME_LOWER", torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.p = 4 : si64} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> return %0 : !torch.vtensor<[1,3,32,32],f32> } } diff --git a/iree_tests/onnx/node/generated/test_lppool_2d_same_upper/model.mlir b/iree_tests/onnx/node/generated/test_lppool_2d_same_upper/model.mlir index 11e4c4a35..123d5757d 100644 --- a/iree_tests/onnx/node/generated/test_lppool_2d_same_upper/model.mlir +++ b/iree_tests/onnx/node/generated/test_lppool_2d_same_upper/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_lppool_2d_same_upper(%arg0: !torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LpPool"(%arg0) {torch.onnx.auto_pad = "SAME_UPPER", torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.p = 2 : si64} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LpPool"(%arg0) {torch.onnx.auto_pad = "SAME_UPPER", torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.p = 2 : si64} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> return %0 : !torch.vtensor<[1,3,32,32],f32> } } diff --git a/iree_tests/onnx/node/generated/test_lppool_2d_strides/model.mlir b/iree_tests/onnx/node/generated/test_lppool_2d_strides/model.mlir index f048c358f..4ff1d52eb 100644 --- a/iree_tests/onnx/node/generated/test_lppool_2d_strides/model.mlir +++ b/iree_tests/onnx/node/generated/test_lppool_2d_strides/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_lppool_2d_strides(%arg0: !torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,10,10],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LpPool"(%arg0) {torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.p = 2 : si64, torch.onnx.strides = [3 : si64, 3 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,10,10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LpPool"(%arg0) {torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.p = 2 : si64, torch.onnx.strides = [3 : si64, 3 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,10,10],f32> return %0 : !torch.vtensor<[1,3,10,10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_lppool_3d_default/model.mlir b/iree_tests/onnx/node/generated/test_lppool_3d_default/model.mlir index 0387b953d..186db484a 100644 --- a/iree_tests/onnx/node/generated/test_lppool_3d_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_lppool_3d_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_lppool_3d_default(%arg0: !torch.vtensor<[1,3,32,32,32],f32>) -> !torch.vtensor<[1,3,31,31,31],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LpPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64, 2 : si64], torch.onnx.p = 3 : si64} : (!torch.vtensor<[1,3,32,32,32],f32>) -> !torch.vtensor<[1,3,31,31,31],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LpPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64, 2 : si64], torch.onnx.p = 3 : si64} : (!torch.vtensor<[1,3,32,32,32],f32>) -> !torch.vtensor<[1,3,31,31,31],f32> return %0 : !torch.vtensor<[1,3,31,31,31],f32> } } diff --git a/iree_tests/onnx/node/generated/test_lrn/model.mlir b/iree_tests/onnx/node/generated/test_lrn/model.mlir index 9422e3337..2ef117b1a 100644 --- a/iree_tests/onnx/node/generated/test_lrn/model.mlir +++ b/iree_tests/onnx/node/generated/test_lrn/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_lrn(%arg0: !torch.vtensor<[5,5,5,5],f32>) -> !torch.vtensor<[5,5,5,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LRN"(%arg0) {torch.onnx.alpha = 2.000000e-04 : f32, torch.onnx.beta = 5.000000e-01 : f32, torch.onnx.bias = 2.000000e+00 : f32, torch.onnx.size = 3 : si64} : (!torch.vtensor<[5,5,5,5],f32>) -> !torch.vtensor<[5,5,5,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LRN"(%arg0) {torch.onnx.alpha = 2.000000e-04 : f32, torch.onnx.beta = 5.000000e-01 : f32, torch.onnx.bias = 2.000000e+00 : f32, torch.onnx.size = 3 : si64} : (!torch.vtensor<[5,5,5,5],f32>) -> !torch.vtensor<[5,5,5,5],f32> return %0 : !torch.vtensor<[5,5,5,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_lrn_default/model.mlir b/iree_tests/onnx/node/generated/test_lrn_default/model.mlir index 6b6edade7..9a9d0d7e7 100644 --- a/iree_tests/onnx/node/generated/test_lrn_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_lrn_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_lrn_default(%arg0: !torch.vtensor<[5,5,5,5],f32>) -> !torch.vtensor<[5,5,5,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.LRN"(%arg0) {torch.onnx.size = 3 : si64} : (!torch.vtensor<[5,5,5,5],f32>) -> !torch.vtensor<[5,5,5,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.LRN"(%arg0) {torch.onnx.size = 3 : si64} : (!torch.vtensor<[5,5,5,5],f32>) -> !torch.vtensor<[5,5,5,5],f32> return %0 : !torch.vtensor<[5,5,5,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_lstm_batchwise/model.mlir b/iree_tests/onnx/node/generated/test_lstm_batchwise/model.mlir index 7f43cacdc..c8eced758 100644 --- a/iree_tests/onnx/node/generated/test_lstm_batchwise/model.mlir +++ b/iree_tests/onnx/node/generated/test_lstm_batchwise/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_lstm_batchwise(%arg0: !torch.vtensor<[3,1,2],f32>, %arg1: !torch.vtensor<[1,28,2],f32>, %arg2: !torch.vtensor<[1,28,7],f32>) -> (!torch.vtensor<[3,1,1,7],f32>, !torch.vtensor<[3,1,7],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.LSTM"(%arg0, %arg1, %arg2) {torch.onnx.hidden_size = 7 : si64, torch.onnx.layout = 1 : si64} : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1,28,2],f32>, !torch.vtensor<[1,28,7],f32>) -> (!torch.vtensor<[3,1,1,7],f32>, !torch.vtensor<[3,1,7],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.LSTM"(%arg0, %arg1, %arg2) {torch.onnx.hidden_size = 7 : si64, torch.onnx.layout = 1 : si64} : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1,28,2],f32>, !torch.vtensor<[1,28,7],f32>) -> (!torch.vtensor<[3,1,1,7],f32>, !torch.vtensor<[3,1,7],f32>) return %0#0, %0#1 : !torch.vtensor<[3,1,1,7],f32>, !torch.vtensor<[3,1,7],f32> } } diff --git a/iree_tests/onnx/node/generated/test_lstm_defaults/input_0.npy b/iree_tests/onnx/node/generated/test_lstm_defaults/input_0.npy new file mode 100644 index 000000000..05b4233c9 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_defaults/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_defaults/input_1.npy b/iree_tests/onnx/node/generated/test_lstm_defaults/input_1.npy new file mode 100644 index 000000000..ca468ca20 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_defaults/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_defaults/input_2.npy b/iree_tests/onnx/node/generated/test_lstm_defaults/input_2.npy new file mode 100644 index 000000000..02a9f2601 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_defaults/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_defaults/model.mlir b/iree_tests/onnx/node/generated/test_lstm_defaults/model.mlir new file mode 100644 index 000000000..7754393c3 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_lstm_defaults/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_lstm_defaults(%arg0: !torch.vtensor<[1,3,2],f32>, %arg1: !torch.vtensor<[1,12,2],f32>, %arg2: !torch.vtensor<[1,12,3],f32>) -> !torch.vtensor<[1,3,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.LSTM"(%arg0, %arg1, %arg2) {torch.onnx.hidden_size = 3 : si64} : (!torch.vtensor<[1,3,2],f32>, !torch.vtensor<[1,12,2],f32>, !torch.vtensor<[1,12,3],f32>) -> (!torch.none, !torch.vtensor<[1,3,3],f32>) + return %0#1 : !torch.vtensor<[1,3,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_lstm_defaults/output_0.npy b/iree_tests/onnx/node/generated/test_lstm_defaults/output_0.npy new file mode 100644 index 000000000..9b928c37f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_defaults/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_defaults/test_data_flags.txt b/iree_tests/onnx/node/generated/test_lstm_defaults/test_data_flags.txt new file mode 100644 index 000000000..cb3b7ab77 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_lstm_defaults/test_data_flags.txt @@ -0,0 +1,4 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/input_0.npy b/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/input_0.npy new file mode 100644 index 000000000..b91e0ac1b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/input_1.npy b/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/input_1.npy new file mode 100644 index 000000000..19a1a6254 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/input_2.npy b/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/input_2.npy new file mode 100644 index 000000000..440c8f43e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/input_3.npy b/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/input_3.npy new file mode 100644 index 000000000..402fb4321 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/input_3.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/model.mlir b/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/model.mlir new file mode 100644 index 000000000..170e63154 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_lstm_with_initial_bias(%arg0: !torch.vtensor<[1,3,3],f32>, %arg1: !torch.vtensor<[1,16,3],f32>, %arg2: !torch.vtensor<[1,16,4],f32>, %arg3: !torch.vtensor<[1,32],f32>) -> !torch.vtensor<[1,3,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.LSTM"(%arg0, %arg1, %arg2, %arg3) {torch.onnx.hidden_size = 4 : si64} : (!torch.vtensor<[1,3,3],f32>, !torch.vtensor<[1,16,3],f32>, !torch.vtensor<[1,16,4],f32>, !torch.vtensor<[1,32],f32>) -> (!torch.none, !torch.vtensor<[1,3,4],f32>) + return %0#1 : !torch.vtensor<[1,3,4],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/output_0.npy b/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/output_0.npy new file mode 100644 index 000000000..ca2d468e1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/test_data_flags.txt b/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/test_data_flags.txt new file mode 100644 index 000000000..fad7bbb82 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_lstm_with_initial_bias/test_data_flags.txt @@ -0,0 +1,5 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--input=@input_3.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_0.npy b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_0.npy new file mode 100644 index 000000000..2078f9ab2 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_1.npy b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_1.npy new file mode 100644 index 000000000..0e5c02606 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_2.npy b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_2.npy new file mode 100644 index 000000000..02a9f2601 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_3.npy b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_3.npy new file mode 100644 index 000000000..a2815f322 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_3.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_4.npy b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_4.npy new file mode 100644 index 000000000..74e646539 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_4.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_5.npy b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_5.npy new file mode 100644 index 000000000..9200c3d05 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_5.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_6.npy b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_6.npy new file mode 100644 index 000000000..9200c3d05 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_6.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_7.npy b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_7.npy new file mode 100644 index 000000000..a4e5a046c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/input_7.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_with_peepholes/model.mlir b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/model.mlir new file mode 100644 index 000000000..86447de13 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_lstm_with_peepholes(%arg0: !torch.vtensor<[1,2,4],f32>, %arg1: !torch.vtensor<[1,12,4],f32>, %arg2: !torch.vtensor<[1,12,3],f32>, %arg3: !torch.vtensor<[1,24],f32>, %arg4: !torch.vtensor<[2],si32>, %arg5: !torch.vtensor<[1,2,3],f32>, %arg6: !torch.vtensor<[1,2,3],f32>, %arg7: !torch.vtensor<[1,9],f32>) -> !torch.vtensor<[1,2,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.LSTM"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) {torch.onnx.hidden_size = 3 : si64} : (!torch.vtensor<[1,2,4],f32>, !torch.vtensor<[1,12,4],f32>, !torch.vtensor<[1,12,3],f32>, !torch.vtensor<[1,24],f32>, !torch.vtensor<[2],si32>, !torch.vtensor<[1,2,3],f32>, !torch.vtensor<[1,2,3],f32>, !torch.vtensor<[1,9],f32>) -> (!torch.none, !torch.vtensor<[1,2,3],f32>) + return %0#1 : !torch.vtensor<[1,2,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_lstm_with_peepholes/output_0.npy b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/output_0.npy new file mode 100644 index 000000000..543e5c659 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_lstm_with_peepholes/test_data_flags.txt b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/test_data_flags.txt new file mode 100644 index 000000000..7d838da1c --- /dev/null +++ b/iree_tests/onnx/node/generated/test_lstm_with_peepholes/test_data_flags.txt @@ -0,0 +1,9 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--input=@input_3.npy +--input=@input_4.npy +--input=@input_5.npy +--input=@input_6.npy +--input=@input_7.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_matmul_2d/model.mlir b/iree_tests/onnx/node/generated/test_matmul_2d/model.mlir index 8cbf06dc5..36a62ac8e 100644 --- a/iree_tests/onnx/node/generated/test_matmul_2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_matmul_2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_matmul_2d(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[4,3],f32>) -> !torch.vtensor<[3,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MatMul"(%arg0, %arg1) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[4,3],f32>) -> !torch.vtensor<[3,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MatMul"(%arg0, %arg1) : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[4,3],f32>) -> !torch.vtensor<[3,3],f32> return %0 : !torch.vtensor<[3,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_matmul_3d/model.mlir b/iree_tests/onnx/node/generated/test_matmul_3d/model.mlir index df90c3a53..7a34c0a90 100644 --- a/iree_tests/onnx/node/generated/test_matmul_3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_matmul_3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_matmul_3d(%arg0: !torch.vtensor<[2,3,4],f32>, %arg1: !torch.vtensor<[2,4,3],f32>) -> !torch.vtensor<[2,3,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MatMul"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[2,4,3],f32>) -> !torch.vtensor<[2,3,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MatMul"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[2,4,3],f32>) -> !torch.vtensor<[2,3,3],f32> return %0 : !torch.vtensor<[2,3,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_matmul_4d/model.mlir b/iree_tests/onnx/node/generated/test_matmul_4d/model.mlir index a077c8c4e..4bcca465d 100644 --- a/iree_tests/onnx/node/generated/test_matmul_4d/model.mlir +++ b/iree_tests/onnx/node/generated/test_matmul_4d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_matmul_4d(%arg0: !torch.vtensor<[1,2,3,4],f32>, %arg1: !torch.vtensor<[1,2,4,3],f32>) -> !torch.vtensor<[1,2,3,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MatMul"(%arg0, %arg1) : (!torch.vtensor<[1,2,3,4],f32>, !torch.vtensor<[1,2,4,3],f32>) -> !torch.vtensor<[1,2,3,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MatMul"(%arg0, %arg1) : (!torch.vtensor<[1,2,3,4],f32>, !torch.vtensor<[1,2,4,3],f32>) -> !torch.vtensor<[1,2,3,3],f32> return %0 : !torch.vtensor<[1,2,3,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_matmulinteger/model.mlir b/iree_tests/onnx/node/generated/test_matmulinteger/model.mlir index 61ba99b58..5e440b536 100644 --- a/iree_tests/onnx/node/generated/test_matmulinteger/model.mlir +++ b/iree_tests/onnx/node/generated/test_matmulinteger/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_matmulinteger(%arg0: !torch.vtensor<[4,3],ui8>, %arg1: !torch.vtensor<[3,2],ui8>, %arg2: !torch.vtensor<[1],ui8>, %arg3: !torch.vtensor<[1],ui8>) -> !torch.vtensor<[4,2],si32> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MatMulInteger"(%arg0, %arg1, %arg2, %arg3) : (!torch.vtensor<[4,3],ui8>, !torch.vtensor<[3,2],ui8>, !torch.vtensor<[1],ui8>, !torch.vtensor<[1],ui8>) -> !torch.vtensor<[4,2],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.MatMulInteger"(%arg0, %arg1, %arg2, %arg3) : (!torch.vtensor<[4,3],ui8>, !torch.vtensor<[3,2],ui8>, !torch.vtensor<[1],ui8>, !torch.vtensor<[1],ui8>) -> !torch.vtensor<[4,2],si32> return %0 : !torch.vtensor<[4,2],si32> } } diff --git a/iree_tests/onnx/node/generated/test_max_example/model.mlir b/iree_tests/onnx/node/generated/test_max_example/model.mlir index e77a61043..a9408739b 100644 --- a/iree_tests/onnx/node/generated/test_max_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_max_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_max_example(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],f32>, %arg2: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Max"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Max"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_max_float16/model.mlir b/iree_tests/onnx/node/generated/test_max_float16/model.mlir index 796691127..129b3f080 100644 --- a/iree_tests/onnx/node/generated/test_max_float16/model.mlir +++ b/iree_tests/onnx/node/generated/test_max_float16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_max_float16(%arg0: !torch.vtensor<[3],f16>, %arg1: !torch.vtensor<[3],f16>) -> !torch.vtensor<[3],f16> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],f16>, !torch.vtensor<[3],f16>) -> !torch.vtensor<[3],f16> + %none = torch.constant.none + %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],f16>, !torch.vtensor<[3],f16>) -> !torch.vtensor<[3],f16> return %0 : !torch.vtensor<[3],f16> } } diff --git a/iree_tests/onnx/node/generated/test_max_float32/model.mlir b/iree_tests/onnx/node/generated/test_max_float32/model.mlir index 761520ec0..9decf58e5 100644 --- a/iree_tests/onnx/node/generated/test_max_float32/model.mlir +++ b/iree_tests/onnx/node/generated/test_max_float32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_max_float32(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_max_float64/model.mlir b/iree_tests/onnx/node/generated/test_max_float64/model.mlir index 1fbf9b5ae..569f60743 100644 --- a/iree_tests/onnx/node/generated/test_max_float64/model.mlir +++ b/iree_tests/onnx/node/generated/test_max_float64/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_max_float64(%arg0: !torch.vtensor<[3],f64>, %arg1: !torch.vtensor<[3],f64>) -> !torch.vtensor<[3],f64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],f64>, !torch.vtensor<[3],f64>) -> !torch.vtensor<[3],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],f64>, !torch.vtensor<[3],f64>) -> !torch.vtensor<[3],f64> return %0 : !torch.vtensor<[3],f64> } } diff --git a/iree_tests/onnx/node/generated/test_max_int16/model.mlir b/iree_tests/onnx/node/generated/test_max_int16/model.mlir index 5c3a8c646..4ee89c9a0 100644 --- a/iree_tests/onnx/node/generated/test_max_int16/model.mlir +++ b/iree_tests/onnx/node/generated/test_max_int16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_max_int16(%arg0: !torch.vtensor<[3],si16>, %arg1: !torch.vtensor<[3],si16>) -> !torch.vtensor<[3],si16> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],si16>, !torch.vtensor<[3],si16>) -> !torch.vtensor<[3],si16> + %none = torch.constant.none + %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],si16>, !torch.vtensor<[3],si16>) -> !torch.vtensor<[3],si16> return %0 : !torch.vtensor<[3],si16> } } diff --git a/iree_tests/onnx/node/generated/test_max_int32/model.mlir b/iree_tests/onnx/node/generated/test_max_int32/model.mlir index f30da599d..35df1ed2a 100644 --- a/iree_tests/onnx/node/generated/test_max_int32/model.mlir +++ b/iree_tests/onnx/node/generated/test_max_int32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_max_int32(%arg0: !torch.vtensor<[3],si32>, %arg1: !torch.vtensor<[3],si32>) -> !torch.vtensor<[3],si32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],si32>, !torch.vtensor<[3],si32>) -> !torch.vtensor<[3],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],si32>, !torch.vtensor<[3],si32>) -> !torch.vtensor<[3],si32> return %0 : !torch.vtensor<[3],si32> } } diff --git a/iree_tests/onnx/node/generated/test_max_int64/model.mlir b/iree_tests/onnx/node/generated/test_max_int64/model.mlir index a85815c24..6e9abe49c 100644 --- a/iree_tests/onnx/node/generated/test_max_int64/model.mlir +++ b/iree_tests/onnx/node/generated/test_max_int64/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_max_int64(%arg0: !torch.vtensor<[3],si64>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> return %0 : !torch.vtensor<[3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_max_int8/model.mlir b/iree_tests/onnx/node/generated/test_max_int8/model.mlir index bba01f194..75ac35358 100644 --- a/iree_tests/onnx/node/generated/test_max_int8/model.mlir +++ b/iree_tests/onnx/node/generated/test_max_int8/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_max_int8(%arg0: !torch.vtensor<[3],si8>, %arg1: !torch.vtensor<[3],si8>) -> !torch.vtensor<[3],si8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],si8>, !torch.vtensor<[3],si8>) -> !torch.vtensor<[3],si8> + %none = torch.constant.none + %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],si8>, !torch.vtensor<[3],si8>) -> !torch.vtensor<[3],si8> return %0 : !torch.vtensor<[3],si8> } } diff --git a/iree_tests/onnx/node/generated/test_max_one_input/model.mlir b/iree_tests/onnx/node/generated/test_max_one_input/model.mlir index c0891ad6c..5933c708d 100644 --- a/iree_tests/onnx/node/generated/test_max_one_input/model.mlir +++ b/iree_tests/onnx/node/generated/test_max_one_input/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_max_one_input(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Max"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Max"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_max_two_inputs/model.mlir b/iree_tests/onnx/node/generated/test_max_two_inputs/model.mlir index 89134ba7b..454e43eda 100644 --- a/iree_tests/onnx/node/generated/test_max_two_inputs/model.mlir +++ b/iree_tests/onnx/node/generated/test_max_two_inputs/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_max_two_inputs(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_max_uint16/model.mlir b/iree_tests/onnx/node/generated/test_max_uint16/model.mlir index 94fb17b5b..946ca999c 100644 --- a/iree_tests/onnx/node/generated/test_max_uint16/model.mlir +++ b/iree_tests/onnx/node/generated/test_max_uint16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_max_uint16(%arg0: !torch.vtensor<[3],ui16>, %arg1: !torch.vtensor<[3],ui16>) -> !torch.vtensor<[3],ui16> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],ui16>, !torch.vtensor<[3],ui16>) -> !torch.vtensor<[3],ui16> + %none = torch.constant.none + %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],ui16>, !torch.vtensor<[3],ui16>) -> !torch.vtensor<[3],ui16> return %0 : !torch.vtensor<[3],ui16> } } diff --git a/iree_tests/onnx/node/generated/test_max_uint32/model.mlir b/iree_tests/onnx/node/generated/test_max_uint32/model.mlir index dda4973a4..9cf24d148 100644 --- a/iree_tests/onnx/node/generated/test_max_uint32/model.mlir +++ b/iree_tests/onnx/node/generated/test_max_uint32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_max_uint32(%arg0: !torch.vtensor<[3],ui32>, %arg1: !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],ui32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],ui32>, !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],ui32> + %none = torch.constant.none + %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],ui32>, !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],ui32> return %0 : !torch.vtensor<[3],ui32> } } diff --git a/iree_tests/onnx/node/generated/test_max_uint64/model.mlir b/iree_tests/onnx/node/generated/test_max_uint64/model.mlir index 3fb0a4549..1455c2712 100644 --- a/iree_tests/onnx/node/generated/test_max_uint64/model.mlir +++ b/iree_tests/onnx/node/generated/test_max_uint64/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_max_uint64(%arg0: !torch.vtensor<[3],ui64>, %arg1: !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],ui64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],ui64>, !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],ui64> + %none = torch.constant.none + %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],ui64>, !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],ui64> return %0 : !torch.vtensor<[3],ui64> } } diff --git a/iree_tests/onnx/node/generated/test_max_uint8/model.mlir b/iree_tests/onnx/node/generated/test_max_uint8/model.mlir index d69cedf05..21413b040 100644 --- a/iree_tests/onnx/node/generated/test_max_uint8/model.mlir +++ b/iree_tests/onnx/node/generated/test_max_uint8/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_max_uint8(%arg0: !torch.vtensor<[3],ui8>, %arg1: !torch.vtensor<[3],ui8>) -> !torch.vtensor<[3],ui8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],ui8>, !torch.vtensor<[3],ui8>) -> !torch.vtensor<[3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.Max"(%arg0, %arg1) : (!torch.vtensor<[3],ui8>, !torch.vtensor<[3],ui8>) -> !torch.vtensor<[3],ui8> return %0 : !torch.vtensor<[3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_1d_default/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_1d_default/model.mlir index 1949df158..54789c5b6 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_1d_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_1d_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_1d_default(%arg0: !torch.vtensor<[1,3,32],f32>) -> !torch.vtensor<[1,3,31],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64]} : (!torch.vtensor<[1,3,32],f32>) -> !torch.vtensor<[1,3,31],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64]} : (!torch.vtensor<[1,3,32],f32>) -> !torch.vtensor<[1,3,31],f32> return %0 : !torch.vtensor<[1,3,31],f32> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_2d_ceil/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_2d_ceil/model.mlir index 40f161b75..eb4e9bf38 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_2d_ceil/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_2d_ceil/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_2d_ceil(%arg0: !torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.ceil_mode = 1 : si64, torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.ceil_mode = 1 : si64, torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> return %0 : !torch.vtensor<[1,1,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_2d_default/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_2d_default/model.mlir index 8afe0a56a..73cec36f9 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_2d_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_2d_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_2d_default(%arg0: !torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,31,31],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,31,31],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,31,31],f32> return %0 : !torch.vtensor<[1,3,31,31],f32> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_2d_dilations/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_2d_dilations/model.mlir index 553e9f0c5..720bbdb11 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_2d_dilations/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_2d_dilations/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_2d_dilations(%arg0: !torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.dilations = [2 : si64, 2 : si64], torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.strides = [1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.dilations = [2 : si64, 2 : si64], torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.strides = [1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,4,4],f32>) -> !torch.vtensor<[1,1,2,2],f32> return %0 : !torch.vtensor<[1,1,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_2d_pads/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_2d_pads/model.mlir index 7d6f80c42..127595c84 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_2d_pads/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_2d_pads/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_2d_pads(%arg0: !torch.vtensor<[1,3,28,28],f32>) -> !torch.vtensor<[1,3,30,30],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,28,28],f32>) -> !torch.vtensor<[1,3,30,30],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,28,28],f32>) -> !torch.vtensor<[1,3,30,30],f32> return %0 : !torch.vtensor<[1,3,30,30],f32> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_2d_precomputed_pads/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_2d_precomputed_pads/model.mlir index 44d4f0900..d2ec889e7 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_2d_precomputed_pads/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_2d_precomputed_pads/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_2d_precomputed_pads(%arg0: !torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,5,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,5,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,5,5],f32> return %0 : !torch.vtensor<[1,1,5,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_2d_precomputed_same_upper/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_2d_precomputed_same_upper/model.mlir index b7f73e698..a808522be 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_2d_precomputed_same_upper/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_2d_precomputed_same_upper/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_2d_precomputed_same_upper(%arg0: !torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,3,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.auto_pad = "SAME_UPPER", torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,3,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.auto_pad = "SAME_UPPER", torch.onnx.kernel_shape = [3 : si64, 3 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,3,3],f32> return %0 : !torch.vtensor<[1,1,3,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_2d_precomputed_strides/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_2d_precomputed_strides/model.mlir index 93651f173..63fbefd53 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_2d_precomputed_strides/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_2d_precomputed_strides/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_2d_precomputed_strides(%arg0: !torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,2,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> !torch.vtensor<[1,1,2,2],f32> return %0 : !torch.vtensor<[1,1,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_2d_same_lower/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_2d_same_lower/model.mlir index 4b6fac357..a523570aa 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_2d_same_lower/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_2d_same_lower/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_2d_same_lower(%arg0: !torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.auto_pad = "SAME_LOWER", torch.onnx.kernel_shape = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.auto_pad = "SAME_LOWER", torch.onnx.kernel_shape = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> return %0 : !torch.vtensor<[1,3,32,32],f32> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_2d_same_upper/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_2d_same_upper/model.mlir index 503120690..f4ad24f6e 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_2d_same_upper/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_2d_same_upper/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_2d_same_upper(%arg0: !torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.auto_pad = "SAME_UPPER", torch.onnx.kernel_shape = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.auto_pad = "SAME_UPPER", torch.onnx.kernel_shape = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,32,32],f32> return %0 : !torch.vtensor<[1,3,32,32],f32> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_2d_strides/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_2d_strides/model.mlir index e887d4a09..0cf937499 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_2d_strides/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_2d_strides/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_2d_strides(%arg0: !torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,10,10],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.strides = [3 : si64, 3 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,10,10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.strides = [3 : si64, 3 : si64]} : (!torch.vtensor<[1,3,32,32],f32>) -> !torch.vtensor<[1,3,10,10],f32> return %0 : !torch.vtensor<[1,3,10,10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_2d_uint8/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_2d_uint8/model.mlir index 6ff842517..3a2ff000c 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_2d_uint8/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_2d_uint8/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_2d_uint8(%arg0: !torch.vtensor<[1,1,5,5],ui8>) -> !torch.vtensor<[1,1,5,5],ui8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],ui8>) -> !torch.vtensor<[1,1,5,5],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],ui8>) -> !torch.vtensor<[1,1,5,5],ui8> return %0 : !torch.vtensor<[1,1,5,5],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_3d_default/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_3d_default/model.mlir index bffc3bc80..cb6fe9b99 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_3d_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_3d_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_3d_default(%arg0: !torch.vtensor<[1,3,32,32,32],f32>) -> !torch.vtensor<[1,3,31,31,31],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32,32],f32>) -> !torch.vtensor<[1,3,31,31,31],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,3,32,32,32],f32>) -> !torch.vtensor<[1,3,31,31,31],f32> return %0 : !torch.vtensor<[1,3,31,31,31],f32> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_3d_dilations/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_3d_dilations/model.mlir index 125b8a087..5b24a5e8d 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_3d_dilations/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_3d_dilations/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_3d_dilations(%arg0: !torch.vtensor<[1,1,4,4,4],f32>) -> !torch.vtensor<[1,1,2,2,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.dilations = [2 : si64, 2 : si64, 2 : si64], torch.onnx.kernel_shape = [2 : si64, 2 : si64, 2 : si64], torch.onnx.strides = [1 : si64, 1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,4,4,4],f32>) -> !torch.vtensor<[1,1,2,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.dilations = [2 : si64, 2 : si64, 2 : si64], torch.onnx.kernel_shape = [2 : si64, 2 : si64, 2 : si64], torch.onnx.strides = [1 : si64, 1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,4,4,4],f32>) -> !torch.vtensor<[1,1,2,2,2],f32> return %0 : !torch.vtensor<[1,1,2,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_3d_dilations_use_ref_impl/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_3d_dilations_use_ref_impl/model.mlir index e5d6e2e2b..582dc1689 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_3d_dilations_use_ref_impl/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_3d_dilations_use_ref_impl/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_3d_dilations_use_ref_impl(%arg0: !torch.vtensor<[1,1,4,4,4],f32>) -> !torch.vtensor<[1,1,2,2,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.dilations = [2 : si64, 2 : si64, 2 : si64], torch.onnx.kernel_shape = [2 : si64, 2 : si64, 2 : si64], torch.onnx.strides = [1 : si64, 1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,4,4,4],f32>) -> !torch.vtensor<[1,1,2,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.dilations = [2 : si64, 2 : si64, 2 : si64], torch.onnx.kernel_shape = [2 : si64, 2 : si64, 2 : si64], torch.onnx.strides = [1 : si64, 1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,4,4,4],f32>) -> !torch.vtensor<[1,1,2,2,2],f32> return %0 : !torch.vtensor<[1,1,2,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_3d_dilations_use_ref_impl_large/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_3d_dilations_use_ref_impl_large/model.mlir index 5eeab528c..cb23de8bf 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_3d_dilations_use_ref_impl_large/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_3d_dilations_use_ref_impl_large/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_3d_dilations_use_ref_impl_large(%arg0: !torch.vtensor<[1,1,32,32,32],f32>) -> !torch.vtensor<[1,1,9,9,9],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.ceil_mode = 1 : si64, torch.onnx.dilations = [2 : si64, 2 : si64, 2 : si64], torch.onnx.kernel_shape = [5 : si64, 5 : si64, 5 : si64], torch.onnx.strides = [3 : si64, 3 : si64, 3 : si64]} : (!torch.vtensor<[1,1,32,32,32],f32>) -> !torch.vtensor<[1,1,9,9,9],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.ceil_mode = 1 : si64, torch.onnx.dilations = [2 : si64, 2 : si64, 2 : si64], torch.onnx.kernel_shape = [5 : si64, 5 : si64, 5 : si64], torch.onnx.strides = [3 : si64, 3 : si64, 3 : si64]} : (!torch.vtensor<[1,1,32,32,32],f32>) -> !torch.vtensor<[1,1,9,9,9],f32> return %0 : !torch.vtensor<[1,1,9,9,9],f32> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_with_argmax_2d_precomputed_pads/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_with_argmax_2d_precomputed_pads/model.mlir index f168b7952..035630b8b 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_with_argmax_2d_precomputed_pads/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_with_argmax_2d_precomputed_pads/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_with_argmax_2d_precomputed_pads(%arg0: !torch.vtensor<[1,1,5,5],f32>) -> (!torch.vtensor<[1,1,5,5],f32>, !torch.vtensor<[1,1,5,5],si64>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> (!torch.vtensor<[1,1,5,5],f32>, !torch.vtensor<[1,1,5,5],si64>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.pads = [2 : si64, 2 : si64, 2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> (!torch.vtensor<[1,1,5,5],f32>, !torch.vtensor<[1,1,5,5],si64>) return %0#0, %0#1 : !torch.vtensor<[1,1,5,5],f32>, !torch.vtensor<[1,1,5,5],si64> } } diff --git a/iree_tests/onnx/node/generated/test_maxpool_with_argmax_2d_precomputed_strides/model.mlir b/iree_tests/onnx/node/generated/test_maxpool_with_argmax_2d_precomputed_strides/model.mlir index 9bf09be21..cd4e2095a 100644 --- a/iree_tests/onnx/node/generated/test_maxpool_with_argmax_2d_precomputed_strides/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxpool_with_argmax_2d_precomputed_strides/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxpool_with_argmax_2d_precomputed_strides(%arg0: !torch.vtensor<[1,1,5,5],f32>) -> (!torch.vtensor<[1,1,2,2],f32>, !torch.vtensor<[1,1,2,2],si64>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 12 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.storage_order = 1 : si64, torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> (!torch.vtensor<[1,1,2,2],f32>, !torch.vtensor<[1,1,2,2],si64>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.MaxPool"(%arg0) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.storage_order = 1 : si64, torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,5,5],f32>) -> (!torch.vtensor<[1,1,2,2],f32>, !torch.vtensor<[1,1,2,2],si64>) return %0#0, %0#1 : !torch.vtensor<[1,1,2,2],f32>, !torch.vtensor<[1,1,2,2],si64> } } diff --git a/iree_tests/onnx/node/generated/test_maxunpool_export_with_output_shape/model.mlir b/iree_tests/onnx/node/generated/test_maxunpool_export_with_output_shape/model.mlir index 3e49945a4..fc4c34a6a 100644 --- a/iree_tests/onnx/node/generated/test_maxunpool_export_with_output_shape/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxunpool_export_with_output_shape/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxunpool_export_with_output_shape(%arg0: !torch.vtensor<[1,1,2,2],f32>, %arg1: !torch.vtensor<[1,1,2,2],si64>, %arg2: !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,5,5],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxUnpool"(%arg0, %arg1, %arg2) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,2,2],f32>, !torch.vtensor<[1,1,2,2],si64>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,5,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxUnpool"(%arg0, %arg1, %arg2) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,2,2],f32>, !torch.vtensor<[1,1,2,2],si64>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,5,5],f32> return %0 : !torch.vtensor<[1,1,5,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_maxunpool_export_without_output_shape/model.mlir b/iree_tests/onnx/node/generated/test_maxunpool_export_without_output_shape/model.mlir index 5c51e10f1..71797b15f 100644 --- a/iree_tests/onnx/node/generated/test_maxunpool_export_without_output_shape/model.mlir +++ b/iree_tests/onnx/node/generated/test_maxunpool_export_without_output_shape/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_maxunpool_export_without_output_shape(%arg0: !torch.vtensor<[1,1,2,2],f32>, %arg1: !torch.vtensor<[1,1,2,2],si64>) -> !torch.vtensor<[1,1,4,4],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MaxUnpool"(%arg0, %arg1) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,2,2],f32>, !torch.vtensor<[1,1,2,2],si64>) -> !torch.vtensor<[1,1,4,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MaxUnpool"(%arg0, %arg1) {torch.onnx.kernel_shape = [2 : si64, 2 : si64], torch.onnx.strides = [2 : si64, 2 : si64]} : (!torch.vtensor<[1,1,2,2],f32>, !torch.vtensor<[1,1,2,2],si64>) -> !torch.vtensor<[1,1,4,4],f32> return %0 : !torch.vtensor<[1,1,4,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_mean_example/model.mlir b/iree_tests/onnx/node/generated/test_mean_example/model.mlir index 74e3d3263..dcb7ab6a5 100644 --- a/iree_tests/onnx/node/generated/test_mean_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_mean_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mean_example(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],f32>, %arg2: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mean"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mean"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_mean_one_input/model.mlir b/iree_tests/onnx/node/generated/test_mean_one_input/model.mlir index 79dd47a1c..8407974cf 100644 --- a/iree_tests/onnx/node/generated/test_mean_one_input/model.mlir +++ b/iree_tests/onnx/node/generated/test_mean_one_input/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mean_one_input(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mean"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mean"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_mean_two_inputs/model.mlir b/iree_tests/onnx/node/generated/test_mean_two_inputs/model.mlir index dfe4517bf..05f492b03 100644 --- a/iree_tests/onnx/node/generated/test_mean_two_inputs/model.mlir +++ b/iree_tests/onnx/node/generated/test_mean_two_inputs/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mean_two_inputs(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mean"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mean"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_melweightmatrix/model.mlir b/iree_tests/onnx/node/generated/test_melweightmatrix/model.mlir index 182a3a31e..9c829bf28 100644 --- a/iree_tests/onnx/node/generated/test_melweightmatrix/model.mlir +++ b/iree_tests/onnx/node/generated/test_melweightmatrix/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_melweightmatrix(%arg0: !torch.vtensor<[],si32>, %arg1: !torch.vtensor<[],si32>, %arg2: !torch.vtensor<[],si32>, %arg3: !torch.vtensor<[],f32>, %arg4: !torch.vtensor<[],f32>) -> !torch.vtensor<[9,8],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MelWeightMatrix"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[],si32>, !torch.vtensor<[],si32>, !torch.vtensor<[],si32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[9,8],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MelWeightMatrix"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[],si32>, !torch.vtensor<[],si32>, !torch.vtensor<[],si32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[9,8],f32> return %0 : !torch.vtensor<[9,8],f32> } } diff --git a/iree_tests/onnx/node/generated/test_min_example/model.mlir b/iree_tests/onnx/node/generated/test_min_example/model.mlir index 591deb3a2..605b7a61c 100644 --- a/iree_tests/onnx/node/generated/test_min_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_min_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_min_example(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],f32>, %arg2: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Min"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Min"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_min_float16/model.mlir b/iree_tests/onnx/node/generated/test_min_float16/model.mlir index d09f3a8ec..b2ccc0d20 100644 --- a/iree_tests/onnx/node/generated/test_min_float16/model.mlir +++ b/iree_tests/onnx/node/generated/test_min_float16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_min_float16(%arg0: !torch.vtensor<[3],f16>, %arg1: !torch.vtensor<[3],f16>) -> !torch.vtensor<[3],f16> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],f16>, !torch.vtensor<[3],f16>) -> !torch.vtensor<[3],f16> + %none = torch.constant.none + %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],f16>, !torch.vtensor<[3],f16>) -> !torch.vtensor<[3],f16> return %0 : !torch.vtensor<[3],f16> } } diff --git a/iree_tests/onnx/node/generated/test_min_float32/model.mlir b/iree_tests/onnx/node/generated/test_min_float32/model.mlir index 980d5530c..6979aa36f 100644 --- a/iree_tests/onnx/node/generated/test_min_float32/model.mlir +++ b/iree_tests/onnx/node/generated/test_min_float32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_min_float32(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_min_float64/model.mlir b/iree_tests/onnx/node/generated/test_min_float64/model.mlir index 5ba3c66cf..f5a756709 100644 --- a/iree_tests/onnx/node/generated/test_min_float64/model.mlir +++ b/iree_tests/onnx/node/generated/test_min_float64/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_min_float64(%arg0: !torch.vtensor<[3],f64>, %arg1: !torch.vtensor<[3],f64>) -> !torch.vtensor<[3],f64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],f64>, !torch.vtensor<[3],f64>) -> !torch.vtensor<[3],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],f64>, !torch.vtensor<[3],f64>) -> !torch.vtensor<[3],f64> return %0 : !torch.vtensor<[3],f64> } } diff --git a/iree_tests/onnx/node/generated/test_min_int16/model.mlir b/iree_tests/onnx/node/generated/test_min_int16/model.mlir index 81dfc66c3..061664cb9 100644 --- a/iree_tests/onnx/node/generated/test_min_int16/model.mlir +++ b/iree_tests/onnx/node/generated/test_min_int16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_min_int16(%arg0: !torch.vtensor<[3],si16>, %arg1: !torch.vtensor<[3],si16>) -> !torch.vtensor<[3],si16> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],si16>, !torch.vtensor<[3],si16>) -> !torch.vtensor<[3],si16> + %none = torch.constant.none + %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],si16>, !torch.vtensor<[3],si16>) -> !torch.vtensor<[3],si16> return %0 : !torch.vtensor<[3],si16> } } diff --git a/iree_tests/onnx/node/generated/test_min_int32/model.mlir b/iree_tests/onnx/node/generated/test_min_int32/model.mlir index d7ed9ec14..25517b1a1 100644 --- a/iree_tests/onnx/node/generated/test_min_int32/model.mlir +++ b/iree_tests/onnx/node/generated/test_min_int32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_min_int32(%arg0: !torch.vtensor<[3],si32>, %arg1: !torch.vtensor<[3],si32>) -> !torch.vtensor<[3],si32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],si32>, !torch.vtensor<[3],si32>) -> !torch.vtensor<[3],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],si32>, !torch.vtensor<[3],si32>) -> !torch.vtensor<[3],si32> return %0 : !torch.vtensor<[3],si32> } } diff --git a/iree_tests/onnx/node/generated/test_min_int64/model.mlir b/iree_tests/onnx/node/generated/test_min_int64/model.mlir index d1f92adfd..e9c8f918c 100644 --- a/iree_tests/onnx/node/generated/test_min_int64/model.mlir +++ b/iree_tests/onnx/node/generated/test_min_int64/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_min_int64(%arg0: !torch.vtensor<[3],si64>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> return %0 : !torch.vtensor<[3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_min_int8/model.mlir b/iree_tests/onnx/node/generated/test_min_int8/model.mlir index 4f25ca01d..f65451f2b 100644 --- a/iree_tests/onnx/node/generated/test_min_int8/model.mlir +++ b/iree_tests/onnx/node/generated/test_min_int8/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_min_int8(%arg0: !torch.vtensor<[3],si8>, %arg1: !torch.vtensor<[3],si8>) -> !torch.vtensor<[3],si8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],si8>, !torch.vtensor<[3],si8>) -> !torch.vtensor<[3],si8> + %none = torch.constant.none + %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],si8>, !torch.vtensor<[3],si8>) -> !torch.vtensor<[3],si8> return %0 : !torch.vtensor<[3],si8> } } diff --git a/iree_tests/onnx/node/generated/test_min_one_input/model.mlir b/iree_tests/onnx/node/generated/test_min_one_input/model.mlir index 0f9a579b4..67ce1c5f0 100644 --- a/iree_tests/onnx/node/generated/test_min_one_input/model.mlir +++ b/iree_tests/onnx/node/generated/test_min_one_input/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_min_one_input(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Min"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Min"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_min_two_inputs/model.mlir b/iree_tests/onnx/node/generated/test_min_two_inputs/model.mlir index 6844eeb2f..2156ae83a 100644 --- a/iree_tests/onnx/node/generated/test_min_two_inputs/model.mlir +++ b/iree_tests/onnx/node/generated/test_min_two_inputs/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_min_two_inputs(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_min_uint16/model.mlir b/iree_tests/onnx/node/generated/test_min_uint16/model.mlir index 14d77af27..f4360dfc1 100644 --- a/iree_tests/onnx/node/generated/test_min_uint16/model.mlir +++ b/iree_tests/onnx/node/generated/test_min_uint16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_min_uint16(%arg0: !torch.vtensor<[3],ui16>, %arg1: !torch.vtensor<[3],ui16>) -> !torch.vtensor<[3],ui16> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],ui16>, !torch.vtensor<[3],ui16>) -> !torch.vtensor<[3],ui16> + %none = torch.constant.none + %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],ui16>, !torch.vtensor<[3],ui16>) -> !torch.vtensor<[3],ui16> return %0 : !torch.vtensor<[3],ui16> } } diff --git a/iree_tests/onnx/node/generated/test_min_uint32/model.mlir b/iree_tests/onnx/node/generated/test_min_uint32/model.mlir index 6e3d89623..f930a5a6a 100644 --- a/iree_tests/onnx/node/generated/test_min_uint32/model.mlir +++ b/iree_tests/onnx/node/generated/test_min_uint32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_min_uint32(%arg0: !torch.vtensor<[3],ui32>, %arg1: !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],ui32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],ui32>, !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],ui32> + %none = torch.constant.none + %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],ui32>, !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],ui32> return %0 : !torch.vtensor<[3],ui32> } } diff --git a/iree_tests/onnx/node/generated/test_min_uint64/model.mlir b/iree_tests/onnx/node/generated/test_min_uint64/model.mlir index ff1d3b1d9..ee2ef5636 100644 --- a/iree_tests/onnx/node/generated/test_min_uint64/model.mlir +++ b/iree_tests/onnx/node/generated/test_min_uint64/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_min_uint64(%arg0: !torch.vtensor<[3],ui64>, %arg1: !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],ui64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],ui64>, !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],ui64> + %none = torch.constant.none + %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],ui64>, !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],ui64> return %0 : !torch.vtensor<[3],ui64> } } diff --git a/iree_tests/onnx/node/generated/test_min_uint8/model.mlir b/iree_tests/onnx/node/generated/test_min_uint8/model.mlir index face16f6f..dadf8fd76 100644 --- a/iree_tests/onnx/node/generated/test_min_uint8/model.mlir +++ b/iree_tests/onnx/node/generated/test_min_uint8/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_min_uint8(%arg0: !torch.vtensor<[3],ui8>, %arg1: !torch.vtensor<[3],ui8>) -> !torch.vtensor<[3],ui8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],ui8>, !torch.vtensor<[3],ui8>) -> !torch.vtensor<[3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.Min"(%arg0, %arg1) : (!torch.vtensor<[3],ui8>, !torch.vtensor<[3],ui8>) -> !torch.vtensor<[3],ui8> return %0 : !torch.vtensor<[3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_mish/model.mlir b/iree_tests/onnx/node/generated/test_mish/model.mlir index e87a6dbdf..52d7b0e97 100644 --- a/iree_tests/onnx/node/generated/test_mish/model.mlir +++ b/iree_tests/onnx/node/generated/test_mish/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mish(%arg0: !torch.vtensor<[10000],f32>) -> !torch.vtensor<[10000],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mish"(%arg0) : (!torch.vtensor<[10000],f32>) -> !torch.vtensor<[10000],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mish"(%arg0) : (!torch.vtensor<[10000],f32>) -> !torch.vtensor<[10000],f32> return %0 : !torch.vtensor<[10000],f32> } } diff --git a/iree_tests/onnx/node/generated/test_mish_expanded/model.mlir b/iree_tests/onnx/node/generated/test_mish_expanded/model.mlir index 733dd654c..c11f67c54 100644 --- a/iree_tests/onnx/node/generated/test_mish_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_mish_expanded/model.mlir @@ -1,8 +1,9 @@ module { func.func @test_mish_expanded(%arg0: !torch.vtensor<[10000],f32>) -> !torch.vtensor<[10000],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Softplus"(%arg0) : (!torch.vtensor<[10000],f32>) -> !torch.vtensor<[10000],f32> - %1 = torch.operator "onnx.Tanh"(%0) : (!torch.vtensor<[10000],f32>) -> !torch.vtensor<[10000],f32> - %2 = torch.operator "onnx.Mul"(%arg0, %1) : (!torch.vtensor<[10000],f32>, !torch.vtensor<[10000],f32>) -> !torch.vtensor<[10000],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Softplus"(%arg0) : (!torch.vtensor<[10000],f32>) -> !torch.vtensor<[10000],f32> + %1 = torch.operator "onnx.Tanh"(%0) : (!torch.vtensor<[10000],f32>) -> !torch.vtensor<[10000],f32> + %2 = torch.operator "onnx.Mul"(%arg0, %1) : (!torch.vtensor<[10000],f32>, !torch.vtensor<[10000],f32>) -> !torch.vtensor<[10000],f32> return %2 : !torch.vtensor<[10000],f32> } } diff --git a/iree_tests/onnx/node/generated/test_mod_broadcast/model.mlir b/iree_tests/onnx/node/generated/test_mod_broadcast/model.mlir index fd148bec5..628c1f151 100644 --- a/iree_tests/onnx/node/generated/test_mod_broadcast/model.mlir +++ b/iree_tests/onnx/node/generated/test_mod_broadcast/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mod_broadcast(%arg0: !torch.vtensor<[3,2,5],si32>, %arg1: !torch.vtensor<[1],si32>) -> !torch.vtensor<[3,2,5],si32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[3,2,5],si32>, !torch.vtensor<[1],si32>) -> !torch.vtensor<[3,2,5],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[3,2,5],si32>, !torch.vtensor<[1],si32>) -> !torch.vtensor<[3,2,5],si32> return %0 : !torch.vtensor<[3,2,5],si32> } } diff --git a/iree_tests/onnx/node/generated/test_mod_int64_fmod/model.mlir b/iree_tests/onnx/node/generated/test_mod_int64_fmod/model.mlir index 83728c733..37d0fc51c 100644 --- a/iree_tests/onnx/node/generated/test_mod_int64_fmod/model.mlir +++ b/iree_tests/onnx/node/generated/test_mod_int64_fmod/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mod_int64_fmod(%arg0: !torch.vtensor<[6],si64>, %arg1: !torch.vtensor<[6],si64>) -> !torch.vtensor<[6],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mod"(%arg0, %arg1) {torch.onnx.fmod = 1 : si64} : (!torch.vtensor<[6],si64>, !torch.vtensor<[6],si64>) -> !torch.vtensor<[6],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Mod"(%arg0, %arg1) {torch.onnx.fmod = 1 : si64} : (!torch.vtensor<[6],si64>, !torch.vtensor<[6],si64>) -> !torch.vtensor<[6],si64> return %0 : !torch.vtensor<[6],si64> } } diff --git a/iree_tests/onnx/node/generated/test_mod_mixed_sign_float16/model.mlir b/iree_tests/onnx/node/generated/test_mod_mixed_sign_float16/model.mlir index 7bb0a2bbf..842fc8124 100644 --- a/iree_tests/onnx/node/generated/test_mod_mixed_sign_float16/model.mlir +++ b/iree_tests/onnx/node/generated/test_mod_mixed_sign_float16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mod_mixed_sign_float16(%arg0: !torch.vtensor<[6],f16>, %arg1: !torch.vtensor<[6],f16>) -> !torch.vtensor<[6],f16> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mod"(%arg0, %arg1) {torch.onnx.fmod = 1 : si64} : (!torch.vtensor<[6],f16>, !torch.vtensor<[6],f16>) -> !torch.vtensor<[6],f16> + %none = torch.constant.none + %0 = torch.operator "onnx.Mod"(%arg0, %arg1) {torch.onnx.fmod = 1 : si64} : (!torch.vtensor<[6],f16>, !torch.vtensor<[6],f16>) -> !torch.vtensor<[6],f16> return %0 : !torch.vtensor<[6],f16> } } diff --git a/iree_tests/onnx/node/generated/test_mod_mixed_sign_float32/model.mlir b/iree_tests/onnx/node/generated/test_mod_mixed_sign_float32/model.mlir index 26267dda7..1f0598e2b 100644 --- a/iree_tests/onnx/node/generated/test_mod_mixed_sign_float32/model.mlir +++ b/iree_tests/onnx/node/generated/test_mod_mixed_sign_float32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mod_mixed_sign_float32(%arg0: !torch.vtensor<[6],f32>, %arg1: !torch.vtensor<[6],f32>) -> !torch.vtensor<[6],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mod"(%arg0, %arg1) {torch.onnx.fmod = 1 : si64} : (!torch.vtensor<[6],f32>, !torch.vtensor<[6],f32>) -> !torch.vtensor<[6],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mod"(%arg0, %arg1) {torch.onnx.fmod = 1 : si64} : (!torch.vtensor<[6],f32>, !torch.vtensor<[6],f32>) -> !torch.vtensor<[6],f32> return %0 : !torch.vtensor<[6],f32> } } diff --git a/iree_tests/onnx/node/generated/test_mod_mixed_sign_float64/model.mlir b/iree_tests/onnx/node/generated/test_mod_mixed_sign_float64/model.mlir index 2ea1081b6..b8187f722 100644 --- a/iree_tests/onnx/node/generated/test_mod_mixed_sign_float64/model.mlir +++ b/iree_tests/onnx/node/generated/test_mod_mixed_sign_float64/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mod_mixed_sign_float64(%arg0: !torch.vtensor<[6],f64>, %arg1: !torch.vtensor<[6],f64>) -> !torch.vtensor<[6],f64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mod"(%arg0, %arg1) {torch.onnx.fmod = 1 : si64} : (!torch.vtensor<[6],f64>, !torch.vtensor<[6],f64>) -> !torch.vtensor<[6],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Mod"(%arg0, %arg1) {torch.onnx.fmod = 1 : si64} : (!torch.vtensor<[6],f64>, !torch.vtensor<[6],f64>) -> !torch.vtensor<[6],f64> return %0 : !torch.vtensor<[6],f64> } } diff --git a/iree_tests/onnx/node/generated/test_mod_mixed_sign_int16/model.mlir b/iree_tests/onnx/node/generated/test_mod_mixed_sign_int16/model.mlir index f46fa8a7f..c4ceac1f9 100644 --- a/iree_tests/onnx/node/generated/test_mod_mixed_sign_int16/model.mlir +++ b/iree_tests/onnx/node/generated/test_mod_mixed_sign_int16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mod_mixed_sign_int16(%arg0: !torch.vtensor<[6],si16>, %arg1: !torch.vtensor<[6],si16>) -> !torch.vtensor<[6],si16> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[6],si16>, !torch.vtensor<[6],si16>) -> !torch.vtensor<[6],si16> + %none = torch.constant.none + %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[6],si16>, !torch.vtensor<[6],si16>) -> !torch.vtensor<[6],si16> return %0 : !torch.vtensor<[6],si16> } } diff --git a/iree_tests/onnx/node/generated/test_mod_mixed_sign_int32/model.mlir b/iree_tests/onnx/node/generated/test_mod_mixed_sign_int32/model.mlir index bb83a350d..a1e27c7ae 100644 --- a/iree_tests/onnx/node/generated/test_mod_mixed_sign_int32/model.mlir +++ b/iree_tests/onnx/node/generated/test_mod_mixed_sign_int32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mod_mixed_sign_int32(%arg0: !torch.vtensor<[6],si32>, %arg1: !torch.vtensor<[6],si32>) -> !torch.vtensor<[6],si32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[6],si32>, !torch.vtensor<[6],si32>) -> !torch.vtensor<[6],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[6],si32>, !torch.vtensor<[6],si32>) -> !torch.vtensor<[6],si32> return %0 : !torch.vtensor<[6],si32> } } diff --git a/iree_tests/onnx/node/generated/test_mod_mixed_sign_int64/model.mlir b/iree_tests/onnx/node/generated/test_mod_mixed_sign_int64/model.mlir index 20180f4e7..3037083f6 100644 --- a/iree_tests/onnx/node/generated/test_mod_mixed_sign_int64/model.mlir +++ b/iree_tests/onnx/node/generated/test_mod_mixed_sign_int64/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mod_mixed_sign_int64(%arg0: !torch.vtensor<[6],si64>, %arg1: !torch.vtensor<[6],si64>) -> !torch.vtensor<[6],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[6],si64>, !torch.vtensor<[6],si64>) -> !torch.vtensor<[6],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[6],si64>, !torch.vtensor<[6],si64>) -> !torch.vtensor<[6],si64> return %0 : !torch.vtensor<[6],si64> } } diff --git a/iree_tests/onnx/node/generated/test_mod_mixed_sign_int8/model.mlir b/iree_tests/onnx/node/generated/test_mod_mixed_sign_int8/model.mlir index 519b755e9..6e15f4b62 100644 --- a/iree_tests/onnx/node/generated/test_mod_mixed_sign_int8/model.mlir +++ b/iree_tests/onnx/node/generated/test_mod_mixed_sign_int8/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mod_mixed_sign_int8(%arg0: !torch.vtensor<[6],si8>, %arg1: !torch.vtensor<[6],si8>) -> !torch.vtensor<[6],si8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[6],si8>, !torch.vtensor<[6],si8>) -> !torch.vtensor<[6],si8> + %none = torch.constant.none + %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[6],si8>, !torch.vtensor<[6],si8>) -> !torch.vtensor<[6],si8> return %0 : !torch.vtensor<[6],si8> } } diff --git a/iree_tests/onnx/node/generated/test_mod_uint16/model.mlir b/iree_tests/onnx/node/generated/test_mod_uint16/model.mlir index b2593fa92..6323b0e7f 100644 --- a/iree_tests/onnx/node/generated/test_mod_uint16/model.mlir +++ b/iree_tests/onnx/node/generated/test_mod_uint16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mod_uint16(%arg0: !torch.vtensor<[3],ui16>, %arg1: !torch.vtensor<[3],ui16>) -> !torch.vtensor<[3],ui16> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[3],ui16>, !torch.vtensor<[3],ui16>) -> !torch.vtensor<[3],ui16> + %none = torch.constant.none + %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[3],ui16>, !torch.vtensor<[3],ui16>) -> !torch.vtensor<[3],ui16> return %0 : !torch.vtensor<[3],ui16> } } diff --git a/iree_tests/onnx/node/generated/test_mod_uint32/model.mlir b/iree_tests/onnx/node/generated/test_mod_uint32/model.mlir index b1714b7e5..7d973e1a2 100644 --- a/iree_tests/onnx/node/generated/test_mod_uint32/model.mlir +++ b/iree_tests/onnx/node/generated/test_mod_uint32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mod_uint32(%arg0: !torch.vtensor<[3],ui32>, %arg1: !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],ui32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[3],ui32>, !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],ui32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[3],ui32>, !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],ui32> return %0 : !torch.vtensor<[3],ui32> } } diff --git a/iree_tests/onnx/node/generated/test_mod_uint64/model.mlir b/iree_tests/onnx/node/generated/test_mod_uint64/model.mlir index 17166072e..f06032ceb 100644 --- a/iree_tests/onnx/node/generated/test_mod_uint64/model.mlir +++ b/iree_tests/onnx/node/generated/test_mod_uint64/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mod_uint64(%arg0: !torch.vtensor<[3],ui64>, %arg1: !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],ui64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[3],ui64>, !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],ui64> + %none = torch.constant.none + %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[3],ui64>, !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],ui64> return %0 : !torch.vtensor<[3],ui64> } } diff --git a/iree_tests/onnx/node/generated/test_mod_uint8/model.mlir b/iree_tests/onnx/node/generated/test_mod_uint8/model.mlir index 330b16153..7f613b782 100644 --- a/iree_tests/onnx/node/generated/test_mod_uint8/model.mlir +++ b/iree_tests/onnx/node/generated/test_mod_uint8/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mod_uint8(%arg0: !torch.vtensor<[3],ui8>, %arg1: !torch.vtensor<[3],ui8>) -> !torch.vtensor<[3],ui8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[3],ui8>, !torch.vtensor<[3],ui8>) -> !torch.vtensor<[3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.Mod"(%arg0, %arg1) : (!torch.vtensor<[3],ui8>, !torch.vtensor<[3],ui8>) -> !torch.vtensor<[3],ui8> return %0 : !torch.vtensor<[3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_momentum/model.mlir b/iree_tests/onnx/node/generated/test_momentum/model.mlir index e67e5b5e9..18ae27f94 100644 --- a/iree_tests/onnx/node/generated/test_momentum/model.mlir +++ b/iree_tests/onnx/node/generated/test_momentum/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_momentum(%arg0: !torch.vtensor<[],f32>, %arg1: !torch.vtensor<[],si64>, %arg2: !torch.vtensor<[2],f32>, %arg3: !torch.vtensor<[2],f32>, %arg4: !torch.vtensor<[2],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_versions = {ai.onnx.preview.training = 1 : si64}, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.Momentum"(%arg0, %arg1, %arg2, %arg3, %arg4) {torch.onnx.alpha = 0.949999988 : f32, torch.onnx.beta = 1.000000e-01 : f32, torch.onnx.mode = "standard", torch.onnx.norm_coefficient = 1.000000e-03 : f32} : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.Momentum"(%arg0, %arg1, %arg2, %arg3, %arg4) {torch.onnx.alpha = 0.949999988 : f32, torch.onnx.beta = 1.000000e-01 : f32, torch.onnx.mode = "standard", torch.onnx.norm_coefficient = 1.000000e-03 : f32} : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) return %0#0, %0#1 : !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_momentum_multiple/model.mlir b/iree_tests/onnx/node/generated/test_momentum_multiple/model.mlir index 12ccb6989..2a4185153 100644 --- a/iree_tests/onnx/node/generated/test_momentum_multiple/model.mlir +++ b/iree_tests/onnx/node/generated/test_momentum_multiple/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_momentum_multiple(%arg0: !torch.vtensor<[],f32>, %arg1: !torch.vtensor<[],si64>, %arg2: !torch.vtensor<[1],f32>, %arg3: !torch.vtensor<[2],f32>, %arg4: !torch.vtensor<[1],f32>, %arg5: !torch.vtensor<[2],f32>, %arg6: !torch.vtensor<[1],f32>, %arg7: !torch.vtensor<[2],f32>) -> (!torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_versions = {ai.onnx.preview.training = 1 : si64}, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:4 = torch.operator "onnx.Momentum"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) {torch.onnx.alpha = 0.949999988 : f32, torch.onnx.beta = 8.500000e-01 : f32, torch.onnx.mode = "standard", torch.onnx.norm_coefficient = 1.000000e-03 : f32} : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>) -> (!torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>) + %none = torch.constant.none + %0:4 = torch.operator "onnx.Momentum"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) {torch.onnx.alpha = 0.949999988 : f32, torch.onnx.beta = 8.500000e-01 : f32, torch.onnx.mode = "standard", torch.onnx.norm_coefficient = 1.000000e-03 : f32} : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>) -> (!torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>) return %0#0, %0#1, %0#2, %0#3 : !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>, !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_mul/model.mlir b/iree_tests/onnx/node/generated/test_mul/model.mlir index 8026450a1..c6491babb 100644 --- a/iree_tests/onnx/node/generated/test_mul/model.mlir +++ b/iree_tests/onnx/node/generated/test_mul/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mul(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_mul_bcast/model.mlir b/iree_tests/onnx/node/generated/test_mul_bcast/model.mlir index 4e64d3f88..f5e8323df 100644 --- a/iree_tests/onnx/node/generated/test_mul_bcast/model.mlir +++ b/iree_tests/onnx/node/generated/test_mul_bcast/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mul_bcast(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_mul_example/model.mlir b/iree_tests/onnx/node/generated/test_mul_example/model.mlir index c749eda2d..6276df7b8 100644 --- a/iree_tests/onnx/node/generated/test_mul_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_mul_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mul_example(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_mul_uint8/model.mlir b/iree_tests/onnx/node/generated/test_mul_uint8/model.mlir index c9140149a..0964bc089 100644 --- a/iree_tests/onnx/node/generated/test_mul_uint8/model.mlir +++ b/iree_tests/onnx/node/generated/test_mul_uint8/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mul_uint8(%arg0: !torch.vtensor<[3,4,5],ui8>, %arg1: !torch.vtensor<[3,4,5],ui8>) -> !torch.vtensor<[3,4,5],ui8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],ui8>, !torch.vtensor<[3,4,5],ui8>) -> !torch.vtensor<[3,4,5],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],ui8>, !torch.vtensor<[3,4,5],ui8>) -> !torch.vtensor<[3,4,5],ui8> return %0 : !torch.vtensor<[3,4,5],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_mvn/model.mlir b/iree_tests/onnx/node/generated/test_mvn/model.mlir index 32d7dfaf3..6e8f4a431 100644 --- a/iree_tests/onnx/node/generated/test_mvn/model.mlir +++ b/iree_tests/onnx/node/generated/test_mvn/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_mvn(%arg0: !torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.MeanVarianceNormalization"(%arg0) : (!torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.MeanVarianceNormalization"(%arg0) : (!torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> return %0 : !torch.vtensor<[3,3,3,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_mvn_expanded/model.mlir b/iree_tests/onnx/node/generated/test_mvn_expanded/model.mlir index 8ff5b0a4a..93098bdb8 100644 --- a/iree_tests/onnx/node/generated/test_mvn_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_mvn_expanded/model.mlir @@ -1,16 +1,17 @@ module { func.func @test_mvn_expanded(%arg0: !torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<2.000000e+00> : tensor) : !torch.vtensor<[],f32> - %1 = torch.vtensor.literal(dense<9.99999971E-10> : tensor) : !torch.vtensor<[],f32> - %2 = torch.operator "onnx.ReduceMean"(%arg0) {torch.onnx.axes = [0 : si64, 2 : si64, 3 : si64]} : (!torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[1,3,1,1],f32> - %3 = torch.operator "onnx.Pow"(%2, %0) : (!torch.vtensor<[1,3,1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,3,1,1],f32> - %4 = torch.operator "onnx.Pow"(%arg0, %0) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,3,3,1],f32> - %5 = torch.operator "onnx.ReduceMean"(%4) {torch.onnx.axes = [0 : si64, 2 : si64, 3 : si64]} : (!torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[1,3,1,1],f32> - %6 = torch.operator "onnx.Sub"(%5, %3) : (!torch.vtensor<[1,3,1,1],f32>, !torch.vtensor<[1,3,1,1],f32>) -> !torch.vtensor<[1,3,1,1],f32> - %7 = torch.operator "onnx.Sqrt"(%6) : (!torch.vtensor<[1,3,1,1],f32>) -> !torch.vtensor<[1,3,1,1],f32> - %8 = torch.operator "onnx.Sub"(%arg0, %2) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[1,3,1,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> - %9 = torch.operator "onnx.Add"(%7, %1) : (!torch.vtensor<[1,3,1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,3,1,1],f32> - %10 = torch.operator "onnx.Div"(%8, %9) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[1,3,1,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999971E-10> : tensor} : () -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.ReduceMean"(%arg0) {torch.onnx.axes = [0 : si64, 2 : si64, 3 : si64]} : (!torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[1,3,1,1],f32> + %3 = torch.operator "onnx.Pow"(%2, %0) : (!torch.vtensor<[1,3,1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,3,1,1],f32> + %4 = torch.operator "onnx.Pow"(%arg0, %0) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,3,3,1],f32> + %5 = torch.operator "onnx.ReduceMean"(%4) {torch.onnx.axes = [0 : si64, 2 : si64, 3 : si64]} : (!torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[1,3,1,1],f32> + %6 = torch.operator "onnx.Sub"(%5, %3) : (!torch.vtensor<[1,3,1,1],f32>, !torch.vtensor<[1,3,1,1],f32>) -> !torch.vtensor<[1,3,1,1],f32> + %7 = torch.operator "onnx.Sqrt"(%6) : (!torch.vtensor<[1,3,1,1],f32>) -> !torch.vtensor<[1,3,1,1],f32> + %8 = torch.operator "onnx.Sub"(%arg0, %2) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[1,3,1,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> + %9 = torch.operator "onnx.Add"(%7, %1) : (!torch.vtensor<[1,3,1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,3,1,1],f32> + %10 = torch.operator "onnx.Div"(%8, %9) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[1,3,1,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> return %10 : !torch.vtensor<[3,3,3,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_mvn_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_mvn_expanded_ver18/model.mlir index 97361b41b..d1ffec192 100644 --- a/iree_tests/onnx/node/generated/test_mvn_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_mvn_expanded_ver18/model.mlir @@ -1,17 +1,18 @@ module { func.func @test_mvn_expanded_ver18(%arg0: !torch.vtensor<[3,3,3,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<2.000000e+00> : tensor) : !torch.vtensor<[],f32> - %1 = torch.vtensor.literal(dense<9.99999971E-10> : tensor) : !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [0 : si64, 2 : si64, 3 : si64]} : () -> !torch.vtensor<[3],si64> - %3 = torch.operator "onnx.ReduceMean"(%arg0, %2) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[1,3,1,1],f32> - %4 = torch.operator "onnx.Pow"(%3, %0) : (!torch.vtensor<[1,3,1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,3,1,1],f32> - %5 = torch.operator "onnx.Pow"(%arg0, %0) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,3,3,1],f32> - %6 = torch.operator "onnx.ReduceMean"(%5, %2) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[1,3,1,1],f32> - %7 = torch.operator "onnx.Sub"(%6, %4) : (!torch.vtensor<[1,3,1,1],f32>, !torch.vtensor<[1,3,1,1],f32>) -> !torch.vtensor<[1,3,1,1],f32> - %8 = torch.operator "onnx.Sqrt"(%7) : (!torch.vtensor<[1,3,1,1],f32>) -> !torch.vtensor<[1,3,1,1],f32> - %9 = torch.operator "onnx.Sub"(%arg0, %3) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[1,3,1,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> - %10 = torch.operator "onnx.Add"(%8, %1) : (!torch.vtensor<[1,3,1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,3,1,1],f32> - %11 = torch.operator "onnx.Div"(%9, %10) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[1,3,1,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<9.99999971E-10> : tensor} : () -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value_ints = [0 : si64, 2 : si64, 3 : si64]} : () -> !torch.vtensor<[3],si64> + %3 = torch.operator "onnx.ReduceMean"(%arg0, %2) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[1,3,1,1],f32> + %4 = torch.operator "onnx.Pow"(%3, %0) : (!torch.vtensor<[1,3,1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,3,1,1],f32> + %5 = torch.operator "onnx.Pow"(%arg0, %0) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,3,3,1],f32> + %6 = torch.operator "onnx.ReduceMean"(%5, %2) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[1,3,1,1],f32> + %7 = torch.operator "onnx.Sub"(%6, %4) : (!torch.vtensor<[1,3,1,1],f32>, !torch.vtensor<[1,3,1,1],f32>) -> !torch.vtensor<[1,3,1,1],f32> + %8 = torch.operator "onnx.Sqrt"(%7) : (!torch.vtensor<[1,3,1,1],f32>) -> !torch.vtensor<[1,3,1,1],f32> + %9 = torch.operator "onnx.Sub"(%arg0, %3) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[1,3,1,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> + %10 = torch.operator "onnx.Add"(%8, %1) : (!torch.vtensor<[1,3,1,1],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[1,3,1,1],f32> + %11 = torch.operator "onnx.Div"(%9, %10) : (!torch.vtensor<[3,3,3,1],f32>, !torch.vtensor<[1,3,1,1],f32>) -> !torch.vtensor<[3,3,3,1],f32> return %11 : !torch.vtensor<[3,3,3,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_neg/model.mlir b/iree_tests/onnx/node/generated/test_neg/model.mlir index 4540879e7..ed8f9a80e 100644 --- a/iree_tests/onnx/node/generated/test_neg/model.mlir +++ b/iree_tests/onnx/node/generated/test_neg/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_neg(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Neg"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Neg"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_neg_example/model.mlir b/iree_tests/onnx/node/generated/test_neg_example/model.mlir index b3a2c715a..172de21fe 100644 --- a/iree_tests/onnx/node/generated/test_neg_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_neg_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_neg_example(%arg0: !torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Neg"(%arg0) : (!torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Neg"(%arg0) : (!torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> return %0 : !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nesterov_momentum/model.mlir b/iree_tests/onnx/node/generated/test_nesterov_momentum/model.mlir index 951c2c740..00a864bcb 100644 --- a/iree_tests/onnx/node/generated/test_nesterov_momentum/model.mlir +++ b/iree_tests/onnx/node/generated/test_nesterov_momentum/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nesterov_momentum(%arg0: !torch.vtensor<[],f32>, %arg1: !torch.vtensor<[],si64>, %arg2: !torch.vtensor<[2],f32>, %arg3: !torch.vtensor<[2],f32>, %arg4: !torch.vtensor<[2],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_versions = {ai.onnx.preview.training = 1 : si64}, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.Momentum"(%arg0, %arg1, %arg2, %arg3, %arg4) {torch.onnx.alpha = 0.949999988 : f32, torch.onnx.beta = 1.000000e+00 : f32, torch.onnx.mode = "nesterov", torch.onnx.norm_coefficient = 0.00999999977 : f32} : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.Momentum"(%arg0, %arg1, %arg2, %arg3, %arg4) {torch.onnx.alpha = 0.949999988 : f32, torch.onnx.beta = 1.000000e+00 : f32, torch.onnx.mode = "nesterov", torch.onnx.norm_coefficient = 0.00999999977 : f32} : (!torch.vtensor<[],f32>, !torch.vtensor<[],si64>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) return %0#0, %0#1 : !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NC/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NC/model.mlir index 185d2ce5c..33d95b78b 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NC/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NC/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NC(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NC_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NC_expanded/model.mlir index 4dd9152a5..25fd6c05d 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NC_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NC_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_nllloss_NC_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1],si64> - %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3,1],si64>) -> !torch.vtensor<[3,1],f32> - %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> - %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1],f32> - %7 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1],si64> + %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3,1],si64>) -> !torch.vtensor<[3,1],f32> + %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1],f32> + %7 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],f32> return %7 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1/model.mlir index b22683d19..0c6b82e31 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1_expanded/model.mlir index 559c7ac49..3e2e8db87 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_nllloss_NCd1_expanded(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],si64> - %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],f32> - %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,2],f32>) -> !torch.vtensor<[3,1,2],f32> - %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> - %7 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> - %8 = torch.operator "onnx.ReduceMean"(%7) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],si64> + %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],f32> + %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,2],f32>) -> !torch.vtensor<[3,1,2],f32> + %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %7 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %8 = torch.operator "onnx.ReduceMean"(%7) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2],f32>) -> !torch.vtensor<[],f32> return %8 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1_ii/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1_ii/model.mlir index 481b203d6..3635acb1f 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1_ii/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1_ii/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1_ii(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.ignore_index = 1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.ignore_index = 1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1_ii_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1_ii_expanded/model.mlir index 6caf11f05..076f89656 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1_ii_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1_ii_expanded/model.mlir @@ -1,27 +1,28 @@ module { func.func @test_nllloss_NCd1_ii_expanded(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],si64> - %4 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %5 = torch.operator "onnx.Sub"(%3, %3) : (!torch.vtensor<[3,1,2],si64>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],si64> - %6 = torch.operator "onnx.Cast"(%3) {torch.onnx.to = 7 : si64} : (!torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],si64> - %7 = torch.operator "onnx.Equal"(%6, %4) : (!torch.vtensor<[3,1,2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],i1> - %8 = torch.operator "onnx.Where"(%7, %5, %3) : (!torch.vtensor<[3,1,2],i1>, !torch.vtensor<[3,1,2],si64>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],si64> - %9 = torch.operator "onnx.GatherElements"(%arg0, %8) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],f32> - %10 = torch.vtensor.literal(dense<0.000000e+00> : tensor<1xf32>) : !torch.vtensor<[1],f32> - %11 = torch.operator "onnx.Where"(%7, %10, %9) : (!torch.vtensor<[3,1,2],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,2],f32>) -> !torch.vtensor<[3,1,2],f32> - %12 = torch.operator "onnx.Neg"(%11) : (!torch.vtensor<[3,1,2],f32>) -> !torch.vtensor<[3,1,2],f32> - %13 = torch.operator "onnx.Slice"(%12, %0, %1, %1) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> - %14 = torch.operator "onnx.Squeeze"(%7, %2) : (!torch.vtensor<[3,1,2],i1>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],i1> - %15 = torch.vtensor.literal(dense<1.000000e+00> : tensor<1xf32>) : !torch.vtensor<[1],f32> - %16 = torch.operator "onnx.Where"(%14, %10, %15) : (!torch.vtensor<[3,2],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,2],f32> - %17 = torch.operator "onnx.Squeeze"(%13, %2) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> - %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3,2],f32>, !torch.vtensor<[3,2],f32>) -> !torch.vtensor<[3,2],f32> - %19 = torch.operator "onnx.ReduceSum"(%18) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2],f32>) -> !torch.vtensor<[],f32> - %20 = torch.operator "onnx.ReduceSum"(%16) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2],f32>) -> !torch.vtensor<[],f32> - %21 = torch.operator "onnx.Div"(%19, %20) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Sub"(%3, %3) : (!torch.vtensor<[3,1,2],si64>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],si64> + %6 = torch.operator "onnx.Cast"(%3) {torch.onnx.to = 7 : si64} : (!torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],si64> + %7 = torch.operator "onnx.Equal"(%6, %4) : (!torch.vtensor<[3,1,2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],i1> + %8 = torch.operator "onnx.Where"(%7, %5, %3) : (!torch.vtensor<[3,1,2],i1>, !torch.vtensor<[3,1,2],si64>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],si64> + %9 = torch.operator "onnx.GatherElements"(%arg0, %8) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],f32> + %10 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor<1xf32>} : () -> !torch.vtensor<[1],f32> + %11 = torch.operator "onnx.Where"(%7, %10, %9) : (!torch.vtensor<[3,1,2],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,2],f32>) -> !torch.vtensor<[3,1,2],f32> + %12 = torch.operator "onnx.Neg"(%11) : (!torch.vtensor<[3,1,2],f32>) -> !torch.vtensor<[3,1,2],f32> + %13 = torch.operator "onnx.Slice"(%12, %0, %1, %1) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %14 = torch.operator "onnx.Squeeze"(%7, %2) : (!torch.vtensor<[3,1,2],i1>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],i1> + %15 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor<1xf32>} : () -> !torch.vtensor<[1],f32> + %16 = torch.operator "onnx.Where"(%14, %10, %15) : (!torch.vtensor<[3,2],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,2],f32> + %17 = torch.operator "onnx.Squeeze"(%13, %2) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3,2],f32>, !torch.vtensor<[3,2],f32>) -> !torch.vtensor<[3,2],f32> + %19 = torch.operator "onnx.ReduceSum"(%18) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2],f32>) -> !torch.vtensor<[],f32> + %20 = torch.operator "onnx.ReduceSum"(%16) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2],f32>) -> !torch.vtensor<[],f32> + %21 = torch.operator "onnx.Div"(%19, %20) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> return %21 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1_mean_weight_negative_ii/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1_mean_weight_negative_ii/model.mlir index 6df241c8c..b25c07f64 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1_mean_weight_negative_ii/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1_mean_weight_negative_ii/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1_mean_weight_negative_ii(%arg0: !torch.vtensor<[3,5,6],f32>, %arg1: !torch.vtensor<[3,6],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = -1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6],f32>, !torch.vtensor<[3,6],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = -1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6],f32>, !torch.vtensor<[3,6],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1_mean_weight_negative_ii_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1_mean_weight_negative_ii_expanded/model.mlir index 15a064ea7..0e1fb4059 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1_mean_weight_negative_ii_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1_mean_weight_negative_ii_expanded/model.mlir @@ -1,27 +1,28 @@ module { func.func @test_nllloss_NCd1_mean_weight_negative_ii_expanded(%arg0: !torch.vtensor<[3,5,6],f32>, %arg1: !torch.vtensor<[3,6],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6],si64> - %4 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %5 = torch.operator "onnx.Sub"(%3, %3) : (!torch.vtensor<[3,1,6],si64>, !torch.vtensor<[3,1,6],si64>) -> !torch.vtensor<[3,1,6],si64> - %6 = torch.operator "onnx.Cast"(%3) {torch.onnx.to = 7 : si64} : (!torch.vtensor<[3,1,6],si64>) -> !torch.vtensor<[3,1,6],si64> - %7 = torch.operator "onnx.Equal"(%6, %4) : (!torch.vtensor<[3,1,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6],i1> - %8 = torch.operator "onnx.Where"(%7, %5, %3) : (!torch.vtensor<[3,1,6],i1>, !torch.vtensor<[3,1,6],si64>, !torch.vtensor<[3,1,6],si64>) -> !torch.vtensor<[3,1,6],si64> - %9 = torch.operator "onnx.GatherElements"(%arg0, %8) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6],f32>, !torch.vtensor<[3,1,6],si64>) -> !torch.vtensor<[3,1,6],f32> - %10 = torch.vtensor.literal(dense<0.000000e+00> : tensor<1xf32>) : !torch.vtensor<[1],f32> - %11 = torch.operator "onnx.Where"(%7, %10, %9) : (!torch.vtensor<[3,1,6],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,6],f32>) -> !torch.vtensor<[3,1,6],f32> - %12 = torch.operator "onnx.Neg"(%11) : (!torch.vtensor<[3,1,6],f32>) -> !torch.vtensor<[3,1,6],f32> - %13 = torch.operator "onnx.Slice"(%12, %0, %1, %1) : (!torch.vtensor<[3,1,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6],f32> - %14 = torch.operator "onnx.Gather"(%arg2, %8) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,1,6],si64>) -> !torch.vtensor<[3,1,6],f32> - %15 = torch.operator "onnx.Where"(%7, %10, %14) : (!torch.vtensor<[3,1,6],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,6],f32>) -> !torch.vtensor<[3,1,6],f32> - %16 = torch.operator "onnx.Squeeze"(%15, %2) : (!torch.vtensor<[3,1,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6],f32> - %17 = torch.operator "onnx.Squeeze"(%13, %2) : (!torch.vtensor<[3,1,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6],f32> - %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3,6],f32>, !torch.vtensor<[3,6],f32>) -> !torch.vtensor<[3,6],f32> - %19 = torch.operator "onnx.ReduceSum"(%18) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6],f32>) -> !torch.vtensor<[],f32> - %20 = torch.operator "onnx.ReduceSum"(%16) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6],f32>) -> !torch.vtensor<[],f32> - %21 = torch.operator "onnx.Div"(%19, %20) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Sub"(%3, %3) : (!torch.vtensor<[3,1,6],si64>, !torch.vtensor<[3,1,6],si64>) -> !torch.vtensor<[3,1,6],si64> + %6 = torch.operator "onnx.Cast"(%3) {torch.onnx.to = 7 : si64} : (!torch.vtensor<[3,1,6],si64>) -> !torch.vtensor<[3,1,6],si64> + %7 = torch.operator "onnx.Equal"(%6, %4) : (!torch.vtensor<[3,1,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6],i1> + %8 = torch.operator "onnx.Where"(%7, %5, %3) : (!torch.vtensor<[3,1,6],i1>, !torch.vtensor<[3,1,6],si64>, !torch.vtensor<[3,1,6],si64>) -> !torch.vtensor<[3,1,6],si64> + %9 = torch.operator "onnx.GatherElements"(%arg0, %8) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6],f32>, !torch.vtensor<[3,1,6],si64>) -> !torch.vtensor<[3,1,6],f32> + %10 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor<1xf32>} : () -> !torch.vtensor<[1],f32> + %11 = torch.operator "onnx.Where"(%7, %10, %9) : (!torch.vtensor<[3,1,6],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,6],f32>) -> !torch.vtensor<[3,1,6],f32> + %12 = torch.operator "onnx.Neg"(%11) : (!torch.vtensor<[3,1,6],f32>) -> !torch.vtensor<[3,1,6],f32> + %13 = torch.operator "onnx.Slice"(%12, %0, %1, %1) : (!torch.vtensor<[3,1,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6],f32> + %14 = torch.operator "onnx.Gather"(%arg2, %8) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,1,6],si64>) -> !torch.vtensor<[3,1,6],f32> + %15 = torch.operator "onnx.Where"(%7, %10, %14) : (!torch.vtensor<[3,1,6],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,6],f32>) -> !torch.vtensor<[3,1,6],f32> + %16 = torch.operator "onnx.Squeeze"(%15, %2) : (!torch.vtensor<[3,1,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6],f32> + %17 = torch.operator "onnx.Squeeze"(%13, %2) : (!torch.vtensor<[3,1,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6],f32> + %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3,6],f32>, !torch.vtensor<[3,6],f32>) -> !torch.vtensor<[3,6],f32> + %19 = torch.operator "onnx.ReduceSum"(%18) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6],f32>) -> !torch.vtensor<[],f32> + %20 = torch.operator "onnx.ReduceSum"(%16) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6],f32>) -> !torch.vtensor<[],f32> + %21 = torch.operator "onnx.Div"(%19, %20) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> return %21 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1_weight/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1_weight/model.mlir index a814b254f..aa47a0f5a 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1_weight/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1_weight/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1_weight(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1_weight_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1_weight_expanded/model.mlir index 00bf2d9ef..df1d3c453 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1_weight_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1_weight_expanded/model.mlir @@ -1,18 +1,19 @@ module { func.func @test_nllloss_NCd1_weight_expanded(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],si64> - %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],f32> - %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,2],f32>) -> !torch.vtensor<[3,1,2],f32> - %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> - %7 = torch.operator "onnx.Gather"(%arg2, %arg1) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[3,2],f32> - %8 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> - %9 = torch.operator "onnx.Mul"(%8, %7) : (!torch.vtensor<[3,2],f32>, !torch.vtensor<[3,2],f32>) -> !torch.vtensor<[3,2],f32> - %10 = torch.operator "onnx.ReduceSum"(%9) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2],f32>) -> !torch.vtensor<[],f32> - %11 = torch.operator "onnx.ReduceSum"(%7) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2],f32>) -> !torch.vtensor<[],f32> - %12 = torch.operator "onnx.Div"(%10, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],si64> + %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],f32> + %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,2],f32>) -> !torch.vtensor<[3,1,2],f32> + %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %7 = torch.operator "onnx.Gather"(%arg2, %arg1) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[3,2],f32> + %8 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %9 = torch.operator "onnx.Mul"(%8, %7) : (!torch.vtensor<[3,2],f32>, !torch.vtensor<[3,2],f32>) -> !torch.vtensor<[3,2],f32> + %10 = torch.operator "onnx.ReduceSum"(%9) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2],f32>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.ReduceSum"(%7) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2],f32>) -> !torch.vtensor<[],f32> + %12 = torch.operator "onnx.Div"(%10, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> return %12 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1_weight_ii/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1_weight_ii/model.mlir index 4e785539c..0b3edfe4f 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1_weight_ii/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1_weight_ii/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1_weight_ii(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1_weight_ii_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1_weight_ii_expanded/model.mlir index 4a15f9896..8edf07289 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1_weight_ii_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1_weight_ii_expanded/model.mlir @@ -1,27 +1,28 @@ module { func.func @test_nllloss_NCd1_weight_ii_expanded(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],si64> - %4 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %5 = torch.operator "onnx.Sub"(%3, %3) : (!torch.vtensor<[3,1,2],si64>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],si64> - %6 = torch.operator "onnx.Cast"(%3) {torch.onnx.to = 7 : si64} : (!torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],si64> - %7 = torch.operator "onnx.Equal"(%6, %4) : (!torch.vtensor<[3,1,2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],i1> - %8 = torch.operator "onnx.Where"(%7, %5, %3) : (!torch.vtensor<[3,1,2],i1>, !torch.vtensor<[3,1,2],si64>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],si64> - %9 = torch.operator "onnx.GatherElements"(%arg0, %8) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],f32> - %10 = torch.vtensor.literal(dense<0.000000e+00> : tensor<1xf32>) : !torch.vtensor<[1],f32> - %11 = torch.operator "onnx.Where"(%7, %10, %9) : (!torch.vtensor<[3,1,2],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,2],f32>) -> !torch.vtensor<[3,1,2],f32> - %12 = torch.operator "onnx.Neg"(%11) : (!torch.vtensor<[3,1,2],f32>) -> !torch.vtensor<[3,1,2],f32> - %13 = torch.operator "onnx.Slice"(%12, %0, %1, %1) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> - %14 = torch.operator "onnx.Gather"(%arg2, %8) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],f32> - %15 = torch.operator "onnx.Where"(%7, %10, %14) : (!torch.vtensor<[3,1,2],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,2],f32>) -> !torch.vtensor<[3,1,2],f32> - %16 = torch.operator "onnx.Squeeze"(%15, %2) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> - %17 = torch.operator "onnx.Squeeze"(%13, %2) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> - %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3,2],f32>, !torch.vtensor<[3,2],f32>) -> !torch.vtensor<[3,2],f32> - %19 = torch.operator "onnx.ReduceSum"(%18) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2],f32>) -> !torch.vtensor<[],f32> - %20 = torch.operator "onnx.ReduceSum"(%16) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2],f32>) -> !torch.vtensor<[],f32> - %21 = torch.operator "onnx.Div"(%19, %20) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Sub"(%3, %3) : (!torch.vtensor<[3,1,2],si64>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],si64> + %6 = torch.operator "onnx.Cast"(%3) {torch.onnx.to = 7 : si64} : (!torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],si64> + %7 = torch.operator "onnx.Equal"(%6, %4) : (!torch.vtensor<[3,1,2],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],i1> + %8 = torch.operator "onnx.Where"(%7, %5, %3) : (!torch.vtensor<[3,1,2],i1>, !torch.vtensor<[3,1,2],si64>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],si64> + %9 = torch.operator "onnx.GatherElements"(%arg0, %8) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],f32> + %10 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor<1xf32>} : () -> !torch.vtensor<[1],f32> + %11 = torch.operator "onnx.Where"(%7, %10, %9) : (!torch.vtensor<[3,1,2],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,2],f32>) -> !torch.vtensor<[3,1,2],f32> + %12 = torch.operator "onnx.Neg"(%11) : (!torch.vtensor<[3,1,2],f32>) -> !torch.vtensor<[3,1,2],f32> + %13 = torch.operator "onnx.Slice"(%12, %0, %1, %1) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %14 = torch.operator "onnx.Gather"(%arg2, %8) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,1,2],si64>) -> !torch.vtensor<[3,1,2],f32> + %15 = torch.operator "onnx.Where"(%7, %10, %14) : (!torch.vtensor<[3,1,2],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,2],f32>) -> !torch.vtensor<[3,1,2],f32> + %16 = torch.operator "onnx.Squeeze"(%15, %2) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %17 = torch.operator "onnx.Squeeze"(%13, %2) : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3,2],f32>, !torch.vtensor<[3,2],f32>) -> !torch.vtensor<[3,2],f32> + %19 = torch.operator "onnx.ReduceSum"(%18) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2],f32>) -> !torch.vtensor<[],f32> + %20 = torch.operator "onnx.ReduceSum"(%16) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2],f32>) -> !torch.vtensor<[],f32> + %21 = torch.operator "onnx.Div"(%19, %20) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> return %21 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2/model.mlir index e7ff643e2..4afeca303 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1d2(%arg0: !torch.vtensor<[3,5,6,6],f32>, %arg1: !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[3,6,6],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[3,6,6],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[3,6,6],f32> return %0 : !torch.vtensor<[3,6,6],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_expanded/model.mlir index 3479a14ba..66360e1a1 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_nllloss_NCd1d2_expanded(%arg0: !torch.vtensor<[3,5,6,6],f32>, %arg1: !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[3,6,6],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],si64> - %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> - %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %7 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],si64> + %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> + %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %7 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> return %7 : !torch.vtensor<[3,6,6],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_no_weight_reduction_mean_ii/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_no_weight_reduction_mean_ii/model.mlir index 98c5fd0ce..95049ab24 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_no_weight_reduction_mean_ii/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_no_weight_reduction_mean_ii/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1d2_no_weight_reduction_mean_ii(%arg0: !torch.vtensor<[3,5,6,6],f32>, %arg1: !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.ignore_index = 1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.ignore_index = 1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_no_weight_reduction_mean_ii_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_no_weight_reduction_mean_ii_expanded/model.mlir index c4cbf6e92..5a217193d 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_no_weight_reduction_mean_ii_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_no_weight_reduction_mean_ii_expanded/model.mlir @@ -1,27 +1,28 @@ module { func.func @test_nllloss_NCd1d2_no_weight_reduction_mean_ii_expanded(%arg0: !torch.vtensor<[3,5,6,6],f32>, %arg1: !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],si64> - %4 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %5 = torch.operator "onnx.Sub"(%3, %3) : (!torch.vtensor<[3,1,6,6],si64>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],si64> - %6 = torch.operator "onnx.Cast"(%3) {torch.onnx.to = 7 : si64} : (!torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],si64> - %7 = torch.operator "onnx.Equal"(%6, %4) : (!torch.vtensor<[3,1,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],i1> - %8 = torch.operator "onnx.Where"(%7, %5, %3) : (!torch.vtensor<[3,1,6,6],i1>, !torch.vtensor<[3,1,6,6],si64>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],si64> - %9 = torch.operator "onnx.GatherElements"(%arg0, %8) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %10 = torch.vtensor.literal(dense<0.000000e+00> : tensor<1xf32>) : !torch.vtensor<[1],f32> - %11 = torch.operator "onnx.Where"(%7, %10, %9) : (!torch.vtensor<[3,1,6,6],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> - %12 = torch.operator "onnx.Neg"(%11) : (!torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> - %13 = torch.operator "onnx.Slice"(%12, %0, %1, %1) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %14 = torch.operator "onnx.Squeeze"(%7, %2) : (!torch.vtensor<[3,1,6,6],i1>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],i1> - %15 = torch.vtensor.literal(dense<1.000000e+00> : tensor<1xf32>) : !torch.vtensor<[1],f32> - %16 = torch.operator "onnx.Where"(%14, %10, %15) : (!torch.vtensor<[3,6,6],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,6,6],f32> - %17 = torch.operator "onnx.Squeeze"(%13, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> - %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3,6,6],f32>, !torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[3,6,6],f32> - %19 = torch.operator "onnx.ReduceSum"(%18) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[],f32> - %20 = torch.operator "onnx.ReduceSum"(%16) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[],f32> - %21 = torch.operator "onnx.Div"(%19, %20) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Sub"(%3, %3) : (!torch.vtensor<[3,1,6,6],si64>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],si64> + %6 = torch.operator "onnx.Cast"(%3) {torch.onnx.to = 7 : si64} : (!torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],si64> + %7 = torch.operator "onnx.Equal"(%6, %4) : (!torch.vtensor<[3,1,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],i1> + %8 = torch.operator "onnx.Where"(%7, %5, %3) : (!torch.vtensor<[3,1,6,6],i1>, !torch.vtensor<[3,1,6,6],si64>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],si64> + %9 = torch.operator "onnx.GatherElements"(%arg0, %8) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %10 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor<1xf32>} : () -> !torch.vtensor<[1],f32> + %11 = torch.operator "onnx.Where"(%7, %10, %9) : (!torch.vtensor<[3,1,6,6],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> + %12 = torch.operator "onnx.Neg"(%11) : (!torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> + %13 = torch.operator "onnx.Slice"(%12, %0, %1, %1) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %14 = torch.operator "onnx.Squeeze"(%7, %2) : (!torch.vtensor<[3,1,6,6],i1>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],i1> + %15 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor<1xf32>} : () -> !torch.vtensor<[1],f32> + %16 = torch.operator "onnx.Where"(%14, %10, %15) : (!torch.vtensor<[3,6,6],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,6,6],f32> + %17 = torch.operator "onnx.Squeeze"(%13, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> + %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3,6,6],f32>, !torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[3,6,6],f32> + %19 = torch.operator "onnx.ReduceSum"(%18) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[],f32> + %20 = torch.operator "onnx.ReduceSum"(%16) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[],f32> + %21 = torch.operator "onnx.Div"(%19, %20) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> return %21 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_reduction_mean/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_reduction_mean/model.mlir index 5b093bddd..0a87cc854 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_reduction_mean/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_reduction_mean/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1d2_reduction_mean(%arg0: !torch.vtensor<[3,5,6,6],f32>, %arg1: !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_reduction_mean_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_reduction_mean_expanded/model.mlir index 000e0299f..4e270d1d8 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_reduction_mean_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_reduction_mean_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_nllloss_NCd1d2_reduction_mean_expanded(%arg0: !torch.vtensor<[3,5,6,6],f32>, %arg1: !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],si64> - %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> - %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %7 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> - %8 = torch.operator "onnx.ReduceMean"(%7) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],si64> + %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> + %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %7 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> + %8 = torch.operator "onnx.ReduceMean"(%7) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[],f32> return %8 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_reduction_sum/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_reduction_sum/model.mlir index e254151bb..2093688f7 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_reduction_sum/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_reduction_sum/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1d2_reduction_sum(%arg0: !torch.vtensor<[3,5,6,6],f32>, %arg1: !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.reduction = "sum"} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.reduction = "sum"} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_reduction_sum_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_reduction_sum_expanded/model.mlir index 2565d0a7e..0a5aa1095 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_reduction_sum_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_reduction_sum_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_nllloss_NCd1d2_reduction_sum_expanded(%arg0: !torch.vtensor<[3,5,6,6],f32>, %arg1: !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],si64> - %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> - %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %7 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> - %8 = torch.operator "onnx.ReduceSum"(%7) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],si64> + %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> + %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %7 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> + %8 = torch.operator "onnx.ReduceSum"(%7) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[],f32> return %8 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight/model.mlir index 749ab6242..cce0d63d2 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1d2_with_weight(%arg0: !torch.vtensor<[3,5,6,6],f32>, %arg1: !torch.vtensor<[3,6,6],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,6,6],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,6,6],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,6,6],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,6,6],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,6,6],f32> return %0 : !torch.vtensor<[3,6,6],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_expanded/model.mlir index 28b7fbf7c..e9cea12cb 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_expanded/model.mlir @@ -1,15 +1,16 @@ module { func.func @test_nllloss_NCd1d2_with_weight_expanded(%arg0: !torch.vtensor<[3,5,6,6],f32>, %arg1: !torch.vtensor<[3,6,6],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,6,6],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],si64> - %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> - %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %7 = torch.operator "onnx.Gather"(%arg2, %arg1) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[3,6,6],f32> - %8 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> - %9 = torch.operator "onnx.Mul"(%8, %7) : (!torch.vtensor<[3,6,6],f32>, !torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[3,6,6],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],si64> + %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> + %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %7 = torch.operator "onnx.Gather"(%arg2, %arg1) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[3,6,6],f32> + %8 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> + %9 = torch.operator "onnx.Mul"(%8, %7) : (!torch.vtensor<[3,6,6],f32>, !torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[3,6,6],f32> return %9 : !torch.vtensor<[3,6,6],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_mean/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_mean/model.mlir index feec8ff2c..b2af3d4bd 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_mean/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_mean/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1d2_with_weight_reduction_mean(%arg0: !torch.vtensor<[3,5,6,6],f32>, %arg1: !torch.vtensor<[3,6,6],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,6,6],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,6,6],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_mean_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_mean_expanded/model.mlir index 77557d196..cfb864a39 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_mean_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_mean_expanded/model.mlir @@ -1,18 +1,19 @@ module { func.func @test_nllloss_NCd1d2_with_weight_reduction_mean_expanded(%arg0: !torch.vtensor<[3,5,6,6],f32>, %arg1: !torch.vtensor<[3,6,6],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],si64> - %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> - %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %7 = torch.operator "onnx.Gather"(%arg2, %arg1) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[3,6,6],f32> - %8 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> - %9 = torch.operator "onnx.Mul"(%8, %7) : (!torch.vtensor<[3,6,6],f32>, !torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[3,6,6],f32> - %10 = torch.operator "onnx.ReduceSum"(%9) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[],f32> - %11 = torch.operator "onnx.ReduceSum"(%7) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[],f32> - %12 = torch.operator "onnx.Div"(%10, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],si64> + %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> + %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %7 = torch.operator "onnx.Gather"(%arg2, %arg1) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[3,6,6],f32> + %8 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> + %9 = torch.operator "onnx.Mul"(%8, %7) : (!torch.vtensor<[3,6,6],f32>, !torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[3,6,6],f32> + %10 = torch.operator "onnx.ReduceSum"(%9) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.ReduceSum"(%7) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[],f32> + %12 = torch.operator "onnx.Div"(%10, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> return %12 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_sum/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_sum/model.mlir index 81738b6d8..2a000fb77 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_sum/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_sum/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1d2_with_weight_reduction_sum(%arg0: !torch.vtensor<[3,5,6,6],f32>, %arg1: !torch.vtensor<[3,6,6],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "sum"} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,6,6],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "sum"} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,6,6],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_sum_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_sum_expanded/model.mlir index be03d5577..4def16729 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_sum_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_sum_expanded/model.mlir @@ -1,16 +1,17 @@ module { func.func @test_nllloss_NCd1d2_with_weight_reduction_sum_expanded(%arg0: !torch.vtensor<[3,5,6,6],f32>, %arg1: !torch.vtensor<[3,6,6],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],si64> - %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> - %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %7 = torch.operator "onnx.Gather"(%arg2, %arg1) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[3,6,6],f32> - %8 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> - %9 = torch.operator "onnx.Mul"(%8, %7) : (!torch.vtensor<[3,6,6],f32>, !torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[3,6,6],f32> - %10 = torch.operator "onnx.ReduceSum"(%9) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],si64> + %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> + %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %7 = torch.operator "onnx.Gather"(%arg2, %arg1) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,6,6],si64>) -> !torch.vtensor<[3,6,6],f32> + %8 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> + %9 = torch.operator "onnx.Mul"(%8, %7) : (!torch.vtensor<[3,6,6],f32>, !torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[3,6,6],f32> + %10 = torch.operator "onnx.ReduceSum"(%9) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[],f32> return %10 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_sum_ii/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_sum_ii/model.mlir index b1dd671dd..75c092767 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_sum_ii/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_sum_ii/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1d2_with_weight_reduction_sum_ii(%arg0: !torch.vtensor<[3,5,6,6],f32>, %arg1: !torch.vtensor<[3,6,6],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 0 : si64, torch.onnx.reduction = "sum"} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,6,6],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 0 : si64, torch.onnx.reduction = "sum"} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,6,6],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_sum_ii_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_sum_ii_expanded/model.mlir index c3828d254..1c2fd4422 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_sum_ii_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2_with_weight_reduction_sum_ii_expanded/model.mlir @@ -1,25 +1,26 @@ module { func.func @test_nllloss_NCd1d2_with_weight_reduction_sum_ii_expanded(%arg0: !torch.vtensor<[3,5,6,6],f32>, %arg1: !torch.vtensor<[3,6,6],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],si64> - %4 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %5 = torch.operator "onnx.Sub"(%3, %3) : (!torch.vtensor<[3,1,6,6],si64>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],si64> - %6 = torch.operator "onnx.Cast"(%3) {torch.onnx.to = 7 : si64} : (!torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],si64> - %7 = torch.operator "onnx.Equal"(%6, %4) : (!torch.vtensor<[3,1,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],i1> - %8 = torch.operator "onnx.Where"(%7, %5, %3) : (!torch.vtensor<[3,1,6,6],i1>, !torch.vtensor<[3,1,6,6],si64>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],si64> - %9 = torch.operator "onnx.GatherElements"(%arg0, %8) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %10 = torch.vtensor.literal(dense<0.000000e+00> : tensor<1xf32>) : !torch.vtensor<[1],f32> - %11 = torch.operator "onnx.Where"(%7, %10, %9) : (!torch.vtensor<[3,1,6,6],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> - %12 = torch.operator "onnx.Neg"(%11) : (!torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> - %13 = torch.operator "onnx.Slice"(%12, %0, %1, %1) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %14 = torch.operator "onnx.Gather"(%arg2, %8) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> - %15 = torch.operator "onnx.Where"(%7, %10, %14) : (!torch.vtensor<[3,1,6,6],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> - %16 = torch.operator "onnx.Squeeze"(%15, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> - %17 = torch.operator "onnx.Squeeze"(%13, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> - %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3,6,6],f32>, !torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[3,6,6],f32> - %19 = torch.operator "onnx.ReduceSum"(%18) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Sub"(%3, %3) : (!torch.vtensor<[3,1,6,6],si64>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],si64> + %6 = torch.operator "onnx.Cast"(%3) {torch.onnx.to = 7 : si64} : (!torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],si64> + %7 = torch.operator "onnx.Equal"(%6, %4) : (!torch.vtensor<[3,1,6,6],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],i1> + %8 = torch.operator "onnx.Where"(%7, %5, %3) : (!torch.vtensor<[3,1,6,6],i1>, !torch.vtensor<[3,1,6,6],si64>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],si64> + %9 = torch.operator "onnx.GatherElements"(%arg0, %8) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %10 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor<1xf32>} : () -> !torch.vtensor<[1],f32> + %11 = torch.operator "onnx.Where"(%7, %10, %9) : (!torch.vtensor<[3,1,6,6],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> + %12 = torch.operator "onnx.Neg"(%11) : (!torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> + %13 = torch.operator "onnx.Slice"(%12, %0, %1, %1) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %14 = torch.operator "onnx.Gather"(%arg2, %8) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,1,6,6],si64>) -> !torch.vtensor<[3,1,6,6],f32> + %15 = torch.operator "onnx.Where"(%7, %10, %14) : (!torch.vtensor<[3,1,6,6],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,6,6],f32>) -> !torch.vtensor<[3,1,6,6],f32> + %16 = torch.operator "onnx.Squeeze"(%15, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> + %17 = torch.operator "onnx.Squeeze"(%13, %2) : (!torch.vtensor<[3,1,6,6],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6],f32> + %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3,6,6],f32>, !torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[3,6,6],f32> + %19 = torch.operator "onnx.ReduceSum"(%18) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6],f32>) -> !torch.vtensor<[],f32> return %19 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3_none_no_weight_negative_ii/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3_none_no_weight_negative_ii/model.mlir index 76fe6bd1a..35d1f7fe5 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3_none_no_weight_negative_ii/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3_none_no_weight_negative_ii/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1d2d3_none_no_weight_negative_ii(%arg0: !torch.vtensor<[3,5,6,6,5],f32>, %arg1: !torch.vtensor<[3,6,6,5],si64>) -> !torch.vtensor<[3,6,6,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.ignore_index = -5 : si64, torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5,6,6,5],f32>, !torch.vtensor<[3,6,6,5],si64>) -> !torch.vtensor<[3,6,6,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.ignore_index = -5 : si64, torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5,6,6,5],f32>, !torch.vtensor<[3,6,6,5],si64>) -> !torch.vtensor<[3,6,6,5],f32> return %0 : !torch.vtensor<[3,6,6,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3_none_no_weight_negative_ii_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3_none_no_weight_negative_ii_expanded/model.mlir index ebf7fbe1e..685defc8b 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3_none_no_weight_negative_ii_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3_none_no_weight_negative_ii_expanded/model.mlir @@ -1,24 +1,25 @@ module { func.func @test_nllloss_NCd1d2d3_none_no_weight_negative_ii_expanded(%arg0: !torch.vtensor<[3,5,6,6,5],f32>, %arg1: !torch.vtensor<[3,6,6,5],si64>) -> !torch.vtensor<[3,6,6,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6,5],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6,5],si64> - %4 = torch.vtensor.literal(dense<-5> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %5 = torch.operator "onnx.Sub"(%3, %3) : (!torch.vtensor<[3,1,6,6,5],si64>, !torch.vtensor<[3,1,6,6,5],si64>) -> !torch.vtensor<[3,1,6,6,5],si64> - %6 = torch.operator "onnx.Cast"(%3) {torch.onnx.to = 7 : si64} : (!torch.vtensor<[3,1,6,6,5],si64>) -> !torch.vtensor<[3,1,6,6,5],si64> - %7 = torch.operator "onnx.Equal"(%6, %4) : (!torch.vtensor<[3,1,6,6,5],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6,5],i1> - %8 = torch.operator "onnx.Where"(%7, %5, %3) : (!torch.vtensor<[3,1,6,6,5],i1>, !torch.vtensor<[3,1,6,6,5],si64>, !torch.vtensor<[3,1,6,6,5],si64>) -> !torch.vtensor<[3,1,6,6,5],si64> - %9 = torch.operator "onnx.GatherElements"(%arg0, %8) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6,5],f32>, !torch.vtensor<[3,1,6,6,5],si64>) -> !torch.vtensor<[3,1,6,6,5],f32> - %10 = torch.vtensor.literal(dense<0.000000e+00> : tensor<1xf32>) : !torch.vtensor<[1],f32> - %11 = torch.operator "onnx.Where"(%7, %10, %9) : (!torch.vtensor<[3,1,6,6,5],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,6,6,5],f32>) -> !torch.vtensor<[3,1,6,6,5],f32> - %12 = torch.operator "onnx.Neg"(%11) : (!torch.vtensor<[3,1,6,6,5],f32>) -> !torch.vtensor<[3,1,6,6,5],f32> - %13 = torch.operator "onnx.Slice"(%12, %0, %1, %1) : (!torch.vtensor<[3,1,6,6,5],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6,5],f32> - %14 = torch.operator "onnx.Squeeze"(%7, %2) : (!torch.vtensor<[3,1,6,6,5],i1>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6,5],i1> - %15 = torch.vtensor.literal(dense<1.000000e+00> : tensor<1xf32>) : !torch.vtensor<[1],f32> - %16 = torch.operator "onnx.Where"(%14, %10, %15) : (!torch.vtensor<[3,6,6,5],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,6,6,5],f32> - %17 = torch.operator "onnx.Squeeze"(%13, %2) : (!torch.vtensor<[3,1,6,6,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6,5],f32> - %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3,6,6,5],f32>, !torch.vtensor<[3,6,6,5],f32>) -> !torch.vtensor<[3,6,6,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6,5],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6,5],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-5> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Sub"(%3, %3) : (!torch.vtensor<[3,1,6,6,5],si64>, !torch.vtensor<[3,1,6,6,5],si64>) -> !torch.vtensor<[3,1,6,6,5],si64> + %6 = torch.operator "onnx.Cast"(%3) {torch.onnx.to = 7 : si64} : (!torch.vtensor<[3,1,6,6,5],si64>) -> !torch.vtensor<[3,1,6,6,5],si64> + %7 = torch.operator "onnx.Equal"(%6, %4) : (!torch.vtensor<[3,1,6,6,5],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6,5],i1> + %8 = torch.operator "onnx.Where"(%7, %5, %3) : (!torch.vtensor<[3,1,6,6,5],i1>, !torch.vtensor<[3,1,6,6,5],si64>, !torch.vtensor<[3,1,6,6,5],si64>) -> !torch.vtensor<[3,1,6,6,5],si64> + %9 = torch.operator "onnx.GatherElements"(%arg0, %8) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6,5],f32>, !torch.vtensor<[3,1,6,6,5],si64>) -> !torch.vtensor<[3,1,6,6,5],f32> + %10 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor<1xf32>} : () -> !torch.vtensor<[1],f32> + %11 = torch.operator "onnx.Where"(%7, %10, %9) : (!torch.vtensor<[3,1,6,6,5],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1,6,6,5],f32>) -> !torch.vtensor<[3,1,6,6,5],f32> + %12 = torch.operator "onnx.Neg"(%11) : (!torch.vtensor<[3,1,6,6,5],f32>) -> !torch.vtensor<[3,1,6,6,5],f32> + %13 = torch.operator "onnx.Slice"(%12, %0, %1, %1) : (!torch.vtensor<[3,1,6,6,5],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6,5],f32> + %14 = torch.operator "onnx.Squeeze"(%7, %2) : (!torch.vtensor<[3,1,6,6,5],i1>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6,5],i1> + %15 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor<1xf32>} : () -> !torch.vtensor<[1],f32> + %16 = torch.operator "onnx.Where"(%14, %10, %15) : (!torch.vtensor<[3,6,6,5],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,6,6,5],f32> + %17 = torch.operator "onnx.Squeeze"(%13, %2) : (!torch.vtensor<[3,1,6,6,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6,5],f32> + %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3,6,6,5],f32>, !torch.vtensor<[3,6,6,5],f32>) -> !torch.vtensor<[3,6,6,5],f32> return %18 : !torch.vtensor<[3,6,6,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3_sum_weight_high_ii/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3_sum_weight_high_ii/model.mlir index a5ad3fb01..664652df3 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3_sum_weight_high_ii/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3_sum_weight_high_ii/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1d2d3_sum_weight_high_ii(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 10 : si64, torch.onnx.reduction = "sum"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 10 : si64, torch.onnx.reduction = "sum"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3_sum_weight_high_ii_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3_sum_weight_high_ii_expanded/model.mlir index 70f8fcd67..455907ab2 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3_sum_weight_high_ii_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3_sum_weight_high_ii_expanded/model.mlir @@ -1,25 +1,26 @@ module { func.func @test_nllloss_NCd1d2d3_sum_weight_high_ii_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1],si64> - %4 = torch.vtensor.literal(dense<10> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %5 = torch.operator "onnx.Sub"(%3, %3) : (!torch.vtensor<[3,1],si64>, !torch.vtensor<[3,1],si64>) -> !torch.vtensor<[3,1],si64> - %6 = torch.operator "onnx.Cast"(%3) {torch.onnx.to = 7 : si64} : (!torch.vtensor<[3,1],si64>) -> !torch.vtensor<[3,1],si64> - %7 = torch.operator "onnx.Equal"(%6, %4) : (!torch.vtensor<[3,1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1],i1> - %8 = torch.operator "onnx.Where"(%7, %5, %3) : (!torch.vtensor<[3,1],i1>, !torch.vtensor<[3,1],si64>, !torch.vtensor<[3,1],si64>) -> !torch.vtensor<[3,1],si64> - %9 = torch.operator "onnx.GatherElements"(%arg0, %8) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3,1],si64>) -> !torch.vtensor<[3,1],f32> - %10 = torch.vtensor.literal(dense<0.000000e+00> : tensor<1xf32>) : !torch.vtensor<[1],f32> - %11 = torch.operator "onnx.Where"(%7, %10, %9) : (!torch.vtensor<[3,1],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> - %12 = torch.operator "onnx.Neg"(%11) : (!torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> - %13 = torch.operator "onnx.Slice"(%12, %0, %1, %1) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1],f32> - %14 = torch.operator "onnx.Gather"(%arg2, %8) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,1],si64>) -> !torch.vtensor<[3,1],f32> - %15 = torch.operator "onnx.Where"(%7, %10, %14) : (!torch.vtensor<[3,1],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> - %16 = torch.operator "onnx.Squeeze"(%15, %2) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],f32> - %17 = torch.operator "onnx.Squeeze"(%13, %2) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],f32> - %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %19 = torch.operator "onnx.ReduceSum"(%18) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1],si64> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<10> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %5 = torch.operator "onnx.Sub"(%3, %3) : (!torch.vtensor<[3,1],si64>, !torch.vtensor<[3,1],si64>) -> !torch.vtensor<[3,1],si64> + %6 = torch.operator "onnx.Cast"(%3) {torch.onnx.to = 7 : si64} : (!torch.vtensor<[3,1],si64>) -> !torch.vtensor<[3,1],si64> + %7 = torch.operator "onnx.Equal"(%6, %4) : (!torch.vtensor<[3,1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1],i1> + %8 = torch.operator "onnx.Where"(%7, %5, %3) : (!torch.vtensor<[3,1],i1>, !torch.vtensor<[3,1],si64>, !torch.vtensor<[3,1],si64>) -> !torch.vtensor<[3,1],si64> + %9 = torch.operator "onnx.GatherElements"(%arg0, %8) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3,1],si64>) -> !torch.vtensor<[3,1],f32> + %10 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor<1xf32>} : () -> !torch.vtensor<[1],f32> + %11 = torch.operator "onnx.Where"(%7, %10, %9) : (!torch.vtensor<[3,1],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %12 = torch.operator "onnx.Neg"(%11) : (!torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %13 = torch.operator "onnx.Slice"(%12, %0, %1, %1) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1],f32> + %14 = torch.operator "onnx.Gather"(%arg2, %8) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,1],si64>) -> !torch.vtensor<[3,1],f32> + %15 = torch.operator "onnx.Where"(%7, %10, %14) : (!torch.vtensor<[3,1],i1>, !torch.vtensor<[1],f32>, !torch.vtensor<[3,1],f32>) -> !torch.vtensor<[3,1],f32> + %16 = torch.operator "onnx.Squeeze"(%15, %2) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],f32> + %17 = torch.operator "onnx.Squeeze"(%13, %2) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3],f32> + %18 = torch.operator "onnx.Mul"(%17, %16) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %19 = torch.operator "onnx.ReduceSum"(%18) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> return %19 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3d4d5_mean_weight/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3d4d5_mean_weight/model.mlir index bb9981bd4..76901a629 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3d4d5_mean_weight/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3d4d5_mean_weight/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1d2d3d4d5_mean_weight(%arg0: !torch.vtensor<[3,5,6,6,5,3,4],f32>, %arg1: !torch.vtensor<[3,6,6,5,3,4],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3d4d5_mean_weight_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3d4d5_mean_weight_expanded/model.mlir index 02f9821f6..3e4fdea08 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3d4d5_mean_weight_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3d4d5_mean_weight_expanded/model.mlir @@ -1,18 +1,19 @@ module { func.func @test_nllloss_NCd1d2d3d4d5_mean_weight_expanded(%arg0: !torch.vtensor<[3,5,6,6,5,3,4],f32>, %arg1: !torch.vtensor<[3,6,6,5,3,4],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6,5,3,4],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6,5,3,4],si64> - %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3,1,6,6,5,3,4],si64>) -> !torch.vtensor<[3,1,6,6,5,3,4],f32> - %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,6,6,5,3,4],f32>) -> !torch.vtensor<[3,1,6,6,5,3,4],f32> - %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,6,6,5,3,4],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6,5,3,4],f32> - %7 = torch.operator "onnx.Gather"(%arg2, %arg1) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> - %8 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,6,6,5,3,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> - %9 = torch.operator "onnx.Mul"(%8, %7) : (!torch.vtensor<[3,6,6,5,3,4],f32>, !torch.vtensor<[3,6,6,5,3,4],f32>) -> !torch.vtensor<[3,6,6,5,3,4],f32> - %10 = torch.operator "onnx.ReduceSum"(%9) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6,5,3,4],f32>) -> !torch.vtensor<[],f32> - %11 = torch.operator "onnx.ReduceSum"(%7) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6,5,3,4],f32>) -> !torch.vtensor<[],f32> - %12 = torch.operator "onnx.Div"(%10, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6,5,3,4],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6,5,3,4],si64> + %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3,1,6,6,5,3,4],si64>) -> !torch.vtensor<[3,1,6,6,5,3,4],f32> + %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,6,6,5,3,4],f32>) -> !torch.vtensor<[3,1,6,6,5,3,4],f32> + %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,6,6,5,3,4],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6,5,3,4],f32> + %7 = torch.operator "onnx.Gather"(%arg2, %arg1) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> + %8 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,6,6,5,3,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> + %9 = torch.operator "onnx.Mul"(%8, %7) : (!torch.vtensor<[3,6,6,5,3,4],f32>, !torch.vtensor<[3,6,6,5,3,4],f32>) -> !torch.vtensor<[3,6,6,5,3,4],f32> + %10 = torch.operator "onnx.ReduceSum"(%9) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6,5,3,4],f32>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.ReduceSum"(%7) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,6,6,5,3,4],f32>) -> !torch.vtensor<[],f32> + %12 = torch.operator "onnx.Div"(%10, %11) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> return %12 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3d4d5_none_no_weight/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3d4d5_none_no_weight/model.mlir index 234cdb4b6..f17597efd 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3d4d5_none_no_weight/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3d4d5_none_no_weight/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nllloss_NCd1d2d3d4d5_none_no_weight(%arg0: !torch.vtensor<[3,5,6,6,5,3,4],f32>, %arg1: !torch.vtensor<[3,6,6,5,3,4],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%arg0, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> return %0 : !torch.vtensor<[3,6,6,5,3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3d4d5_none_no_weight_expanded/model.mlir b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3d4d5_none_no_weight_expanded/model.mlir index a872cd3d6..6bdc391d6 100644 --- a/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3d4d5_none_no_weight_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_nllloss_NCd1d2d3d4d5_none_no_weight_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_nllloss_NCd1d2d3d4d5_none_no_weight_expanded(%arg0: !torch.vtensor<[3,5,6,6,5,3,4],f32>, %arg1: !torch.vtensor<[3,6,6,5,3,4],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %2 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6,5,3,4],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6,5,3,4],si64> - %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3,1,6,6,5,3,4],si64>) -> !torch.vtensor<[3,1,6,6,5,3,4],f32> - %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,6,6,5,3,4],f32>) -> !torch.vtensor<[3,1,6,6,5,3,4],f32> - %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,6,6,5,3,4],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6,5,3,4],f32> - %7 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,6,6,5,3,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %3 = torch.operator "onnx.Unsqueeze"(%arg1, %2) : (!torch.vtensor<[3,6,6,5,3,4],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6,5,3,4],si64> + %4 = torch.operator "onnx.GatherElements"(%arg0, %3) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3,1,6,6,5,3,4],si64>) -> !torch.vtensor<[3,1,6,6,5,3,4],f32> + %5 = torch.operator "onnx.Neg"(%4) : (!torch.vtensor<[3,1,6,6,5,3,4],f32>) -> !torch.vtensor<[3,1,6,6,5,3,4],f32> + %6 = torch.operator "onnx.Slice"(%5, %0, %1, %1) : (!torch.vtensor<[3,1,6,6,5,3,4],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,6,6,5,3,4],f32> + %7 = torch.operator "onnx.Squeeze"(%6, %2) : (!torch.vtensor<[3,1,6,6,5,3,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> return %7 : !torch.vtensor<[3,6,6,5,3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_nonmaxsuppression_center_point_box_format/model.mlir b/iree_tests/onnx/node/generated/test_nonmaxsuppression_center_point_box_format/model.mlir index c9165f503..a34f99f2c 100644 --- a/iree_tests/onnx/node/generated/test_nonmaxsuppression_center_point_box_format/model.mlir +++ b/iree_tests/onnx/node/generated/test_nonmaxsuppression_center_point_box_format/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nonmaxsuppression_center_point_box_format(%arg0: !torch.vtensor<[1,6,4],f32>, %arg1: !torch.vtensor<[1,1,6],f32>, %arg2: !torch.vtensor<[1],si64>, %arg3: !torch.vtensor<[1],f32>, %arg4: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,3],si64> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) {torch.onnx.center_point_box = 1 : si64} : (!torch.vtensor<[1,6,4],f32>, !torch.vtensor<[1,1,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) {torch.onnx.center_point_box = 1 : si64} : (!torch.vtensor<[1,6,4],f32>, !torch.vtensor<[1,1,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,3],si64> return %0 : !torch.vtensor<[3,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_nonmaxsuppression_flipped_coordinates/model.mlir b/iree_tests/onnx/node/generated/test_nonmaxsuppression_flipped_coordinates/model.mlir index 7cd40daa7..184b8af6a 100644 --- a/iree_tests/onnx/node/generated/test_nonmaxsuppression_flipped_coordinates/model.mlir +++ b/iree_tests/onnx/node/generated/test_nonmaxsuppression_flipped_coordinates/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nonmaxsuppression_flipped_coordinates(%arg0: !torch.vtensor<[1,6,4],f32>, %arg1: !torch.vtensor<[1,1,6],f32>, %arg2: !torch.vtensor<[1],si64>, %arg3: !torch.vtensor<[1],f32>, %arg4: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,3],si64> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[1,6,4],f32>, !torch.vtensor<[1,1,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[1,6,4],f32>, !torch.vtensor<[1,1,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,3],si64> return %0 : !torch.vtensor<[3,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_nonmaxsuppression_identical_boxes/model.mlir b/iree_tests/onnx/node/generated/test_nonmaxsuppression_identical_boxes/model.mlir index 2a7087e6d..63f7890f2 100644 --- a/iree_tests/onnx/node/generated/test_nonmaxsuppression_identical_boxes/model.mlir +++ b/iree_tests/onnx/node/generated/test_nonmaxsuppression_identical_boxes/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nonmaxsuppression_identical_boxes(%arg0: !torch.vtensor<[1,10,4],f32>, %arg1: !torch.vtensor<[1,1,10],f32>, %arg2: !torch.vtensor<[1],si64>, %arg3: !torch.vtensor<[1],f32>, %arg4: !torch.vtensor<[1],f32>) -> !torch.vtensor<[1,3],si64> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[1,10,4],f32>, !torch.vtensor<[1,1,10],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1,3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[1,10,4],f32>, !torch.vtensor<[1,1,10],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1,3],si64> return %0 : !torch.vtensor<[1,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_nonmaxsuppression_limit_output_size/model.mlir b/iree_tests/onnx/node/generated/test_nonmaxsuppression_limit_output_size/model.mlir index 83e13277b..273be8abc 100644 --- a/iree_tests/onnx/node/generated/test_nonmaxsuppression_limit_output_size/model.mlir +++ b/iree_tests/onnx/node/generated/test_nonmaxsuppression_limit_output_size/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nonmaxsuppression_limit_output_size(%arg0: !torch.vtensor<[1,6,4],f32>, %arg1: !torch.vtensor<[1,1,6],f32>, %arg2: !torch.vtensor<[1],si64>, %arg3: !torch.vtensor<[1],f32>, %arg4: !torch.vtensor<[1],f32>) -> !torch.vtensor<[2,3],si64> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[1,6,4],f32>, !torch.vtensor<[1,1,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[2,3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[1,6,4],f32>, !torch.vtensor<[1,1,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[2,3],si64> return %0 : !torch.vtensor<[2,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_nonmaxsuppression_single_box/model.mlir b/iree_tests/onnx/node/generated/test_nonmaxsuppression_single_box/model.mlir index 8d4399a92..c8c3949e6 100644 --- a/iree_tests/onnx/node/generated/test_nonmaxsuppression_single_box/model.mlir +++ b/iree_tests/onnx/node/generated/test_nonmaxsuppression_single_box/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nonmaxsuppression_single_box(%arg0: !torch.vtensor<[1,1,4],f32>, %arg1: !torch.vtensor<[1,1,1],f32>, %arg2: !torch.vtensor<[1],si64>, %arg3: !torch.vtensor<[1],f32>, %arg4: !torch.vtensor<[1],f32>) -> !torch.vtensor<[1,3],si64> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[1,1,4],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1,3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[1,1,4],f32>, !torch.vtensor<[1,1,1],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[1,3],si64> return %0 : !torch.vtensor<[1,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_nonmaxsuppression_suppress_by_IOU/model.mlir b/iree_tests/onnx/node/generated/test_nonmaxsuppression_suppress_by_IOU/model.mlir index c26ee288f..f82e18c60 100644 --- a/iree_tests/onnx/node/generated/test_nonmaxsuppression_suppress_by_IOU/model.mlir +++ b/iree_tests/onnx/node/generated/test_nonmaxsuppression_suppress_by_IOU/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nonmaxsuppression_suppress_by_IOU(%arg0: !torch.vtensor<[1,6,4],f32>, %arg1: !torch.vtensor<[1,1,6],f32>, %arg2: !torch.vtensor<[1],si64>, %arg3: !torch.vtensor<[1],f32>, %arg4: !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,3],si64> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[1,6,4],f32>, !torch.vtensor<[1,1,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[1,6,4],f32>, !torch.vtensor<[1,1,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[3,3],si64> return %0 : !torch.vtensor<[3,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_nonmaxsuppression_suppress_by_IOU_and_scores/model.mlir b/iree_tests/onnx/node/generated/test_nonmaxsuppression_suppress_by_IOU_and_scores/model.mlir index 2d2c3bee8..05dcb5ddf 100644 --- a/iree_tests/onnx/node/generated/test_nonmaxsuppression_suppress_by_IOU_and_scores/model.mlir +++ b/iree_tests/onnx/node/generated/test_nonmaxsuppression_suppress_by_IOU_and_scores/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nonmaxsuppression_suppress_by_IOU_and_scores(%arg0: !torch.vtensor<[1,6,4],f32>, %arg1: !torch.vtensor<[1,1,6],f32>, %arg2: !torch.vtensor<[1],si64>, %arg3: !torch.vtensor<[1],f32>, %arg4: !torch.vtensor<[1],f32>) -> !torch.vtensor<[2,3],si64> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[1,6,4],f32>, !torch.vtensor<[1,1,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[2,3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[1,6,4],f32>, !torch.vtensor<[1,1,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[2,3],si64> return %0 : !torch.vtensor<[2,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_nonmaxsuppression_two_batches/model.mlir b/iree_tests/onnx/node/generated/test_nonmaxsuppression_two_batches/model.mlir index 80a178153..18904ddbf 100644 --- a/iree_tests/onnx/node/generated/test_nonmaxsuppression_two_batches/model.mlir +++ b/iree_tests/onnx/node/generated/test_nonmaxsuppression_two_batches/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nonmaxsuppression_two_batches(%arg0: !torch.vtensor<[2,6,4],f32>, %arg1: !torch.vtensor<[2,1,6],f32>, %arg2: !torch.vtensor<[1],si64>, %arg3: !torch.vtensor<[1],f32>, %arg4: !torch.vtensor<[1],f32>) -> !torch.vtensor<[4,3],si64> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[2,6,4],f32>, !torch.vtensor<[2,1,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[4,3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[2,6,4],f32>, !torch.vtensor<[2,1,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[4,3],si64> return %0 : !torch.vtensor<[4,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_nonmaxsuppression_two_classes/model.mlir b/iree_tests/onnx/node/generated/test_nonmaxsuppression_two_classes/model.mlir index f23ade863..b1f4f3262 100644 --- a/iree_tests/onnx/node/generated/test_nonmaxsuppression_two_classes/model.mlir +++ b/iree_tests/onnx/node/generated/test_nonmaxsuppression_two_classes/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nonmaxsuppression_two_classes(%arg0: !torch.vtensor<[1,6,4],f32>, %arg1: !torch.vtensor<[1,2,6],f32>, %arg2: !torch.vtensor<[1],si64>, %arg3: !torch.vtensor<[1],f32>, %arg4: !torch.vtensor<[1],f32>) -> !torch.vtensor<[4,3],si64> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[1,6,4],f32>, !torch.vtensor<[1,2,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[4,3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.NonMaxSuppression"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[1,6,4],f32>, !torch.vtensor<[1,2,6],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],f32>) -> !torch.vtensor<[4,3],si64> return %0 : !torch.vtensor<[4,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_nonzero_example/model.mlir b/iree_tests/onnx/node/generated/test_nonzero_example/model.mlir index 2f2799be9..d9208405d 100644 --- a/iree_tests/onnx/node/generated/test_nonzero_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_nonzero_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_nonzero_example(%arg0: !torch.vtensor<[2,2],i1>) -> !torch.vtensor<[2,3],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.NonZero"(%arg0) : (!torch.vtensor<[2,2],i1>) -> !torch.vtensor<[2,3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.NonZero"(%arg0) : (!torch.vtensor<[2,2],i1>) -> !torch.vtensor<[2,3],si64> return %0 : !torch.vtensor<[2,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_not_2d/model.mlir b/iree_tests/onnx/node/generated/test_not_2d/model.mlir index db5b86e95..8eb05ec25 100644 --- a/iree_tests/onnx/node/generated/test_not_2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_not_2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_not_2d(%arg0: !torch.vtensor<[3,4],i1>) -> !torch.vtensor<[3,4],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 1 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Not"(%arg0) : (!torch.vtensor<[3,4],i1>) -> !torch.vtensor<[3,4],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Not"(%arg0) : (!torch.vtensor<[3,4],i1>) -> !torch.vtensor<[3,4],i1> return %0 : !torch.vtensor<[3,4],i1> } } diff --git a/iree_tests/onnx/node/generated/test_not_3d/model.mlir b/iree_tests/onnx/node/generated/test_not_3d/model.mlir index b22da4812..5eb03e127 100644 --- a/iree_tests/onnx/node/generated/test_not_3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_not_3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_not_3d(%arg0: !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 1 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Not"(%arg0) : (!torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Not"(%arg0) : (!torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_not_4d/model.mlir b/iree_tests/onnx/node/generated/test_not_4d/model.mlir index bc58745ec..4b67dcd49 100644 --- a/iree_tests/onnx/node/generated/test_not_4d/model.mlir +++ b/iree_tests/onnx/node/generated/test_not_4d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_not_4d(%arg0: !torch.vtensor<[3,4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 1 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Not"(%arg0) : (!torch.vtensor<[3,4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Not"(%arg0) : (!torch.vtensor<[3,4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> return %0 : !torch.vtensor<[3,4,5,6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_onehot_negative_indices/model.mlir b/iree_tests/onnx/node/generated/test_onehot_negative_indices/model.mlir index e62b97667..cec245eee 100644 --- a/iree_tests/onnx/node/generated/test_onehot_negative_indices/model.mlir +++ b/iree_tests/onnx/node/generated/test_onehot_negative_indices/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_onehot_negative_indices(%arg0: !torch.vtensor<[3],si64>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[2],f32>) -> !torch.vtensor<[3,10],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.OneHot"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3],si64>, !torch.vtensor<[],f32>, !torch.vtensor<[2],f32>) -> !torch.vtensor<[3,10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.OneHot"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3],si64>, !torch.vtensor<[],f32>, !torch.vtensor<[2],f32>) -> !torch.vtensor<[3,10],f32> return %0 : !torch.vtensor<[3,10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_onehot_with_axis/model.mlir b/iree_tests/onnx/node/generated/test_onehot_with_axis/model.mlir index f533ba62d..f7447936e 100644 --- a/iree_tests/onnx/node/generated/test_onehot_with_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_onehot_with_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_onehot_with_axis(%arg0: !torch.vtensor<[2,2],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[2],f32>) -> !torch.vtensor<[2,10,2],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.OneHot"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,2],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[2],f32>) -> !torch.vtensor<[2,10,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.OneHot"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,2],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[2],f32>) -> !torch.vtensor<[2,10,2],f32> return %0 : !torch.vtensor<[2,10,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_onehot_with_negative_axis/model.mlir b/iree_tests/onnx/node/generated/test_onehot_with_negative_axis/model.mlir index 4b1e199f7..d1d7e2a7e 100644 --- a/iree_tests/onnx/node/generated/test_onehot_with_negative_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_onehot_with_negative_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_onehot_with_negative_axis(%arg0: !torch.vtensor<[2,2],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[2],f32>) -> !torch.vtensor<[2,10,2],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.OneHot"(%arg0, %arg1, %arg2) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[2,2],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[2],f32>) -> !torch.vtensor<[2,10,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.OneHot"(%arg0, %arg1, %arg2) {torch.onnx.axis = -2 : si64} : (!torch.vtensor<[2,2],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[2],f32>) -> !torch.vtensor<[2,10,2],f32> return %0 : !torch.vtensor<[2,10,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_onehot_without_axis/model.mlir b/iree_tests/onnx/node/generated/test_onehot_without_axis/model.mlir index 269cd705e..da2ccd1b1 100644 --- a/iree_tests/onnx/node/generated/test_onehot_without_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_onehot_without_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_onehot_without_axis(%arg0: !torch.vtensor<[3],si64>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[2],si32>) -> !torch.vtensor<[3,12],si32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.OneHot"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],si64>, !torch.vtensor<[],f32>, !torch.vtensor<[2],si32>) -> !torch.vtensor<[3,12],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.OneHot"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],si64>, !torch.vtensor<[],f32>, !torch.vtensor<[2],si32>) -> !torch.vtensor<[3,12],si32> return %0 : !torch.vtensor<[3,12],si32> } } diff --git a/iree_tests/onnx/node/generated/test_optional_get_element_tensor/model.mlir b/iree_tests/onnx/node/generated/test_optional_get_element_tensor/model.mlir index f542fc376..363de512a 100644 --- a/iree_tests/onnx/node/generated/test_optional_get_element_tensor/model.mlir +++ b/iree_tests/onnx/node/generated/test_optional_get_element_tensor/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_optional_get_element_tensor(%arg0: !torch.vtensor<[4],f32>) -> !torch.vtensor<[4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.OptionalGetElement"(%arg0) : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.OptionalGetElement"(%arg0) : (!torch.vtensor<[4],f32>) -> !torch.vtensor<[4],f32> return %0 : !torch.vtensor<[4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_optional_input/model.mlir b/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_optional_input/model.mlir new file mode 100644 index 000000000..88a2ebb86 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_optional_input/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_optional_has_element_empty_no_input_name_optional_input() -> !torch.vtensor<[],i1> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.OptionalHasElement"(%none) : (!torch.none) -> !torch.vtensor<[],i1> + return %0 : !torch.vtensor<[],i1> + } +} + diff --git a/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_optional_input/output_0.npy b/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_optional_input/output_0.npy new file mode 100644 index 000000000..185568c8e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_optional_input/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_optional_input/test_data_flags.txt b/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_optional_input/test_data_flags.txt new file mode 100644 index 000000000..2b0550b8b --- /dev/null +++ b/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_optional_input/test_data_flags.txt @@ -0,0 +1 @@ +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_tensor_input/model.mlir b/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_tensor_input/model.mlir new file mode 100644 index 000000000..6aff7d551 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_tensor_input/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_optional_has_element_empty_no_input_name_tensor_input() -> !torch.vtensor<[],i1> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.OptionalHasElement"(%none) : (!torch.none) -> !torch.vtensor<[],i1> + return %0 : !torch.vtensor<[],i1> + } +} + diff --git a/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_tensor_input/output_0.npy b/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_tensor_input/output_0.npy new file mode 100644 index 000000000..185568c8e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_tensor_input/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_tensor_input/test_data_flags.txt b/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_tensor_input/test_data_flags.txt new file mode 100644 index 000000000..2b0550b8b --- /dev/null +++ b/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_name_tensor_input/test_data_flags.txt @@ -0,0 +1 @@ +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_optional_input/model.mlir b/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_optional_input/model.mlir index 8ef6e41bb..53bc733aa 100644 --- a/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_optional_input/model.mlir +++ b/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_optional_input/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_optional_has_element_empty_no_input_optional_input() -> !torch.vtensor<[],i1> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.OptionalHasElement"() : () -> !torch.vtensor<[],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.OptionalHasElement"() : () -> !torch.vtensor<[],i1> return %0 : !torch.vtensor<[],i1> } } diff --git a/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_tensor_input/model.mlir b/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_tensor_input/model.mlir index 49ff8afed..efc10c01c 100644 --- a/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_tensor_input/model.mlir +++ b/iree_tests/onnx/node/generated/test_optional_has_element_empty_no_input_tensor_input/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_optional_has_element_empty_no_input_tensor_input() -> !torch.vtensor<[],i1> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.OptionalHasElement"() : () -> !torch.vtensor<[],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.OptionalHasElement"() : () -> !torch.vtensor<[],i1> return %0 : !torch.vtensor<[],i1> } } diff --git a/iree_tests/onnx/node/generated/test_or2d/model.mlir b/iree_tests/onnx/node/generated/test_or2d/model.mlir index 668259a83..6f26dd73d 100644 --- a/iree_tests/onnx/node/generated/test_or2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_or2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_or2d(%arg0: !torch.vtensor<[3,4],i1>, %arg1: !torch.vtensor<[3,4],i1>) -> !torch.vtensor<[3,4],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Or"(%arg0, %arg1) : (!torch.vtensor<[3,4],i1>, !torch.vtensor<[3,4],i1>) -> !torch.vtensor<[3,4],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Or"(%arg0, %arg1) : (!torch.vtensor<[3,4],i1>, !torch.vtensor<[3,4],i1>) -> !torch.vtensor<[3,4],i1> return %0 : !torch.vtensor<[3,4],i1> } } diff --git a/iree_tests/onnx/node/generated/test_or3d/model.mlir b/iree_tests/onnx/node/generated/test_or3d/model.mlir index 353b0daec..e5922d774 100644 --- a/iree_tests/onnx/node/generated/test_or3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_or3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_or3d(%arg0: !torch.vtensor<[3,4,5],i1>, %arg1: !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Or"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Or"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_or4d/model.mlir b/iree_tests/onnx/node/generated/test_or4d/model.mlir index c208dae74..b5cc460a1 100644 --- a/iree_tests/onnx/node/generated/test_or4d/model.mlir +++ b/iree_tests/onnx/node/generated/test_or4d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_or4d(%arg0: !torch.vtensor<[3,4,5,6],i1>, %arg1: !torch.vtensor<[3,4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Or"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[3,4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Or"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[3,4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> return %0 : !torch.vtensor<[3,4,5,6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_or_bcast3v1d/model.mlir b/iree_tests/onnx/node/generated/test_or_bcast3v1d/model.mlir index 4e962d226..e2f3ef9d0 100644 --- a/iree_tests/onnx/node/generated/test_or_bcast3v1d/model.mlir +++ b/iree_tests/onnx/node/generated/test_or_bcast3v1d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_or_bcast3v1d(%arg0: !torch.vtensor<[3,4,5],i1>, %arg1: !torch.vtensor<[5],i1>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Or"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[5],i1>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Or"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[5],i1>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_or_bcast3v2d/model.mlir b/iree_tests/onnx/node/generated/test_or_bcast3v2d/model.mlir index e393f8057..e8e17070e 100644 --- a/iree_tests/onnx/node/generated/test_or_bcast3v2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_or_bcast3v2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_or_bcast3v2d(%arg0: !torch.vtensor<[3,4,5],i1>, %arg1: !torch.vtensor<[4,5],i1>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Or"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[4,5],i1>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Or"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[4,5],i1>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_or_bcast4v2d/model.mlir b/iree_tests/onnx/node/generated/test_or_bcast4v2d/model.mlir index 469e885a7..0f1b48ba9 100644 --- a/iree_tests/onnx/node/generated/test_or_bcast4v2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_or_bcast4v2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_or_bcast4v2d(%arg0: !torch.vtensor<[3,4,5,6],i1>, %arg1: !torch.vtensor<[5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Or"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Or"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> return %0 : !torch.vtensor<[3,4,5,6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_or_bcast4v3d/model.mlir b/iree_tests/onnx/node/generated/test_or_bcast4v3d/model.mlir index 0678ab538..86b1ec913 100644 --- a/iree_tests/onnx/node/generated/test_or_bcast4v3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_or_bcast4v3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_or_bcast4v3d(%arg0: !torch.vtensor<[3,4,5,6],i1>, %arg1: !torch.vtensor<[4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Or"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Or"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> return %0 : !torch.vtensor<[3,4,5,6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_or_bcast4v4d/model.mlir b/iree_tests/onnx/node/generated/test_or_bcast4v4d/model.mlir index 5dcefe3df..c1371aeb5 100644 --- a/iree_tests/onnx/node/generated/test_or_bcast4v4d/model.mlir +++ b/iree_tests/onnx/node/generated/test_or_bcast4v4d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_or_bcast4v4d(%arg0: !torch.vtensor<[1,4,1,6],i1>, %arg1: !torch.vtensor<[3,1,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Or"(%arg0, %arg1) : (!torch.vtensor<[1,4,1,6],i1>, !torch.vtensor<[3,1,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Or"(%arg0, %arg1) : (!torch.vtensor<[1,4,1,6],i1>, !torch.vtensor<[3,1,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> return %0 : !torch.vtensor<[3,4,5,6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_pow/model.mlir b/iree_tests/onnx/node/generated/test_pow/model.mlir index 58a3a8886..5b9267a33 100644 --- a/iree_tests/onnx/node/generated/test_pow/model.mlir +++ b/iree_tests/onnx/node/generated/test_pow/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_pow(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_pow_bcast_array/model.mlir b/iree_tests/onnx/node/generated/test_pow_bcast_array/model.mlir index 84a2bd403..7c2cbcf6d 100644 --- a/iree_tests/onnx/node/generated/test_pow_bcast_array/model.mlir +++ b/iree_tests/onnx/node/generated/test_pow_bcast_array/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_pow_bcast_array(%arg0: !torch.vtensor<[2,3],f32>, %arg1: !torch.vtensor<[3],f32>) -> !torch.vtensor<[2,3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[2,3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[2,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[2,3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[2,3],f32> return %0 : !torch.vtensor<[2,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_pow_bcast_scalar/model.mlir b/iree_tests/onnx/node/generated/test_pow_bcast_scalar/model.mlir index b849cee12..1ee5beb98 100644 --- a/iree_tests/onnx/node/generated/test_pow_bcast_scalar/model.mlir +++ b/iree_tests/onnx/node/generated/test_pow_bcast_scalar/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_pow_bcast_scalar(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_pow_example/model.mlir b/iree_tests/onnx/node/generated/test_pow_example/model.mlir index fc4832f8a..a3dc669a3 100644 --- a/iree_tests/onnx/node/generated/test_pow_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_pow_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_pow_example(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_pow_types_float32_int32/model.mlir b/iree_tests/onnx/node/generated/test_pow_types_float32_int32/model.mlir index 8365bf5e1..30e5517f9 100644 --- a/iree_tests/onnx/node/generated/test_pow_types_float32_int32/model.mlir +++ b/iree_tests/onnx/node/generated/test_pow_types_float32_int32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_pow_types_float32_int32(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],si32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],si32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],si32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_pow_types_float32_int64/model.mlir b/iree_tests/onnx/node/generated/test_pow_types_float32_int64/model.mlir index af0757afb..e242c1b71 100644 --- a/iree_tests/onnx/node/generated/test_pow_types_float32_int64/model.mlir +++ b/iree_tests/onnx/node/generated/test_pow_types_float32_int64/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_pow_types_float32_int64(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_pow_types_float32_uint32/model.mlir b/iree_tests/onnx/node/generated/test_pow_types_float32_uint32/model.mlir index 3ae698394..a7e178d82 100644 --- a/iree_tests/onnx/node/generated/test_pow_types_float32_uint32/model.mlir +++ b/iree_tests/onnx/node/generated/test_pow_types_float32_uint32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_pow_types_float32_uint32(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],ui32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_pow_types_float32_uint64/model.mlir b/iree_tests/onnx/node/generated/test_pow_types_float32_uint64/model.mlir index 244fb9358..4ab20a901 100644 --- a/iree_tests/onnx/node/generated/test_pow_types_float32_uint64/model.mlir +++ b/iree_tests/onnx/node/generated/test_pow_types_float32_uint64/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_pow_types_float32_uint64(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],ui64>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_pow_types_int32_float32/model.mlir b/iree_tests/onnx/node/generated/test_pow_types_int32_float32/model.mlir index 2ddf0fe33..b81e8e08d 100644 --- a/iree_tests/onnx/node/generated/test_pow_types_int32_float32/model.mlir +++ b/iree_tests/onnx/node/generated/test_pow_types_int32_float32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_pow_types_int32_float32(%arg0: !torch.vtensor<[3],si32>, %arg1: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],si32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],si32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],si32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],si32> return %0 : !torch.vtensor<[3],si32> } } diff --git a/iree_tests/onnx/node/generated/test_pow_types_int32_int32/model.mlir b/iree_tests/onnx/node/generated/test_pow_types_int32_int32/model.mlir index 0be4a9f85..d192726b1 100644 --- a/iree_tests/onnx/node/generated/test_pow_types_int32_int32/model.mlir +++ b/iree_tests/onnx/node/generated/test_pow_types_int32_int32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_pow_types_int32_int32(%arg0: !torch.vtensor<[3],si32>, %arg1: !torch.vtensor<[3],si32>) -> !torch.vtensor<[3],si32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],si32>, !torch.vtensor<[3],si32>) -> !torch.vtensor<[3],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],si32>, !torch.vtensor<[3],si32>) -> !torch.vtensor<[3],si32> return %0 : !torch.vtensor<[3],si32> } } diff --git a/iree_tests/onnx/node/generated/test_pow_types_int64_float32/model.mlir b/iree_tests/onnx/node/generated/test_pow_types_int64_float32/model.mlir index 1fd0a36a0..6b36d388e 100644 --- a/iree_tests/onnx/node/generated/test_pow_types_int64_float32/model.mlir +++ b/iree_tests/onnx/node/generated/test_pow_types_int64_float32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_pow_types_int64_float32(%arg0: !torch.vtensor<[3],si64>, %arg1: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],si64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],si64> return %0 : !torch.vtensor<[3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_pow_types_int64_int64/model.mlir b/iree_tests/onnx/node/generated/test_pow_types_int64_int64/model.mlir index da15f2748..594b5ae42 100644 --- a/iree_tests/onnx/node/generated/test_pow_types_int64_int64/model.mlir +++ b/iree_tests/onnx/node/generated/test_pow_types_int64_int64/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_pow_types_int64_int64(%arg0: !torch.vtensor<[3],si64>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 15 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Pow"(%arg0, %arg1) : (!torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],si64> return %0 : !torch.vtensor<[3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_prelu_broadcast/model.mlir b/iree_tests/onnx/node/generated/test_prelu_broadcast/model.mlir index 1d3ace3cb..3f095203c 100644 --- a/iree_tests/onnx/node/generated/test_prelu_broadcast/model.mlir +++ b/iree_tests/onnx/node/generated/test_prelu_broadcast/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_prelu_broadcast(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.PRelu"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.PRelu"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_prelu_broadcast_expanded/model.mlir b/iree_tests/onnx/node/generated/test_prelu_broadcast_expanded/model.mlir index ea4cca457..d54204555 100644 --- a/iree_tests/onnx/node/generated/test_prelu_broadcast_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_prelu_broadcast_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_prelu_broadcast_expanded(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Less"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> - %3 = torch.operator "onnx.Mul"(%arg1, %arg0) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.Where"(%2, %3, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Less"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> + %3 = torch.operator "onnx.Mul"(%arg1, %arg0) : (!torch.vtensor<[5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.Where"(%2, %3, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %4 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_prelu_example/model.mlir b/iree_tests/onnx/node/generated/test_prelu_example/model.mlir index 5a694fe58..a843be50d 100644 --- a/iree_tests/onnx/node/generated/test_prelu_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_prelu_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_prelu_example(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.PRelu"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.PRelu"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_prelu_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_prelu_example_expanded/model.mlir index 0197b1141..69d32f752 100644 --- a/iree_tests/onnx/node/generated/test_prelu_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_prelu_example_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_prelu_example_expanded(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Less"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> - %3 = torch.operator "onnx.Mul"(%arg1, %arg0) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.Where"(%2, %3, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Less"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> + %3 = torch.operator "onnx.Mul"(%arg1, %arg0) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.Where"(%2, %3, %arg0) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %4 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_qlinearconv/model.mlir b/iree_tests/onnx/node/generated/test_qlinearconv/model.mlir index 0567589a9..f3b3e7eef 100644 --- a/iree_tests/onnx/node/generated/test_qlinearconv/model.mlir +++ b/iree_tests/onnx/node/generated/test_qlinearconv/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_qlinearconv(%arg0: !torch.vtensor<[1,1,7,7],ui8>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],ui8>, %arg3: !torch.vtensor<[1,1,1,1],ui8>, %arg4: !torch.vtensor<[1],f32>, %arg5: !torch.vtensor<[1],ui8>, %arg6: !torch.vtensor<[],f32>, %arg7: !torch.vtensor<[],ui8>) -> !torch.vtensor<[1,1,7,7],ui8> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.QLinearConv"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[1,1,7,7],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>, !torch.vtensor<[1,1,1,1],ui8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) -> !torch.vtensor<[1,1,7,7],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.QLinearConv"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[1,1,7,7],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>, !torch.vtensor<[1,1,1,1],ui8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],ui8>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) -> !torch.vtensor<[1,1,7,7],ui8> return %0 : !torch.vtensor<[1,1,7,7],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_qlinearmatmul_2D_int8_float16/model.mlir b/iree_tests/onnx/node/generated/test_qlinearmatmul_2D_int8_float16/model.mlir index 7ab32295b..4932f0f93 100644 --- a/iree_tests/onnx/node/generated/test_qlinearmatmul_2D_int8_float16/model.mlir +++ b/iree_tests/onnx/node/generated/test_qlinearmatmul_2D_int8_float16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_qlinearmatmul_2D_int8_float16(%arg0: !torch.vtensor<[2,4],si8>, %arg1: !torch.vtensor<[1],f16>, %arg2: !torch.vtensor<[1],si8>, %arg3: !torch.vtensor<[4,3],si8>, %arg4: !torch.vtensor<[1],f16>, %arg5: !torch.vtensor<[1],si8>, %arg6: !torch.vtensor<[1],f16>, %arg7: !torch.vtensor<[1],si8>) -> !torch.vtensor<[2,3],si8> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.QLinearMatMul"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[2,4],si8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],si8>, !torch.vtensor<[4,3],si8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],si8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],si8>) -> !torch.vtensor<[2,3],si8> + %none = torch.constant.none + %0 = torch.operator "onnx.QLinearMatMul"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[2,4],si8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],si8>, !torch.vtensor<[4,3],si8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],si8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],si8>) -> !torch.vtensor<[2,3],si8> return %0 : !torch.vtensor<[2,3],si8> } } diff --git a/iree_tests/onnx/node/generated/test_qlinearmatmul_2D_int8_float32/model.mlir b/iree_tests/onnx/node/generated/test_qlinearmatmul_2D_int8_float32/model.mlir index f1a856e10..b07f98b79 100644 --- a/iree_tests/onnx/node/generated/test_qlinearmatmul_2D_int8_float32/model.mlir +++ b/iree_tests/onnx/node/generated/test_qlinearmatmul_2D_int8_float32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_qlinearmatmul_2D_int8_float32(%arg0: !torch.vtensor<[2,4],si8>, %arg1: !torch.vtensor<[1],f32>, %arg2: !torch.vtensor<[1],si8>, %arg3: !torch.vtensor<[4,3],si8>, %arg4: !torch.vtensor<[1],f32>, %arg5: !torch.vtensor<[1],si8>, %arg6: !torch.vtensor<[1],f32>, %arg7: !torch.vtensor<[1],si8>) -> !torch.vtensor<[2,3],si8> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.QLinearMatMul"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[2,4],si8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],si8>, !torch.vtensor<[4,3],si8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],si8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],si8>) -> !torch.vtensor<[2,3],si8> + %none = torch.constant.none + %0 = torch.operator "onnx.QLinearMatMul"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[2,4],si8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],si8>, !torch.vtensor<[4,3],si8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],si8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],si8>) -> !torch.vtensor<[2,3],si8> return %0 : !torch.vtensor<[2,3],si8> } } diff --git a/iree_tests/onnx/node/generated/test_qlinearmatmul_2D_uint8_float16/model.mlir b/iree_tests/onnx/node/generated/test_qlinearmatmul_2D_uint8_float16/model.mlir index e327e32b4..7ac564c7f 100644 --- a/iree_tests/onnx/node/generated/test_qlinearmatmul_2D_uint8_float16/model.mlir +++ b/iree_tests/onnx/node/generated/test_qlinearmatmul_2D_uint8_float16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_qlinearmatmul_2D_uint8_float16(%arg0: !torch.vtensor<[2,4],ui8>, %arg1: !torch.vtensor<[1],f16>, %arg2: !torch.vtensor<[1],ui8>, %arg3: !torch.vtensor<[4,3],ui8>, %arg4: !torch.vtensor<[1],f16>, %arg5: !torch.vtensor<[1],ui8>, %arg6: !torch.vtensor<[1],f16>, %arg7: !torch.vtensor<[1],ui8>) -> !torch.vtensor<[2,3],ui8> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.QLinearMatMul"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[2,4],ui8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],ui8>, !torch.vtensor<[4,3],ui8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],ui8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],ui8>) -> !torch.vtensor<[2,3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.QLinearMatMul"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[2,4],ui8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],ui8>, !torch.vtensor<[4,3],ui8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],ui8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],ui8>) -> !torch.vtensor<[2,3],ui8> return %0 : !torch.vtensor<[2,3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_qlinearmatmul_2D_uint8_float32/model.mlir b/iree_tests/onnx/node/generated/test_qlinearmatmul_2D_uint8_float32/model.mlir index c5beaad1b..a18b3634a 100644 --- a/iree_tests/onnx/node/generated/test_qlinearmatmul_2D_uint8_float32/model.mlir +++ b/iree_tests/onnx/node/generated/test_qlinearmatmul_2D_uint8_float32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_qlinearmatmul_2D_uint8_float32(%arg0: !torch.vtensor<[2,4],ui8>, %arg1: !torch.vtensor<[1],f32>, %arg2: !torch.vtensor<[1],ui8>, %arg3: !torch.vtensor<[4,3],ui8>, %arg4: !torch.vtensor<[1],f32>, %arg5: !torch.vtensor<[1],ui8>, %arg6: !torch.vtensor<[1],f32>, %arg7: !torch.vtensor<[1],ui8>) -> !torch.vtensor<[2,3],ui8> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.QLinearMatMul"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[2,4],ui8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],ui8>, !torch.vtensor<[4,3],ui8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],ui8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],ui8>) -> !torch.vtensor<[2,3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.QLinearMatMul"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[2,4],ui8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],ui8>, !torch.vtensor<[4,3],ui8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],ui8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],ui8>) -> !torch.vtensor<[2,3],ui8> return %0 : !torch.vtensor<[2,3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_qlinearmatmul_3D_int8_float16/model.mlir b/iree_tests/onnx/node/generated/test_qlinearmatmul_3D_int8_float16/model.mlir index faa0d1fdf..dc2fcca82 100644 --- a/iree_tests/onnx/node/generated/test_qlinearmatmul_3D_int8_float16/model.mlir +++ b/iree_tests/onnx/node/generated/test_qlinearmatmul_3D_int8_float16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_qlinearmatmul_3D_int8_float16(%arg0: !torch.vtensor<[2,2,4],si8>, %arg1: !torch.vtensor<[1],f16>, %arg2: !torch.vtensor<[1],si8>, %arg3: !torch.vtensor<[2,4,3],si8>, %arg4: !torch.vtensor<[1],f16>, %arg5: !torch.vtensor<[1],si8>, %arg6: !torch.vtensor<[1],f16>, %arg7: !torch.vtensor<[1],si8>) -> !torch.vtensor<[2,2,3],si8> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.QLinearMatMul"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[2,2,4],si8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],si8>, !torch.vtensor<[2,4,3],si8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],si8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],si8>) -> !torch.vtensor<[2,2,3],si8> + %none = torch.constant.none + %0 = torch.operator "onnx.QLinearMatMul"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[2,2,4],si8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],si8>, !torch.vtensor<[2,4,3],si8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],si8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],si8>) -> !torch.vtensor<[2,2,3],si8> return %0 : !torch.vtensor<[2,2,3],si8> } } diff --git a/iree_tests/onnx/node/generated/test_qlinearmatmul_3D_int8_float32/model.mlir b/iree_tests/onnx/node/generated/test_qlinearmatmul_3D_int8_float32/model.mlir index a4de987c8..c730c3394 100644 --- a/iree_tests/onnx/node/generated/test_qlinearmatmul_3D_int8_float32/model.mlir +++ b/iree_tests/onnx/node/generated/test_qlinearmatmul_3D_int8_float32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_qlinearmatmul_3D_int8_float32(%arg0: !torch.vtensor<[2,2,4],si8>, %arg1: !torch.vtensor<[1],f32>, %arg2: !torch.vtensor<[1],si8>, %arg3: !torch.vtensor<[2,4,3],si8>, %arg4: !torch.vtensor<[1],f32>, %arg5: !torch.vtensor<[1],si8>, %arg6: !torch.vtensor<[1],f32>, %arg7: !torch.vtensor<[1],si8>) -> !torch.vtensor<[2,2,3],si8> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.QLinearMatMul"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[2,2,4],si8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],si8>, !torch.vtensor<[2,4,3],si8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],si8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],si8>) -> !torch.vtensor<[2,2,3],si8> + %none = torch.constant.none + %0 = torch.operator "onnx.QLinearMatMul"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[2,2,4],si8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],si8>, !torch.vtensor<[2,4,3],si8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],si8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],si8>) -> !torch.vtensor<[2,2,3],si8> return %0 : !torch.vtensor<[2,2,3],si8> } } diff --git a/iree_tests/onnx/node/generated/test_qlinearmatmul_3D_uint8_float16/model.mlir b/iree_tests/onnx/node/generated/test_qlinearmatmul_3D_uint8_float16/model.mlir index 18bcf0cee..9ef2b4385 100644 --- a/iree_tests/onnx/node/generated/test_qlinearmatmul_3D_uint8_float16/model.mlir +++ b/iree_tests/onnx/node/generated/test_qlinearmatmul_3D_uint8_float16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_qlinearmatmul_3D_uint8_float16(%arg0: !torch.vtensor<[2,2,4],ui8>, %arg1: !torch.vtensor<[1],f16>, %arg2: !torch.vtensor<[1],ui8>, %arg3: !torch.vtensor<[2,4,3],ui8>, %arg4: !torch.vtensor<[1],f16>, %arg5: !torch.vtensor<[1],ui8>, %arg6: !torch.vtensor<[1],f16>, %arg7: !torch.vtensor<[1],ui8>) -> !torch.vtensor<[2,2,3],ui8> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.QLinearMatMul"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[2,2,4],ui8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],ui8>, !torch.vtensor<[2,4,3],ui8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],ui8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],ui8>) -> !torch.vtensor<[2,2,3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.QLinearMatMul"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[2,2,4],ui8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],ui8>, !torch.vtensor<[2,4,3],ui8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],ui8>, !torch.vtensor<[1],f16>, !torch.vtensor<[1],ui8>) -> !torch.vtensor<[2,2,3],ui8> return %0 : !torch.vtensor<[2,2,3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_qlinearmatmul_3D_uint8_float32/model.mlir b/iree_tests/onnx/node/generated/test_qlinearmatmul_3D_uint8_float32/model.mlir index e2144b743..ab52dc3cc 100644 --- a/iree_tests/onnx/node/generated/test_qlinearmatmul_3D_uint8_float32/model.mlir +++ b/iree_tests/onnx/node/generated/test_qlinearmatmul_3D_uint8_float32/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_qlinearmatmul_3D_uint8_float32(%arg0: !torch.vtensor<[2,2,4],ui8>, %arg1: !torch.vtensor<[1],f32>, %arg2: !torch.vtensor<[1],ui8>, %arg3: !torch.vtensor<[2,4,3],ui8>, %arg4: !torch.vtensor<[1],f32>, %arg5: !torch.vtensor<[1],ui8>, %arg6: !torch.vtensor<[1],f32>, %arg7: !torch.vtensor<[1],ui8>) -> !torch.vtensor<[2,2,3],ui8> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.QLinearMatMul"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[2,2,4],ui8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],ui8>, !torch.vtensor<[2,4,3],ui8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],ui8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],ui8>) -> !torch.vtensor<[2,2,3],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.QLinearMatMul"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7) : (!torch.vtensor<[2,2,4],ui8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],ui8>, !torch.vtensor<[2,4,3],ui8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],ui8>, !torch.vtensor<[1],f32>, !torch.vtensor<[1],ui8>) -> !torch.vtensor<[2,2,3],ui8> return %0 : !torch.vtensor<[2,2,3],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_quantizelinear/model.mlir b/iree_tests/onnx/node/generated/test_quantizelinear/model.mlir index 0e885f660..e50f1908a 100644 --- a/iree_tests/onnx/node/generated/test_quantizelinear/model.mlir +++ b/iree_tests/onnx/node/generated/test_quantizelinear/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_quantizelinear(%arg0: !torch.vtensor<[6],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],ui8>) -> !torch.vtensor<[6],ui8> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.QuantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[6],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) -> !torch.vtensor<[6],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.QuantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[6],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui8>) -> !torch.vtensor<[6],ui8> return %0 : !torch.vtensor<[6],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_quantizelinear_axis/model.mlir b/iree_tests/onnx/node/generated/test_quantizelinear_axis/model.mlir index 3225df11f..e12d13728 100644 --- a/iree_tests/onnx/node/generated/test_quantizelinear_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_quantizelinear_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_quantizelinear_axis(%arg0: !torch.vtensor<[1,3,3,2],f32>, %arg1: !torch.vtensor<[3],f32>, %arg2: !torch.vtensor<[3],ui8>) -> !torch.vtensor<[1,3,3,2],ui8> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.QuantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[1,3,3,2],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],ui8>) -> !torch.vtensor<[1,3,3,2],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.QuantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[1,3,3,2],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],ui8>) -> !torch.vtensor<[1,3,3,2],ui8> return %0 : !torch.vtensor<[1,3,3,2],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_quantizelinear_blocked/model.mlir b/iree_tests/onnx/node/generated/test_quantizelinear_blocked/model.mlir index 810e3245c..46f3467f2 100644 --- a/iree_tests/onnx/node/generated/test_quantizelinear_blocked/model.mlir +++ b/iree_tests/onnx/node/generated/test_quantizelinear_blocked/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_quantizelinear_blocked(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[3,2],f32>, %arg2: !torch.vtensor<[3,2],ui8>) -> !torch.vtensor<[3,4],ui8> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.QuantizeLinear"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64, torch.onnx.block_size = 2 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,2],f32>, !torch.vtensor<[3,2],ui8>) -> !torch.vtensor<[3,4],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.QuantizeLinear"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64, torch.onnx.block_size = 2 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,2],f32>, !torch.vtensor<[3,2],ui8>) -> !torch.vtensor<[3,4],ui8> return %0 : !torch.vtensor<[3,4],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/input_0.npy b/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/input_0.npy new file mode 100644 index 000000000..dddeb1ef1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/input_1.npy b/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/input_1.npy new file mode 100644 index 000000000..656a8d759 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/input_2.npy b/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/input_2.npy new file mode 100644 index 000000000..c25d6a8c2 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/model.mlir b/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/model.mlir new file mode 100644 index 000000000..43f264a07 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_quantizelinear_e4m3fn(%arg0: !torch.vtensor<[5],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[1],f8E4M3FN>) -> !torch.vtensor<[5],f8E4M3FN> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.QuantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[5],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[1],f8E4M3FN>) -> !torch.vtensor<[5],f8E4M3FN> + return %0 : !torch.vtensor<[5],f8E4M3FN> + } +} + diff --git a/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/output_0.npy b/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/output_0.npy new file mode 100644 index 000000000..743f3ccf6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/test_data_flags.txt b/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/test_data_flags.txt new file mode 100644 index 000000000..cb3b7ab77 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_quantizelinear_e4m3fn/test_data_flags.txt @@ -0,0 +1,4 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/input_0.npy b/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/input_0.npy new file mode 100644 index 000000000..dddeb1ef1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/input_1.npy b/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/input_1.npy new file mode 100644 index 000000000..656a8d759 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/input_2.npy b/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/input_2.npy new file mode 100644 index 000000000..c25d6a8c2 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/model.mlir b/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/model.mlir new file mode 100644 index 000000000..a485d986d --- /dev/null +++ b/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_quantizelinear_e5m2(%arg0: !torch.vtensor<[5],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[1],f8E5M2>) -> !torch.vtensor<[5],f8E5M2> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.QuantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[5],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[1],f8E5M2>) -> !torch.vtensor<[5],f8E5M2> + return %0 : !torch.vtensor<[5],f8E5M2> + } +} + diff --git a/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/output_0.npy b/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/output_0.npy new file mode 100644 index 000000000..307abe039 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/test_data_flags.txt b/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/test_data_flags.txt new file mode 100644 index 000000000..cb3b7ab77 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_quantizelinear_e5m2/test_data_flags.txt @@ -0,0 +1,4 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_quantizelinear_int16/model.mlir b/iree_tests/onnx/node/generated/test_quantizelinear_int16/model.mlir index 797e6baea..50b1e425e 100644 --- a/iree_tests/onnx/node/generated/test_quantizelinear_int16/model.mlir +++ b/iree_tests/onnx/node/generated/test_quantizelinear_int16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_quantizelinear_int16(%arg0: !torch.vtensor<[16],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],si16>) -> !torch.vtensor<[16],si16> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.QuantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[16],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],si16>) -> !torch.vtensor<[16],si16> + %none = torch.constant.none + %0 = torch.operator "onnx.QuantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[16],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],si16>) -> !torch.vtensor<[16],si16> return %0 : !torch.vtensor<[16],si16> } } diff --git a/iree_tests/onnx/node/generated/test_quantizelinear_uint16/model.mlir b/iree_tests/onnx/node/generated/test_quantizelinear_uint16/model.mlir index 48d6aafa5..e574a3b50 100644 --- a/iree_tests/onnx/node/generated/test_quantizelinear_uint16/model.mlir +++ b/iree_tests/onnx/node/generated/test_quantizelinear_uint16/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_quantizelinear_uint16(%arg0: !torch.vtensor<[12],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],ui16>) -> !torch.vtensor<[12],ui16> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.QuantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[12],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui16>) -> !torch.vtensor<[12],ui16> + %none = torch.constant.none + %0 = torch.operator "onnx.QuantizeLinear"(%arg0, %arg1, %arg2) : (!torch.vtensor<[12],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],ui16>) -> !torch.vtensor<[12],ui16> return %0 : !torch.vtensor<[12],ui16> } } diff --git a/iree_tests/onnx/node/generated/test_range_float_type_positive_delta/model.mlir b/iree_tests/onnx/node/generated/test_range_float_type_positive_delta/model.mlir index 55cc4dfa6..f1494eea3 100644 --- a/iree_tests/onnx/node/generated/test_range_float_type_positive_delta/model.mlir +++ b/iree_tests/onnx/node/generated/test_range_float_type_positive_delta/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_range_float_type_positive_delta(%arg0: !torch.vtensor<[],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],f32>) -> !torch.vtensor<[2],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Range"(%arg0, %arg1, %arg2) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Range"(%arg0, %arg1, %arg2) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[2],f32> return %0 : !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/input_0.npy new file mode 100644 index 000000000..f9688e616 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/input_1.npy new file mode 100644 index 000000000..27294ed90 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/input_2.npy new file mode 100644 index 000000000..656a8d759 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/model.mlir b/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/model.mlir new file mode 100644 index 000000000..06c9bf36b --- /dev/null +++ b/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/model.mlir @@ -0,0 +1,22 @@ +module { + func.func @test_range_float_type_positive_delta_expanded(%arg0: !torch.vtensor<[],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],f32>) -> !torch.vtensor<[2],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Sub"(%arg1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Cast"(%arg2) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Div"(%1, %2) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Ceil"(%3) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.Relu"(%4) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Cast"(%5) {torch.onnx.to = 7 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],si64> + %7 = torch.operator "onnx.Cast"(%5) {torch.onnx.to = 9 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],i1> + %8:2 = torch.operator "onnx.Loop"(%6, %7, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[],i1>, !torch.vtensor<[],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[2],f32>) { + ^bb0(%arg3: !torch.vtensor<[],si64>, %arg4: !torch.vtensor<[],i1>, %arg5: !torch.vtensor<[],f32>): + %9 = torch.operator "onnx.Identity"(%arg4) : (!torch.vtensor<[],i1>) -> !torch.vtensor<[],i1> + %10 = torch.operator "onnx.Add"(%arg5, %arg2) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %11 = torch.operator "onnx.Identity"(%arg5) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + torch.operator_terminator %9, %10, %11 : !torch.vtensor<[],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32> + } + return %8#1 : !torch.vtensor<[2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/output_0.npy new file mode 100644 index 000000000..a20404eeb Binary files /dev/null and b/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/test_data_flags.txt new file mode 100644 index 000000000..cb3b7ab77 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_range_float_type_positive_delta_expanded/test_data_flags.txt @@ -0,0 +1,4 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta/model.mlir b/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta/model.mlir index d32e2f1e0..eba535b11 100644 --- a/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta/model.mlir +++ b/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_range_int32_type_negative_delta(%arg0: !torch.vtensor<[],si32>, %arg1: !torch.vtensor<[],si32>, %arg2: !torch.vtensor<[],si32>) -> !torch.vtensor<[2],si32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Range"(%arg0, %arg1, %arg2) : (!torch.vtensor<[],si32>, !torch.vtensor<[],si32>, !torch.vtensor<[],si32>) -> !torch.vtensor<[2],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.Range"(%arg0, %arg1, %arg2) : (!torch.vtensor<[],si32>, !torch.vtensor<[],si32>, !torch.vtensor<[],si32>) -> !torch.vtensor<[2],si32> return %0 : !torch.vtensor<[2],si32> } } diff --git a/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/input_0.npy b/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/input_0.npy new file mode 100644 index 000000000..44d70be80 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/input_1.npy b/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/input_1.npy new file mode 100644 index 000000000..82526b651 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/input_2.npy b/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/input_2.npy new file mode 100644 index 000000000..f1461291f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/model.mlir b/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/model.mlir new file mode 100644 index 000000000..53875ae47 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/model.mlir @@ -0,0 +1,22 @@ +module { + func.func @test_range_int32_type_negative_delta_expanded(%arg0: !torch.vtensor<[],si32>, %arg1: !torch.vtensor<[],si32>, %arg2: !torch.vtensor<[],si32>) -> !torch.vtensor<[2],si32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Sub"(%arg1, %arg0) : (!torch.vtensor<[],si32>, !torch.vtensor<[],si32>) -> !torch.vtensor<[],si32> + %1 = torch.operator "onnx.Cast"(%0) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Cast"(%arg2) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],si32>) -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Div"(%1, %2) : (!torch.vtensor<[],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Ceil"(%3) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.Relu"(%4) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Cast"(%5) {torch.onnx.to = 7 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],si64> + %7 = torch.operator "onnx.Cast"(%5) {torch.onnx.to = 9 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],i1> + %8:2 = torch.operator "onnx.Loop"(%6, %7, %arg0) : (!torch.vtensor<[],si64>, !torch.vtensor<[],i1>, !torch.vtensor<[],si32>) -> (!torch.vtensor<[],si32>, !torch.vtensor<[2],si32>) { + ^bb0(%arg3: !torch.vtensor<[],si64>, %arg4: !torch.vtensor<[],i1>, %arg5: !torch.vtensor<[],si32>): + %9 = torch.operator "onnx.Identity"(%arg4) : (!torch.vtensor<[],i1>) -> !torch.vtensor<[],i1> + %10 = torch.operator "onnx.Add"(%arg5, %arg2) : (!torch.vtensor<[],si32>, !torch.vtensor<[],si32>) -> !torch.vtensor<[],si32> + %11 = torch.operator "onnx.Identity"(%arg5) : (!torch.vtensor<[],si32>) -> !torch.vtensor<[],si32> + torch.operator_terminator %9, %10, %11 : !torch.vtensor<[],i1>, !torch.vtensor<[],si32>, !torch.vtensor<[],si32> + } + return %8#1 : !torch.vtensor<[2],si32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/output_0.npy b/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/output_0.npy new file mode 100644 index 000000000..944fe3da1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/test_data_flags.txt b/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/test_data_flags.txt new file mode 100644 index 000000000..cb3b7ab77 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_range_int32_type_negative_delta_expanded/test_data_flags.txt @@ -0,0 +1,4 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_reciprocal/model.mlir b/iree_tests/onnx/node/generated/test_reciprocal/model.mlir index c69ddb67b..6edc50168 100644 --- a/iree_tests/onnx/node/generated/test_reciprocal/model.mlir +++ b/iree_tests/onnx/node/generated/test_reciprocal/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reciprocal(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Reciprocal"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Reciprocal"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reciprocal_example/model.mlir b/iree_tests/onnx/node/generated/test_reciprocal_example/model.mlir index 539208bd4..4b14cc65f 100644 --- a/iree_tests/onnx/node/generated/test_reciprocal_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reciprocal_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reciprocal_example(%arg0: !torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Reciprocal"(%arg0) : (!torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Reciprocal"(%arg0) : (!torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> return %0 : !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_default_axes_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_default_axes_keepdims_example/model.mlir index 36f295818..1cfe0be87 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_default_axes_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_default_axes_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l1_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_default_axes_keepdims_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_default_axes_keepdims_example_expanded/model.mlir index 1cbf9557d..03ea76812 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_default_axes_keepdims_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_default_axes_keepdims_example_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_l1_default_axes_keepdims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> return %1 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_default_axes_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_default_axes_keepdims_random/model.mlir index 4cbf8cb1d..8c952fbdd 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_default_axes_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_default_axes_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l1_default_axes_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_default_axes_keepdims_random_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_default_axes_keepdims_random_expanded/model.mlir index 96e90f17c..7ec953aa1 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_default_axes_keepdims_random_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_default_axes_keepdims_random_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_l1_default_axes_keepdims_random_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> return %1 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_do_not_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_do_not_keepdims_example/model.mlir index 26fe41749..182a1fc69 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_do_not_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_do_not_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l1_do_not_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_do_not_keepdims_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_do_not_keepdims_example_expanded/model.mlir index 9faa7376c..cde08de20 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_do_not_keepdims_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_do_not_keepdims_example_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_l1_do_not_keepdims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %1 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_do_not_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_do_not_keepdims_random/model.mlir index 9ef6c4ba1..6ac5e9fc5 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_do_not_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_do_not_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l1_do_not_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_do_not_keepdims_random_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_do_not_keepdims_random_expanded/model.mlir index ce1a43396..4f5b0cd6c 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_do_not_keepdims_random_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_do_not_keepdims_random_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_l1_do_not_keepdims_random_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %1 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_empty_set/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_empty_set/model.mlir index b7f91f7cf..1b00d85c6 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_empty_set/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_empty_set/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l1_empty_set(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> return %0 : !torch.vtensor<[2,1,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_empty_set_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_empty_set_expanded/model.mlir index e560cc586..c1883cb09 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_empty_set_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_empty_set_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_l1_empty_set_expanded(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[2,0,4],f32>) -> !torch.vtensor<[2,0,4],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[2,0,4],f32>) -> !torch.vtensor<[2,0,4],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> return %1 : !torch.vtensor<[2,1,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_keep_dims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_keep_dims_example/model.mlir index d21118a98..2e51f1433 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_keep_dims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_keep_dims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l1_keep_dims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> return %0 : !torch.vtensor<[3,2,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_keep_dims_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_keep_dims_example_expanded/model.mlir index 10dca35b2..8e16f4756 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_keep_dims_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_keep_dims_example_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_l1_keep_dims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> return %1 : !torch.vtensor<[3,2,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_keep_dims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_keep_dims_random/model.mlir index 6452a9292..011fe9dd0 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_keep_dims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_keep_dims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l1_keep_dims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> return %0 : !torch.vtensor<[3,2,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_keep_dims_random_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_keep_dims_random_expanded/model.mlir index 9ff2a3578..5a213d073 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_keep_dims_random_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_keep_dims_random_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_l1_keep_dims_random_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> return %1 : !torch.vtensor<[3,2,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_negative_axes_keep_dims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_negative_axes_keep_dims_example/model.mlir index 2a126ad9e..2f7e537ec 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_negative_axes_keep_dims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_negative_axes_keep_dims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l1_negative_axes_keep_dims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> return %0 : !torch.vtensor<[3,2,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_negative_axes_keep_dims_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_negative_axes_keep_dims_example_expanded/model.mlir index eb2165c50..c694cb3c8 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_negative_axes_keep_dims_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_negative_axes_keep_dims_example_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_l1_negative_axes_keep_dims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> return %1 : !torch.vtensor<[3,2,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_negative_axes_keep_dims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_negative_axes_keep_dims_random/model.mlir index f9a235c55..8580192da 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_negative_axes_keep_dims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_negative_axes_keep_dims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l1_negative_axes_keep_dims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL1"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> return %0 : !torch.vtensor<[3,2,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l1_negative_axes_keep_dims_random_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l1_negative_axes_keep_dims_random_expanded/model.mlir index 793304cf1..4c4978cb8 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l1_negative_axes_keep_dims_random_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l1_negative_axes_keep_dims_random_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_l1_negative_axes_keep_dims_random_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> return %1 : !torch.vtensor<[3,2,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_default_axes_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_default_axes_keepdims_example/model.mlir index 5303cea12..08cd3f65c 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_default_axes_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_default_axes_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l2_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_default_axes_keepdims_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_default_axes_keepdims_example_expanded/model.mlir index 25ab6f091..d9b32eb3f 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_default_axes_keepdims_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_default_axes_keepdims_example_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_l2_default_axes_keepdims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> return %4 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_default_axes_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_default_axes_keepdims_random/model.mlir index 881635b81..26f60f2f2 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_default_axes_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_default_axes_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l2_default_axes_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_default_axes_keepdims_random_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_default_axes_keepdims_random_expanded/model.mlir index 0bbeb7785..0bb8eaa1a 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_default_axes_keepdims_random_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_default_axes_keepdims_random_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_l2_default_axes_keepdims_random_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> return %4 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_do_not_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_do_not_keepdims_example/model.mlir index 3fba79886..3fd4d514e 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_do_not_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_do_not_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l2_do_not_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_do_not_keepdims_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_do_not_keepdims_example_expanded/model.mlir index 03270fe07..5f03a6e79 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_do_not_keepdims_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_do_not_keepdims_example_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_l2_do_not_keepdims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2],f32> return %4 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_do_not_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_do_not_keepdims_random/model.mlir index 6a9089d3e..94573ac27 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_do_not_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_do_not_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l2_do_not_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_do_not_keepdims_random_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_do_not_keepdims_random_expanded/model.mlir index 07784af2d..46b4a462a 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_do_not_keepdims_random_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_do_not_keepdims_random_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_l2_do_not_keepdims_random_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2],f32> return %4 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_empty_set/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_empty_set/model.mlir index 2de7be825..111224601 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_empty_set/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_empty_set/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l2_empty_set(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> return %0 : !torch.vtensor<[2,1,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_empty_set_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_empty_set_expanded/model.mlir index 801345f24..260eb26d5 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_empty_set_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_empty_set_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_l2_empty_set_expanded(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[2,0,4],f32>) -> !torch.vtensor<[2,0,4],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[2,0,4],f32>) -> !torch.vtensor<[2,1,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[2,0,4],f32>) -> !torch.vtensor<[2,0,4],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[2,0,4],f32>) -> !torch.vtensor<[2,1,4],f32> return %4 : !torch.vtensor<[2,1,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_keep_dims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_keep_dims_example/model.mlir index cfaa14dca..7b8dc8acd 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_keep_dims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_keep_dims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l2_keep_dims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> return %0 : !torch.vtensor<[3,2,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_keep_dims_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_keep_dims_example_expanded/model.mlir index b6db2d896..7fafbabee 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_keep_dims_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_keep_dims_example_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_l2_keep_dims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,1],f32> return %4 : !torch.vtensor<[3,2,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_keep_dims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_keep_dims_random/model.mlir index 5012d0360..15fe92158 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_keep_dims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_keep_dims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l2_keep_dims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> return %0 : !torch.vtensor<[3,2,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_keep_dims_random_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_keep_dims_random_expanded/model.mlir index 36968dc52..f50dc6e77 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_keep_dims_random_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_keep_dims_random_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_l2_keep_dims_random_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,1],f32> return %4 : !torch.vtensor<[3,2,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_negative_axes_keep_dims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_negative_axes_keep_dims_example/model.mlir index 750eaf4ec..a24b25597 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_negative_axes_keep_dims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_negative_axes_keep_dims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l2_negative_axes_keep_dims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> return %0 : !torch.vtensor<[3,2,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_negative_axes_keep_dims_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_negative_axes_keep_dims_example_expanded/model.mlir index 4b6e23361..1e34c8d09 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_negative_axes_keep_dims_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_negative_axes_keep_dims_example_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_l2_negative_axes_keep_dims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,1],f32> return %4 : !torch.vtensor<[3,2,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_negative_axes_keep_dims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_negative_axes_keep_dims_random/model.mlir index 35d9495dd..9e7569948 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_negative_axes_keep_dims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_negative_axes_keep_dims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_l2_negative_axes_keep_dims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceL2"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> return %0 : !torch.vtensor<[3,2,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_l2_negative_axes_keep_dims_random_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_l2_negative_axes_keep_dims_random_expanded/model.mlir index 2623b1ad6..1a02ad51f 100644 --- a/iree_tests/onnx/node/generated/test_reduce_l2_negative_axes_keep_dims_random_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_l2_negative_axes_keep_dims_random_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_l2_negative_axes_keep_dims_random_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Cast"(%1) {torch.onnx.to = 1 : si64} : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Sqrt"(%2) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,1],f32> return %4 : !torch.vtensor<[3,2,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_asc_axes/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_asc_axes/model.mlir index f5b14a542..960597b7b 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_asc_axes/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_asc_axes/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_log_sum_asc_axes(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceLogSum"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceLogSum"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[5],f32> return %0 : !torch.vtensor<[5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_asc_axes_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_asc_axes_expanded/model.mlir index 7caf0ea39..66274e2e3 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_asc_axes_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_asc_axes_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_log_sum_asc_axes_expanded(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.Log"(%0) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Log"(%0) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> return %1 : !torch.vtensor<[5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_default/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_default/model.mlir index 047e3bff2..9ba1ed064 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_log_sum_default(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceLogSum"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceLogSum"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_default_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_default_expanded/model.mlir index 0a0c12696..053041ea3 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_default_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_default_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_log_sum_default_expanded(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.Log"(%0) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Log"(%0) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[1,1,1],f32> return %1 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_desc_axes/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_desc_axes/model.mlir index 4d2084122..f7b0d6e4f 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_desc_axes/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_desc_axes/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_log_sum_desc_axes(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceLogSum"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceLogSum"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_desc_axes_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_desc_axes_expanded/model.mlir index 617315b4d..f39a47155 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_desc_axes_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_desc_axes_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_log_sum_desc_axes_expanded(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.Log"(%0) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Log"(%0) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> return %1 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_empty_set/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_empty_set/model.mlir index e48018316..8aadaab12 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_empty_set/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_empty_set/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_log_sum_empty_set(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceLogSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceLogSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> return %0 : !torch.vtensor<[2,1,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_empty_set_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_empty_set_expanded/model.mlir index bc1a76e9f..bd16b3fba 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_empty_set_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_empty_set_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_log_sum_empty_set_expanded(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.Log"(%0) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[2,1,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Log"(%0) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[2,1,4],f32> return %1 : !torch.vtensor<[2,1,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_default_axes_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_default_axes_keepdims_example/model.mlir index 2429d5c40..d6aacaf22 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_default_axes_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_default_axes_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_log_sum_exp_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f64>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f64> return %0 : !torch.vtensor<[1,1,1],f64> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_default_axes_keepdims_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_default_axes_keepdims_example_expanded/model.mlir index bbe4b54de..d8a4ab84e 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_default_axes_keepdims_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_default_axes_keepdims_example_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_log_sum_exp_default_axes_keepdims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f64>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> - %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> - %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[],f64> - %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[1,1,1],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> + %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> + %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[],f64> + %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[1,1,1],f64> return %4 : !torch.vtensor<[1,1,1],f64> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_default_axes_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_default_axes_keepdims_random/model.mlir index bafe7964e..2cd2efc93 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_default_axes_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_default_axes_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_log_sum_exp_default_axes_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f64>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f64> return %0 : !torch.vtensor<[1,1,1],f64> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_default_axes_keepdims_random_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_default_axes_keepdims_random_expanded/model.mlir index 534500f1e..e0e24c591 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_default_axes_keepdims_random_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_default_axes_keepdims_random_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_log_sum_exp_default_axes_keepdims_random_expanded(%arg0: !torch.vtensor<[3,2,2],f64>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> - %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> - %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[],f64> - %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[1,1,1],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> + %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> + %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[],f64> + %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[1,1,1],f64> return %4 : !torch.vtensor<[1,1,1],f64> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_do_not_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_do_not_keepdims_example/model.mlir index 2346e3b60..01358e3ad 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_do_not_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_do_not_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_log_sum_exp_do_not_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f64>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f64> return %0 : !torch.vtensor<[3,2],f64> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_do_not_keepdims_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_do_not_keepdims_example_expanded/model.mlir index 2454ad752..fff59c5a2 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_do_not_keepdims_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_do_not_keepdims_example_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_log_sum_exp_do_not_keepdims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f64>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> - %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> - %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f64> - %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> + %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> + %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f64> + %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2],f64> return %4 : !torch.vtensor<[3,2],f64> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_do_not_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_do_not_keepdims_random/model.mlir index 77d7aa671..e107caf66 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_do_not_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_do_not_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_log_sum_exp_do_not_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f64>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f64> return %0 : !torch.vtensor<[3,2],f64> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_do_not_keepdims_random_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_do_not_keepdims_random_expanded/model.mlir index 14b1ec6e9..ee6d8e4a7 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_do_not_keepdims_random_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_do_not_keepdims_random_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_log_sum_exp_do_not_keepdims_random_expanded(%arg0: !torch.vtensor<[3,2,2],f64>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> - %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> - %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f64> - %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> + %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> + %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f64> + %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2],f64> return %4 : !torch.vtensor<[3,2],f64> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_empty_set/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_empty_set/model.mlir index a5cbdcfe6..85af43b95 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_empty_set/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_empty_set/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_log_sum_exp_empty_set(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> return %0 : !torch.vtensor<[2,1,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_empty_set_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_empty_set_expanded/model.mlir index 9b2da582a..4ae63f1ff 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_empty_set_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_empty_set_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_log_sum_exp_empty_set_expanded(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[2,0,4],f32>) -> !torch.vtensor<[2,0,4],f64> - %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[2,0,4],f64>) -> !torch.vtensor<[2,0,4],f64> - %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f64> - %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[2,0,4],f32>) -> !torch.vtensor<[2,1,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[2,0,4],f32>) -> !torch.vtensor<[2,0,4],f64> + %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[2,0,4],f64>) -> !torch.vtensor<[2,0,4],f64> + %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f64> + %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[2,0,4],f32>) -> !torch.vtensor<[2,1,4],f32> return %4 : !torch.vtensor<[2,1,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_keepdims_example/model.mlir index 757929ccb..52066d805 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_log_sum_exp_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f64>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f64> return %0 : !torch.vtensor<[3,1,2],f64> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_keepdims_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_keepdims_example_expanded/model.mlir index 6da12dcc0..c3e785977 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_keepdims_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_keepdims_example_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_log_sum_exp_keepdims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f64>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> - %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> - %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f64> - %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,1,2],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> + %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> + %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f64> + %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,1,2],f64> return %4 : !torch.vtensor<[3,1,2],f64> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_keepdims_random/model.mlir index 199a23e26..f3c96b22a 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_log_sum_exp_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f64>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f64> return %0 : !torch.vtensor<[3,1,2],f64> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_keepdims_random_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_keepdims_random_expanded/model.mlir index 6579c312c..180fd2263 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_keepdims_random_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_keepdims_random_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_log_sum_exp_keepdims_random_expanded(%arg0: !torch.vtensor<[3,2,2],f64>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> - %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> - %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f64> - %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,1,2],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> + %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> + %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f64> + %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,1,2],f64> return %4 : !torch.vtensor<[3,1,2],f64> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_negative_axes_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_negative_axes_keepdims_example/model.mlir index 49179aed6..ebc76a346 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_negative_axes_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_negative_axes_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_log_sum_exp_negative_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f64>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f64> return %0 : !torch.vtensor<[3,1,2],f64> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded/model.mlir index 09d5daf7a..62db11c4e 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_log_sum_exp_negative_axes_keepdims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f64>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> - %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> - %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f64> - %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,1,2],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> + %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> + %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f64> + %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,1,2],f64> return %4 : !torch.vtensor<[3,1,2],f64> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_negative_axes_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_negative_axes_keepdims_random/model.mlir index aab4677ec..f3258d769 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_negative_axes_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_negative_axes_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_log_sum_exp_negative_axes_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f64>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceLogSumExp"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f64> return %0 : !torch.vtensor<[3,1,2],f64> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded/model.mlir index 85938db44..00e4c3f21 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_reduce_log_sum_exp_negative_axes_keepdims_random_expanded(%arg0: !torch.vtensor<[3,2,2],f64>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> - %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> - %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f64> - %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> - %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,1,2],f64> + %none = torch.constant.none + %0 = torch.operator "onnx.Cast"(%arg0) {torch.onnx.to = 11 : si64} : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> + %1 = torch.operator "onnx.Exp"(%0) : (!torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,2,2],f64> + %2 = torch.operator "onnx.ReduceSum"(%1, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f64> + %3 = torch.operator "onnx.Log"(%2) : (!torch.vtensor<[],f64>) -> !torch.vtensor<[],f64> + %4 = torch.operator "onnx.CastLike"(%3, %arg0) : (!torch.vtensor<[],f64>, !torch.vtensor<[3,2,2],f64>) -> !torch.vtensor<[3,1,2],f64> return %4 : !torch.vtensor<[3,1,2],f64> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_negative_axes/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_negative_axes/model.mlir index 66a8b6021..875cbc408 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_negative_axes/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_negative_axes/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_log_sum_negative_axes(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceLogSum"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceLogSum"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,5],f32> return %0 : !torch.vtensor<[3,1,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_log_sum_negative_axes_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_log_sum_negative_axes_expanded/model.mlir index cc8b5b682..bbb90c3ae 100644 --- a/iree_tests/onnx/node/generated/test_reduce_log_sum_negative_axes_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_log_sum_negative_axes_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_log_sum_negative_axes_expanded(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.Log"(%0) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,1,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.Log"(%0) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,1,5],f32> return %1 : !torch.vtensor<[3,1,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_max_bool_inputs/model.mlir b/iree_tests/onnx/node/generated/test_reduce_max_bool_inputs/model.mlir index 497883bda..8c2edb174 100644 --- a/iree_tests/onnx/node/generated/test_reduce_max_bool_inputs/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_max_bool_inputs/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_max_bool_inputs(%arg0: !torch.vtensor<[4,2],i1>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[4,1],i1> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMax"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[4,2],i1>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[4,1],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMax"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[4,2],i1>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[4,1],i1> return %0 : !torch.vtensor<[4,1],i1> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_max_default_axes_keepdim_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_max_default_axes_keepdim_example/model.mlir index 2a6058b40..044220369 100644 --- a/iree_tests/onnx/node/generated/test_reduce_max_default_axes_keepdim_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_max_default_axes_keepdim_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_max_default_axes_keepdim_example(%arg0: !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_max_default_axes_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_max_default_axes_keepdims_random/model.mlir index 2ad73c9e4..eea5b1035 100644 --- a/iree_tests/onnx/node/generated/test_reduce_max_default_axes_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_max_default_axes_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_max_default_axes_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_max_do_not_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_max_do_not_keepdims_example/model.mlir index 63346a333..5f051bed4 100644 --- a/iree_tests/onnx/node/generated/test_reduce_max_do_not_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_max_do_not_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_max_do_not_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMax"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMax"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_max_do_not_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_max_do_not_keepdims_random/model.mlir index 9f06be8e8..a715ecf74 100644 --- a/iree_tests/onnx/node/generated/test_reduce_max_do_not_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_max_do_not_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_max_do_not_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMax"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMax"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_max_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_max_keepdims_example/model.mlir index bc9cc7172..ea80bb631 100644 --- a/iree_tests/onnx/node/generated/test_reduce_max_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_max_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_max_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMax"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMax"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_max_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_max_keepdims_random/model.mlir index 84d9e440f..350a88ea8 100644 --- a/iree_tests/onnx/node/generated/test_reduce_max_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_max_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_max_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMax"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMax"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_max_negative_axes_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_max_negative_axes_keepdims_example/model.mlir index 70341ec61..21eac84ac 100644 --- a/iree_tests/onnx/node/generated/test_reduce_max_negative_axes_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_max_negative_axes_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_max_negative_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMax"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMax"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_max_negative_axes_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_max_negative_axes_keepdims_random/model.mlir index f508150ed..23d9b0da7 100644 --- a/iree_tests/onnx/node/generated/test_reduce_max_negative_axes_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_max_negative_axes_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_max_negative_axes_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMax"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMax"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_mean_default_axes_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_mean_default_axes_keepdims_example/model.mlir index 1a83674fb..5795df513 100644 --- a/iree_tests/onnx/node/generated/test_reduce_mean_default_axes_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_mean_default_axes_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_mean_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMean"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMean"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_mean_default_axes_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_mean_default_axes_keepdims_random/model.mlir index 102ce16f1..1b870dca0 100644 --- a/iree_tests/onnx/node/generated/test_reduce_mean_default_axes_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_mean_default_axes_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_mean_default_axes_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMean"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMean"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_mean_do_not_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_mean_do_not_keepdims_example/model.mlir index a9985b20d..d42f461c1 100644 --- a/iree_tests/onnx/node/generated/test_reduce_mean_do_not_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_mean_do_not_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_mean_do_not_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMean"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMean"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_mean_do_not_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_mean_do_not_keepdims_random/model.mlir index e5dd65797..45b12e3c3 100644 --- a/iree_tests/onnx/node/generated/test_reduce_mean_do_not_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_mean_do_not_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_mean_do_not_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMean"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMean"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_mean_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_mean_keepdims_example/model.mlir index 65d6d5ce1..7f6fed761 100644 --- a/iree_tests/onnx/node/generated/test_reduce_mean_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_mean_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_mean_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMean"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMean"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_mean_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_mean_keepdims_random/model.mlir index e93a74cef..bdf75bd37 100644 --- a/iree_tests/onnx/node/generated/test_reduce_mean_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_mean_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_mean_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMean"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMean"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_mean_negative_axes_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_mean_negative_axes_keepdims_example/model.mlir index 53bb8a9ad..75b3a74f1 100644 --- a/iree_tests/onnx/node/generated/test_reduce_mean_negative_axes_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_mean_negative_axes_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_mean_negative_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMean"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMean"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_mean_negative_axes_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_mean_negative_axes_keepdims_random/model.mlir index dca07a633..8a60f4df3 100644 --- a/iree_tests/onnx/node/generated/test_reduce_mean_negative_axes_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_mean_negative_axes_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_mean_negative_axes_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMean"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMean"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_min_bool_inputs/model.mlir b/iree_tests/onnx/node/generated/test_reduce_min_bool_inputs/model.mlir index dba906367..4a950cda3 100644 --- a/iree_tests/onnx/node/generated/test_reduce_min_bool_inputs/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_min_bool_inputs/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_min_bool_inputs(%arg0: !torch.vtensor<[4,2],i1>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[4,1],i1> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMin"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[4,2],i1>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[4,1],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMin"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[4,2],i1>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[4,1],i1> return %0 : !torch.vtensor<[4,1],i1> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_min_default_axes_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_min_default_axes_keepdims_example/model.mlir index 1a5bfa2af..b7745239a 100644 --- a/iree_tests/onnx/node/generated/test_reduce_min_default_axes_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_min_default_axes_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_min_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMin"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMin"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_min_default_axes_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_min_default_axes_keepdims_random/model.mlir index fed45ed7b..89b04a59a 100644 --- a/iree_tests/onnx/node/generated/test_reduce_min_default_axes_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_min_default_axes_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_min_default_axes_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMin"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMin"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_min_do_not_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_min_do_not_keepdims_example/model.mlir index 4586a1515..f03e0d7a4 100644 --- a/iree_tests/onnx/node/generated/test_reduce_min_do_not_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_min_do_not_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_min_do_not_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMin"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMin"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_min_do_not_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_min_do_not_keepdims_random/model.mlir index e0d5aea65..ec42f6b97 100644 --- a/iree_tests/onnx/node/generated/test_reduce_min_do_not_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_min_do_not_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_min_do_not_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMin"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMin"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_min_empty_set/model.mlir b/iree_tests/onnx/node/generated/test_reduce_min_empty_set/model.mlir index 649a8da57..b1087ad78 100644 --- a/iree_tests/onnx/node/generated/test_reduce_min_empty_set/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_min_empty_set/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_min_empty_set(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMin"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMin"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> return %0 : !torch.vtensor<[2,1,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_min_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_min_keepdims_example/model.mlir index 5f00295b4..e7009446d 100644 --- a/iree_tests/onnx/node/generated/test_reduce_min_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_min_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_min_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMin"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMin"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_min_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_min_keepdims_random/model.mlir index 1f6c36da3..f64b7e628 100644 --- a/iree_tests/onnx/node/generated/test_reduce_min_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_min_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_min_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMin"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMin"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_min_negative_axes_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_min_negative_axes_keepdims_example/model.mlir index dc99d4554..eb6c552a3 100644 --- a/iree_tests/onnx/node/generated/test_reduce_min_negative_axes_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_min_negative_axes_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_min_negative_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMin"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMin"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_min_negative_axes_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_min_negative_axes_keepdims_random/model.mlir index a48e9a72f..e91b3cf71 100644 --- a/iree_tests/onnx/node/generated/test_reduce_min_negative_axes_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_min_negative_axes_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_min_negative_axes_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceMin"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceMin"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_prod_default_axes_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_prod_default_axes_keepdims_example/model.mlir index 26a825c16..d8e579600 100644 --- a/iree_tests/onnx/node/generated/test_reduce_prod_default_axes_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_prod_default_axes_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_prod_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceProd"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceProd"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_prod_default_axes_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_prod_default_axes_keepdims_random/model.mlir index eb55de9f8..baa6c4fdd 100644 --- a/iree_tests/onnx/node/generated/test_reduce_prod_default_axes_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_prod_default_axes_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_prod_default_axes_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceProd"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceProd"(%arg0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_prod_do_not_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_prod_do_not_keepdims_example/model.mlir index 8a8910b54..22d66898e 100644 --- a/iree_tests/onnx/node/generated/test_reduce_prod_do_not_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_prod_do_not_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_prod_do_not_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceProd"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceProd"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_prod_do_not_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_prod_do_not_keepdims_random/model.mlir index 39bf9ce3c..38980f3da 100644 --- a/iree_tests/onnx/node/generated/test_reduce_prod_do_not_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_prod_do_not_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_prod_do_not_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceProd"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceProd"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_prod_empty_set/model.mlir b/iree_tests/onnx/node/generated/test_reduce_prod_empty_set/model.mlir index 05bff77e5..8aaa44373 100644 --- a/iree_tests/onnx/node/generated/test_reduce_prod_empty_set/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_prod_empty_set/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_prod_empty_set(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceProd"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceProd"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> return %0 : !torch.vtensor<[2,1,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_prod_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_prod_keepdims_example/model.mlir index c6f31935b..15b81fe21 100644 --- a/iree_tests/onnx/node/generated/test_reduce_prod_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_prod_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_prod_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceProd"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceProd"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_prod_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_prod_keepdims_random/model.mlir index 28edf1085..8a5225c6a 100644 --- a/iree_tests/onnx/node/generated/test_reduce_prod_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_prod_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_prod_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceProd"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceProd"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_prod_negative_axes_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_prod_negative_axes_keepdims_example/model.mlir index 2ce2ff240..4eff25676 100644 --- a/iree_tests/onnx/node/generated/test_reduce_prod_negative_axes_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_prod_negative_axes_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_prod_negative_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceProd"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceProd"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_prod_negative_axes_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_prod_negative_axes_keepdims_random/model.mlir index 2df6e5f4d..1cc098ca3 100644 --- a/iree_tests/onnx/node/generated/test_reduce_prod_negative_axes_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_prod_negative_axes_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_prod_negative_axes_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceProd"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceProd"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_default_axes_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_default_axes_keepdims_example/model.mlir index 921e01c52..01d6f4495 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_default_axes_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_default_axes_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_default_axes_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_default_axes_keepdims_random/model.mlir index 0aa4b14b1..4c2f66e7e 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_default_axes_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_default_axes_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_default_axes_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_do_not_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_do_not_keepdims_example/model.mlir index b3bd01bae..447b0598a 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_do_not_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_do_not_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_do_not_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_do_not_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_do_not_keepdims_random/model.mlir index ff0c04a93..d4e1a8929 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_do_not_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_do_not_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_do_not_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_empty_axes_input_noop_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_empty_axes_input_noop_example/model.mlir index b3ca41ca6..c26a1fe25 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_empty_axes_input_noop_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_empty_axes_input_noop_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_empty_axes_input_noop_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[3,2,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64, torch.onnx.noop_with_empty_axes = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[3,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64, torch.onnx.noop_with_empty_axes = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[3,2,2],f32> return %0 : !torch.vtensor<[3,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_empty_set/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_empty_set/model.mlir index 54e489b64..ee6e78918 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_empty_set/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_empty_set/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_empty_set(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> return %0 : !torch.vtensor<[2,1,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_empty_set_non_reduced_axis_zero/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_empty_set_non_reduced_axis_zero/model.mlir index 2d5fd0373..efc27bd0a 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_empty_set_non_reduced_axis_zero/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_empty_set_non_reduced_axis_zero/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_empty_set_non_reduced_axis_zero(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,0,1],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,0,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,0,1],f32> return %0 : !torch.vtensor<[2,0,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_keepdims_example/model.mlir index 4c941fc90..e1cf5e648 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_keepdims_random/model.mlir index 05230d2ed..19524e565 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_negative_axes_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_negative_axes_keepdims_example/model.mlir index e72c5a4d8..6ac87dc6f 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_negative_axes_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_negative_axes_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_negative_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_negative_axes_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_negative_axes_keepdims_random/model.mlir index 2f515a940..462b2b732 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_negative_axes_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_negative_axes_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_negative_axes_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[3,2,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64, torch.onnx.noop_with_empty_axes = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[3,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSum"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64, torch.onnx.noop_with_empty_axes = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[3,2,2],f32> return %0 : !torch.vtensor<[3,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_default_axes_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_default_axes_keepdims_example/model.mlir index aae6d20a3..5ef3b2403 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_default_axes_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_default_axes_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_square_default_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_default_axes_keepdims_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_default_axes_keepdims_example_expanded/model.mlir index 3b36ef061..45c717552 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_default_axes_keepdims_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_default_axes_keepdims_example_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_sum_square_default_axes_keepdims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> return %1 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_default_axes_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_default_axes_keepdims_random/model.mlir index 0cc70a184..4bd838568 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_default_axes_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_default_axes_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_square_default_axes_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> return %0 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_default_axes_keepdims_random_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_default_axes_keepdims_random_expanded/model.mlir index 9d20900ca..0d49a3a7e 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_default_axes_keepdims_random_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_default_axes_keepdims_random_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_sum_square_default_axes_keepdims_random_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[0],si64>) -> !torch.vtensor<[1,1,1],f32> return %1 : !torch.vtensor<[1,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_do_not_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_do_not_keepdims_example/model.mlir index 43d54ff45..810fcc849 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_do_not_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_do_not_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_square_do_not_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_do_not_keepdims_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_do_not_keepdims_example_expanded/model.mlir index c79ddbf7e..6e8d45e49 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_do_not_keepdims_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_do_not_keepdims_example_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_sum_square_do_not_keepdims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %1 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_do_not_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_do_not_keepdims_random/model.mlir index 96b1f3e8d..46af65873 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_do_not_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_do_not_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_square_do_not_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %0 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_do_not_keepdims_random_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_do_not_keepdims_random_expanded/model.mlir index da4d13a44..4f59780d4 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_do_not_keepdims_random_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_do_not_keepdims_random_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_sum_square_do_not_keepdims_random_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 0 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,2],f32> return %1 : !torch.vtensor<[3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_empty_set/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_empty_set/model.mlir index af106d18f..beed81d66 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_empty_set/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_empty_set/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_square_empty_set(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> return %0 : !torch.vtensor<[2,1,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_empty_set_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_empty_set_expanded/model.mlir index 5f36a9b3a..36b5d39cd 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_empty_set_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_empty_set_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_sum_square_empty_set_expanded(%arg0: !torch.vtensor<[2,0,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[2,0,4],f32>) -> !torch.vtensor<[2,0,4],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[2,0,4],f32>) -> !torch.vtensor<[2,0,4],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,0,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1,4],f32> return %1 : !torch.vtensor<[2,1,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_keepdims_example/model.mlir index 50cfe4a6f..725b6e919 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_square_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_keepdims_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_keepdims_example_expanded/model.mlir index df7c62264..cd3a41c23 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_keepdims_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_keepdims_example_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_sum_square_keepdims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %1 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_keepdims_random/model.mlir index efade27b9..7731ea9bd 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_square_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_keepdims_random_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_keepdims_random_expanded/model.mlir index 93a987d1e..6c60e8dd6 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_keepdims_random_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_keepdims_random_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_sum_square_keepdims_random_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %1 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_negative_axes_keepdims_example/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_negative_axes_keepdims_example/model.mlir index 8be194f48..9db58c401 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_negative_axes_keepdims_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_negative_axes_keepdims_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_square_negative_axes_keepdims_example(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_negative_axes_keepdims_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_negative_axes_keepdims_example_expanded/model.mlir index 182fb7ccb..65d2b36b1 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_negative_axes_keepdims_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_negative_axes_keepdims_example_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_sum_square_negative_axes_keepdims_example_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %1 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_negative_axes_keepdims_random/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_negative_axes_keepdims_random/model.mlir index b4fc567c0..c13137521 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_negative_axes_keepdims_random/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_negative_axes_keepdims_random/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reduce_sum_square_negative_axes_keepdims_random(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReduceSumSquare"(%arg0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %0 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reduce_sum_square_negative_axes_keepdims_random_expanded/model.mlir b/iree_tests/onnx/node/generated/test_reduce_sum_square_negative_axes_keepdims_random_expanded/model.mlir index deaf0f89a..0a72509f2 100644 --- a/iree_tests/onnx/node/generated/test_reduce_sum_square_negative_axes_keepdims_random_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_reduce_sum_square_negative_axes_keepdims_random_expanded/model.mlir @@ -1,7 +1,8 @@ module { func.func @test_reduce_sum_square_negative_axes_keepdims_random_expanded(%arg0: !torch.vtensor<[3,2,2],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> - %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Mul"(%arg0, %arg0) : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[3,2,2],f32>) -> !torch.vtensor<[3,2,2],f32> + %1 = torch.operator "onnx.ReduceSum"(%0, %arg1) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,2,2],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,2],f32> return %1 : !torch.vtensor<[3,1,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reflect_pad/model.mlir b/iree_tests/onnx/node/generated/test_reflect_pad/model.mlir index f155a7b27..51ddf771d 100644 --- a/iree_tests/onnx/node/generated/test_reflect_pad/model.mlir +++ b/iree_tests/onnx/node/generated/test_reflect_pad/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reflect_pad(%arg0: !torch.vtensor<[1,3,4,5],si32>, %arg1: !torch.vtensor<[8],si64>) -> !torch.vtensor<[1,3,6,7],si32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pad"(%arg0, %arg1) {torch.onnx.mode = "reflect"} : (!torch.vtensor<[1,3,4,5],si32>, !torch.vtensor<[8],si64>) -> !torch.vtensor<[1,3,6,7],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.Pad"(%arg0, %arg1) {torch.onnx.mode = "reflect"} : (!torch.vtensor<[1,3,4,5],si32>, !torch.vtensor<[8],si64>) -> !torch.vtensor<[1,3,6,7],si32> return %0 : !torch.vtensor<[1,3,6,7],si32> } } diff --git a/iree_tests/onnx/node/generated/test_regex_full_match_basic/input_0.npy b/iree_tests/onnx/node/generated/test_regex_full_match_basic/input_0.npy new file mode 100644 index 000000000..c79d1d018 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_regex_full_match_basic/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_regex_full_match_basic/model.mlir b/iree_tests/onnx/node/generated/test_regex_full_match_basic/model.mlir new file mode 100644 index 000000000..d30b253d3 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_regex_full_match_basic/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_regex_full_match_basic(%arg0: !torch.vtensor<[3],!torch.str>) -> !torch.vtensor<[3],i1> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.RegexFullMatch"(%arg0) {torch.onnx.pattern = "www\\.[\\w.-]+\\.\\bcom\\b"} : (!torch.vtensor<[3],!torch.str>) -> !torch.vtensor<[3],i1> + return %0 : !torch.vtensor<[3],i1> + } +} + diff --git a/iree_tests/onnx/node/generated/test_regex_full_match_basic/output_0.npy b/iree_tests/onnx/node/generated/test_regex_full_match_basic/output_0.npy new file mode 100644 index 000000000..994e399b1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_regex_full_match_basic/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_regex_full_match_basic/test_data_flags.txt b/iree_tests/onnx/node/generated/test_regex_full_match_basic/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_regex_full_match_basic/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_regex_full_match_email_domain/input_0.npy b/iree_tests/onnx/node/generated/test_regex_full_match_email_domain/input_0.npy new file mode 100644 index 000000000..1e6e9bd2b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_regex_full_match_email_domain/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_regex_full_match_email_domain/model.mlir b/iree_tests/onnx/node/generated/test_regex_full_match_email_domain/model.mlir new file mode 100644 index 000000000..b448d6412 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_regex_full_match_email_domain/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_regex_full_match_email_domain(%arg0: !torch.vtensor<[2,2],!torch.str>) -> !torch.vtensor<[2,2],i1> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.RegexFullMatch"(%arg0) {torch.onnx.pattern = "(\\W|^)[\\w.\\-]{0,25}@(yahoo|gmail)\\.com(\\W|$)"} : (!torch.vtensor<[2,2],!torch.str>) -> !torch.vtensor<[2,2],i1> + return %0 : !torch.vtensor<[2,2],i1> + } +} + diff --git a/iree_tests/onnx/node/generated/test_regex_full_match_email_domain/output_0.npy b/iree_tests/onnx/node/generated/test_regex_full_match_email_domain/output_0.npy new file mode 100644 index 000000000..7c03fb3e6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_regex_full_match_email_domain/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_regex_full_match_email_domain/test_data_flags.txt b/iree_tests/onnx/node/generated/test_regex_full_match_email_domain/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_regex_full_match_email_domain/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_regex_full_match_empty/input_0.npy b/iree_tests/onnx/node/generated/test_regex_full_match_empty/input_0.npy new file mode 100644 index 000000000..8e80ce057 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_regex_full_match_empty/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_regex_full_match_empty/model.mlir b/iree_tests/onnx/node/generated/test_regex_full_match_empty/model.mlir new file mode 100644 index 000000000..5af58e808 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_regex_full_match_empty/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_regex_full_match_empty(%arg0: !torch.vtensor<[2,0],!torch.str>) -> !torch.vtensor<[2,0],i1> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.RegexFullMatch"(%arg0) {torch.onnx.pattern = "(\\W|^)[\\w.\\-]{0,25}@(yahoo|gmail)\\.com(\\W|$)"} : (!torch.vtensor<[2,0],!torch.str>) -> !torch.vtensor<[2,0],i1> + return %0 : !torch.vtensor<[2,0],i1> + } +} + diff --git a/iree_tests/onnx/node/generated/test_regex_full_match_empty/output_0.npy b/iree_tests/onnx/node/generated/test_regex_full_match_empty/output_0.npy new file mode 100644 index 000000000..f36c428da Binary files /dev/null and b/iree_tests/onnx/node/generated/test_regex_full_match_empty/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_regex_full_match_empty/test_data_flags.txt b/iree_tests/onnx/node/generated/test_regex_full_match_empty/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_regex_full_match_empty/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_relu/model.mlir b/iree_tests/onnx/node/generated/test_relu/model.mlir index df06ffeae..a406cc88c 100644 --- a/iree_tests/onnx/node/generated/test_relu/model.mlir +++ b/iree_tests/onnx/node/generated/test_relu/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_relu(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Relu"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Relu"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_relu_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_relu_expanded_ver18/model.mlir index ec017460c..ca6033988 100644 --- a/iree_tests/onnx/node/generated/test_relu_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_relu_expanded_ver18/model.mlir @@ -1,8 +1,9 @@ module { func.func @test_relu_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Max"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Max"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> return %2 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reshape_allowzero_reordered/model.mlir b/iree_tests/onnx/node/generated/test_reshape_allowzero_reordered/model.mlir index b85618206..9dcefdfe4 100644 --- a/iree_tests/onnx/node/generated/test_reshape_allowzero_reordered/model.mlir +++ b/iree_tests/onnx/node/generated/test_reshape_allowzero_reordered/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reshape_allowzero_reordered(%arg0: !torch.vtensor<[0,3,4],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,4,0],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) {torch.onnx.allowzero = 1 : si64} : (!torch.vtensor<[0,3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,4,0],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) {torch.onnx.allowzero = 1 : si64} : (!torch.vtensor<[0,3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,4,0],f32> return %0 : !torch.vtensor<[3,4,0],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reshape_extended_dims/model.mlir b/iree_tests/onnx/node/generated/test_reshape_extended_dims/model.mlir index 135b065c5..9add1ac30 100644 --- a/iree_tests/onnx/node/generated/test_reshape_extended_dims/model.mlir +++ b/iree_tests/onnx/node/generated/test_reshape_extended_dims/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reshape_extended_dims(%arg0: !torch.vtensor<[2,3,4],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,2,2],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,2,2],f32> return %0 : !torch.vtensor<[2,3,2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reshape_negative_dim/model.mlir b/iree_tests/onnx/node/generated/test_reshape_negative_dim/model.mlir index 5d51234f2..55a73bfc8 100644 --- a/iree_tests/onnx/node/generated/test_reshape_negative_dim/model.mlir +++ b/iree_tests/onnx/node/generated/test_reshape_negative_dim/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reshape_negative_dim(%arg0: !torch.vtensor<[2,3,4],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,6,2],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,6,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,6,2],f32> return %0 : !torch.vtensor<[2,6,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reshape_negative_extended_dims/model.mlir b/iree_tests/onnx/node/generated/test_reshape_negative_extended_dims/model.mlir index b8081cea5..133ac3b5f 100644 --- a/iree_tests/onnx/node/generated/test_reshape_negative_extended_dims/model.mlir +++ b/iree_tests/onnx/node/generated/test_reshape_negative_extended_dims/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reshape_negative_extended_dims(%arg0: !torch.vtensor<[2,3,4],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,2,3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,2,3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,2,3,4],f32> return %0 : !torch.vtensor<[1,2,3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reshape_one_dim/model.mlir b/iree_tests/onnx/node/generated/test_reshape_one_dim/model.mlir index 2053749fd..4aead0243 100644 --- a/iree_tests/onnx/node/generated/test_reshape_one_dim/model.mlir +++ b/iree_tests/onnx/node/generated/test_reshape_one_dim/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reshape_one_dim(%arg0: !torch.vtensor<[2,3,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[24],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[24],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[24],f32> return %0 : !torch.vtensor<[24],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reshape_reduced_dims/model.mlir b/iree_tests/onnx/node/generated/test_reshape_reduced_dims/model.mlir index 4822a8c2f..9281b081d 100644 --- a/iree_tests/onnx/node/generated/test_reshape_reduced_dims/model.mlir +++ b/iree_tests/onnx/node/generated/test_reshape_reduced_dims/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reshape_reduced_dims(%arg0: !torch.vtensor<[2,3,4],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[2,12],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2,12],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[2,12],f32> return %0 : !torch.vtensor<[2,12],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reshape_reordered_all_dims/model.mlir b/iree_tests/onnx/node/generated/test_reshape_reordered_all_dims/model.mlir index e2a9a5475..b8b3dfcce 100644 --- a/iree_tests/onnx/node/generated/test_reshape_reordered_all_dims/model.mlir +++ b/iree_tests/onnx/node/generated/test_reshape_reordered_all_dims/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reshape_reordered_all_dims(%arg0: !torch.vtensor<[2,3,4],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[4,2,3],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[4,2,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[4,2,3],f32> return %0 : !torch.vtensor<[4,2,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reshape_reordered_last_dims/model.mlir b/iree_tests/onnx/node/generated/test_reshape_reordered_last_dims/model.mlir index 960dc5fcb..679f5f381 100644 --- a/iree_tests/onnx/node/generated/test_reshape_reordered_last_dims/model.mlir +++ b/iree_tests/onnx/node/generated/test_reshape_reordered_last_dims/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reshape_reordered_last_dims(%arg0: !torch.vtensor<[2,3,4],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,4,3],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,4,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,4,3],f32> return %0 : !torch.vtensor<[2,4,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reshape_zero_and_negative_dim/model.mlir b/iree_tests/onnx/node/generated/test_reshape_zero_and_negative_dim/model.mlir index 33618707f..ee4d4e9a8 100644 --- a/iree_tests/onnx/node/generated/test_reshape_zero_and_negative_dim/model.mlir +++ b/iree_tests/onnx/node/generated/test_reshape_zero_and_negative_dim/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reshape_zero_and_negative_dim(%arg0: !torch.vtensor<[2,3,4],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,1,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,1,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,1,4],f32> return %0 : !torch.vtensor<[2,3,1,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reshape_zero_dim/model.mlir b/iree_tests/onnx/node/generated/test_reshape_zero_dim/model.mlir index 066185e32..29c278c4c 100644 --- a/iree_tests/onnx/node/generated/test_reshape_zero_dim/model.mlir +++ b/iree_tests/onnx/node/generated/test_reshape_zero_dim/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reshape_zero_dim(%arg0: !torch.vtensor<[2,3,4],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,1],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Reshape"(%arg0, %arg1) : (!torch.vtensor<[2,3,4],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[2,3,4,1],f32> return %0 : !torch.vtensor<[2,3,4,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic/input_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic/input_1.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic/input_1.npy new file mode 100644 index 000000000..bdca1ea3b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic/model.mlir b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic/model.mlir new file mode 100644 index 000000000..5ef910fe3 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_downsample_scales_cubic(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,3,3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,3,3],f32> + return %0 : !torch.vtensor<[1,1,3,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic/output_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic/output_0.npy new file mode 100644 index 000000000..610517ba1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_A_n0p5_exclude_outside/input_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_A_n0p5_exclude_outside/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_A_n0p5_exclude_outside/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_A_n0p5_exclude_outside/input_1.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_A_n0p5_exclude_outside/input_1.npy new file mode 100644 index 000000000..bdca1ea3b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_A_n0p5_exclude_outside/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_A_n0p5_exclude_outside/model.mlir b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_A_n0p5_exclude_outside/model.mlir new file mode 100644 index 000000000..4cff154ed --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_A_n0p5_exclude_outside/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_downsample_scales_cubic_A_n0p5_exclude_outside(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,3,3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.cubic_coeff_a = -5.000000e-01 : f32, torch.onnx.exclude_outside = 1 : si64, torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,3,3],f32> + return %0 : !torch.vtensor<[1,1,3,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_A_n0p5_exclude_outside/output_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_A_n0p5_exclude_outside/output_0.npy new file mode 100644 index 000000000..54e9761a1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_A_n0p5_exclude_outside/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_A_n0p5_exclude_outside/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_A_n0p5_exclude_outside/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_A_n0p5_exclude_outside/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_align_corners/input_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_align_corners/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_align_corners/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_align_corners/input_1.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_align_corners/input_1.npy new file mode 100644 index 000000000..bdca1ea3b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_align_corners/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_align_corners/model.mlir b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_align_corners/model.mlir new file mode 100644 index 000000000..837528759 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_align_corners/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_downsample_scales_cubic_align_corners(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,3,3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.coordinate_transformation_mode = "align_corners", torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,3,3],f32> + return %0 : !torch.vtensor<[1,1,3,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_align_corners/output_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_align_corners/output_0.npy new file mode 100644 index 000000000..01cc68721 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_align_corners/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_align_corners/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_align_corners/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_align_corners/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_antialias/input_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_antialias/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_antialias/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_antialias/input_1.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_antialias/input_1.npy new file mode 100644 index 000000000..8fb3a1e29 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_antialias/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_antialias/model.mlir b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_antialias/model.mlir new file mode 100644 index 000000000..a1fd0fbba --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_antialias/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_downsample_scales_cubic_antialias(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,2,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.antialias = 1 : si64, torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,2,2],f32> + return %0 : !torch.vtensor<[1,1,2,2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_antialias/output_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_antialias/output_0.npy new file mode 100644 index 000000000..de435b990 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_antialias/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_antialias/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_antialias/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_cubic_antialias/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear/input_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear/input_0.npy new file mode 100644 index 000000000..e02bc4dac Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear/input_1.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear/input_1.npy new file mode 100644 index 000000000..8fb3a1e29 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear/model.mlir b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear/model.mlir new file mode 100644 index 000000000..890f2acbd --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_downsample_scales_linear(%arg0: !torch.vtensor<[1,1,2,4],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,1,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,2,4],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,1,2],f32> + return %0 : !torch.vtensor<[1,1,1,2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear/output_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear/output_0.npy new file mode 100644 index 000000000..64cd15441 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_align_corners/input_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_align_corners/input_0.npy new file mode 100644 index 000000000..e02bc4dac Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_align_corners/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_align_corners/input_1.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_align_corners/input_1.npy new file mode 100644 index 000000000..8fb3a1e29 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_align_corners/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_align_corners/model.mlir b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_align_corners/model.mlir new file mode 100644 index 000000000..d4ede655a --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_align_corners/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_downsample_scales_linear_align_corners(%arg0: !torch.vtensor<[1,1,2,4],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,1,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.coordinate_transformation_mode = "align_corners", torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,2,4],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,1,2],f32> + return %0 : !torch.vtensor<[1,1,1,2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_align_corners/output_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_align_corners/output_0.npy new file mode 100644 index 000000000..448ea64a2 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_align_corners/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_align_corners/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_align_corners/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_align_corners/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_antialias/input_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_antialias/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_antialias/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_antialias/input_1.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_antialias/input_1.npy new file mode 100644 index 000000000..8fb3a1e29 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_antialias/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_antialias/model.mlir b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_antialias/model.mlir new file mode 100644 index 000000000..aadf96423 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_antialias/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_downsample_scales_linear_antialias(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,2,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.antialias = 1 : si64, torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,2,2],f32> + return %0 : !torch.vtensor<[1,1,2,2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_antialias/output_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_antialias/output_0.npy new file mode 100644 index 000000000..c2c96c9ed Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_antialias/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_antialias/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_antialias/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_antialias/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_half_pixel_symmetric/input_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_half_pixel_symmetric/input_0.npy new file mode 100644 index 000000000..4a3ad55de Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_half_pixel_symmetric/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_half_pixel_symmetric/input_1.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_half_pixel_symmetric/input_1.npy new file mode 100644 index 000000000..f6cc87409 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_half_pixel_symmetric/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_half_pixel_symmetric/model.mlir b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_half_pixel_symmetric/model.mlir new file mode 100644 index 000000000..514ead856 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_half_pixel_symmetric/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_downsample_scales_linear_half_pixel_symmetric(%arg0: !torch.vtensor<[1,1,1,4],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,1,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.coordinate_transformation_mode = "half_pixel_symmetric", torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,1,4],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,1,2],f32> + return %0 : !torch.vtensor<[1,1,1,2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_half_pixel_symmetric/output_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_half_pixel_symmetric/output_0.npy new file mode 100644 index 000000000..2be28b97c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_half_pixel_symmetric/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_half_pixel_symmetric/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_half_pixel_symmetric/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_linear_half_pixel_symmetric/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_nearest/input_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_nearest/input_0.npy new file mode 100644 index 000000000..e02bc4dac Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_nearest/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_nearest/input_1.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_nearest/input_1.npy new file mode 100644 index 000000000..8fb3a1e29 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_nearest/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_nearest/model.mlir b/iree_tests/onnx/node/generated/test_resize_downsample_scales_nearest/model.mlir new file mode 100644 index 000000000..46ee2b541 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_nearest/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_downsample_scales_nearest(%arg0: !torch.vtensor<[1,1,2,4],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,1,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,2,4],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,1,2],f32> + return %0 : !torch.vtensor<[1,1,1,2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_nearest/output_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_scales_nearest/output_0.npy new file mode 100644 index 000000000..fdc9f5a8c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_scales_nearest/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_scales_nearest/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_downsample_scales_nearest/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_scales_nearest/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic/input_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic/input_1.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic/input_1.npy new file mode 100644 index 000000000..d4627526e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic/model.mlir b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic/model.mlir new file mode 100644 index 000000000..d72412bda --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_downsample_sizes_cubic(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,3,3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %none, %arg1) {torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.none, !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,3,3],f32> + return %0 : !torch.vtensor<[1,1,3,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic/output_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic/output_0.npy new file mode 100644 index 000000000..d8d333179 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic_antialias/input_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic_antialias/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic_antialias/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic_antialias/input_1.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic_antialias/input_1.npy new file mode 100644 index 000000000..d4627526e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic_antialias/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic_antialias/model.mlir b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic_antialias/model.mlir new file mode 100644 index 000000000..c1d4dc1fe --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic_antialias/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_downsample_sizes_cubic_antialias(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,3,3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %none, %arg1) {torch.onnx.antialias = 1 : si64, torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.none, !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,3,3],f32> + return %0 : !torch.vtensor<[1,1,3,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic_antialias/output_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic_antialias/output_0.npy new file mode 100644 index 000000000..8f496b133 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic_antialias/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic_antialias/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic_antialias/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_cubic_antialias/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_antialias/input_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_antialias/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_antialias/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_antialias/input_1.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_antialias/input_1.npy new file mode 100644 index 000000000..d4627526e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_antialias/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_antialias/model.mlir b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_antialias/model.mlir new file mode 100644 index 000000000..4db4afd27 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_antialias/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_downsample_sizes_linear_antialias(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,3,3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %none, %arg1) {torch.onnx.antialias = 1 : si64, torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.none, !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,3,3],f32> + return %0 : !torch.vtensor<[1,1,3,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_antialias/output_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_antialias/output_0.npy new file mode 100644 index 000000000..0253118f0 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_antialias/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_antialias/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_antialias/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_antialias/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_pytorch_half_pixel/input_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_pytorch_half_pixel/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_pytorch_half_pixel/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_pytorch_half_pixel/input_1.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_pytorch_half_pixel/input_1.npy new file mode 100644 index 000000000..4d9fb3556 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_pytorch_half_pixel/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_pytorch_half_pixel/model.mlir b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_pytorch_half_pixel/model.mlir new file mode 100644 index 000000000..5de302eae --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_pytorch_half_pixel/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_downsample_sizes_linear_pytorch_half_pixel(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,3,1],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %none, %arg1) {torch.onnx.coordinate_transformation_mode = "pytorch_half_pixel", torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.none, !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,3,1],f32> + return %0 : !torch.vtensor<[1,1,3,1],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_pytorch_half_pixel/output_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_pytorch_half_pixel/output_0.npy new file mode 100644 index 000000000..03130a2c4 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_pytorch_half_pixel/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_pytorch_half_pixel/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_pytorch_half_pixel/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_linear_pytorch_half_pixel/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest/input_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest/input_0.npy new file mode 100644 index 000000000..e02bc4dac Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest/input_1.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest/input_1.npy new file mode 100644 index 000000000..093182464 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest/model.mlir b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest/model.mlir new file mode 100644 index 000000000..80ad7f876 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_downsample_sizes_nearest(%arg0: !torch.vtensor<[1,1,2,4],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,1,3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %none, %arg1) {torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,2,4],f32>, !torch.none, !torch.none, !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,1,3],f32> + return %0 : !torch.vtensor<[1,1,1,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest/output_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest/output_0.npy new file mode 100644 index 000000000..5db711810 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_larger/input_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_larger/input_0.npy new file mode 100644 index 000000000..e02bc4dac Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_larger/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_larger/input_1.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_larger/input_1.npy new file mode 100644 index 000000000..3fe353477 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_larger/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_larger/model.mlir b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_larger/model.mlir new file mode 100644 index 000000000..b0f0a7227 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_larger/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_downsample_sizes_nearest_not_larger(%arg0: !torch.vtensor<[1,1,2,4],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,1,2],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %none, %arg1) {torch.onnx.axes = [2 : si64, 3 : si64], torch.onnx.keep_aspect_ratio_policy = "not_larger", torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,2,4],f32>, !torch.none, !torch.none, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,1,2],f32> + return %0 : !torch.vtensor<[1,1,1,2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_larger/output_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_larger/output_0.npy new file mode 100644 index 000000000..fdc9f5a8c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_larger/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_larger/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_larger/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_larger/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_smaller/input_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_smaller/input_0.npy new file mode 100644 index 000000000..e02bc4dac Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_smaller/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_smaller/input_1.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_smaller/input_1.npy new file mode 100644 index 000000000..3fe353477 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_smaller/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_smaller/model.mlir b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_smaller/model.mlir new file mode 100644 index 000000000..fba17139c --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_smaller/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_downsample_sizes_nearest_not_smaller(%arg0: !torch.vtensor<[1,1,2,4],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,2,3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %none, %arg1) {torch.onnx.axes = [2 : si64, 3 : si64], torch.onnx.keep_aspect_ratio_policy = "not_smaller", torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,2,4],f32>, !torch.none, !torch.none, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,2,3],f32> + return %0 : !torch.vtensor<[1,1,2,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_smaller/output_0.npy b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_smaller/output_0.npy new file mode 100644 index 000000000..b7df37a1c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_smaller/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_smaller/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_smaller/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_downsample_sizes_nearest_not_smaller/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/input_0.npy b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/input_1.npy b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/input_1.npy new file mode 100644 index 000000000..0ae68a657 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/input_2.npy b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/input_2.npy new file mode 100644 index 000000000..d4627526e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/model.mlir b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/model.mlir new file mode 100644 index 000000000..d49be0831 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_tf_crop_and_resize(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[8],f32>, %arg2: !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,3,3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %arg1, %none, %arg2) {torch.onnx.coordinate_transformation_mode = "tf_crop_and_resize", torch.onnx.extrapolation_value = 1.000000e+01 : f32, torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.vtensor<[8],f32>, !torch.none, !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,3,3],f32> + return %0 : !torch.vtensor<[1,1,3,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/output_0.npy b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/output_0.npy new file mode 100644 index 000000000..890dc7f77 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/test_data_flags.txt new file mode 100644 index 000000000..cb3b7ab77 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize/test_data_flags.txt @@ -0,0 +1,4 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/input_0.npy b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/input_1.npy b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/input_1.npy new file mode 100644 index 000000000..f888a8920 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/input_2.npy b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/input_2.npy new file mode 100644 index 000000000..df6918bed Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/model.mlir b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/model.mlir new file mode 100644 index 000000000..4f9ed61d6 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_tf_crop_and_resize_axes_2_3(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],f32>, %arg2: !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,3,3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %arg1, %none, %arg2) {torch.onnx.axes = [2 : si64, 3 : si64], torch.onnx.coordinate_transformation_mode = "tf_crop_and_resize", torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.vtensor<[4],f32>, !torch.none, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,3,3],f32> + return %0 : !torch.vtensor<[1,1,3,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/output_0.npy b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/output_0.npy new file mode 100644 index 000000000..d4be4345a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/test_data_flags.txt new file mode 100644 index 000000000..cb3b7ab77 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_2_3/test_data_flags.txt @@ -0,0 +1,4 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/input_0.npy b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/input_1.npy b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/input_1.npy new file mode 100644 index 000000000..27a759200 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/input_2.npy b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/input_2.npy new file mode 100644 index 000000000..df6918bed Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/model.mlir b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/model.mlir new file mode 100644 index 000000000..7d951e8ce --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_tf_crop_and_resize_axes_3_2(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],f32>, %arg2: !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,3,3],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %arg1, %none, %arg2) {torch.onnx.axes = [3 : si64, 2 : si64], torch.onnx.coordinate_transformation_mode = "tf_crop_and_resize", torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.vtensor<[4],f32>, !torch.none, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,3,3],f32> + return %0 : !torch.vtensor<[1,1,3,3],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/output_0.npy b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/output_0.npy new file mode 100644 index 000000000..d4be4345a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/test_data_flags.txt new file mode 100644 index 000000000..cb3b7ab77 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_tf_crop_and_resize_axes_3_2/test_data_flags.txt @@ -0,0 +1,4 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic/input_1.npy new file mode 100644 index 000000000..aea02373b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic/model.mlir new file mode 100644 index 000000000..7197f5e30 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_scales_cubic(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,8,8],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,8,8],f32> + return %0 : !torch.vtensor<[1,1,8,8],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic/output_0.npy new file mode 100644 index 000000000..97a194473 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_A_n0p5_exclude_outside/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_A_n0p5_exclude_outside/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_A_n0p5_exclude_outside/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_A_n0p5_exclude_outside/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_A_n0p5_exclude_outside/input_1.npy new file mode 100644 index 000000000..aea02373b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_A_n0p5_exclude_outside/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_A_n0p5_exclude_outside/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_A_n0p5_exclude_outside/model.mlir new file mode 100644 index 000000000..99ac81a43 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_A_n0p5_exclude_outside/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_scales_cubic_A_n0p5_exclude_outside(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,8,8],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.cubic_coeff_a = -5.000000e-01 : f32, torch.onnx.exclude_outside = 1 : si64, torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,8,8],f32> + return %0 : !torch.vtensor<[1,1,8,8],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_A_n0p5_exclude_outside/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_A_n0p5_exclude_outside/output_0.npy new file mode 100644 index 000000000..f6320606e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_A_n0p5_exclude_outside/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_A_n0p5_exclude_outside/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_A_n0p5_exclude_outside/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_A_n0p5_exclude_outside/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_align_corners/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_align_corners/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_align_corners/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_align_corners/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_align_corners/input_1.npy new file mode 100644 index 000000000..aea02373b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_align_corners/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_align_corners/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_align_corners/model.mlir new file mode 100644 index 000000000..3ef76910b --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_align_corners/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_scales_cubic_align_corners(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,8,8],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.coordinate_transformation_mode = "align_corners", torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,8,8],f32> + return %0 : !torch.vtensor<[1,1,8,8],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_align_corners/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_align_corners/output_0.npy new file mode 100644 index 000000000..8821eee84 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_align_corners/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_align_corners/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_align_corners/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_align_corners/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_asymmetric/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_asymmetric/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_asymmetric/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_asymmetric/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_asymmetric/input_1.npy new file mode 100644 index 000000000..aea02373b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_asymmetric/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_asymmetric/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_asymmetric/model.mlir new file mode 100644 index 000000000..79108fc76 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_asymmetric/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_scales_cubic_asymmetric(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,8,8],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.coordinate_transformation_mode = "asymmetric", torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,8,8],f32> + return %0 : !torch.vtensor<[1,1,8,8],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_asymmetric/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_asymmetric/output_0.npy new file mode 100644 index 000000000..c36bbfd91 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_asymmetric/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_asymmetric/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_asymmetric/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_cubic_asymmetric/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear/input_0.npy new file mode 100644 index 000000000..12db14385 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear/input_1.npy new file mode 100644 index 000000000..aea02373b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear/model.mlir new file mode 100644 index 000000000..6d13ab85e --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_scales_linear(%arg0: !torch.vtensor<[1,1,2,2],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,4,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,2,2],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,4,4],f32> + return %0 : !torch.vtensor<[1,1,4,4],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear/output_0.npy new file mode 100644 index 000000000..cde276f74 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_align_corners/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_align_corners/input_0.npy new file mode 100644 index 000000000..12db14385 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_align_corners/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_align_corners/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_align_corners/input_1.npy new file mode 100644 index 000000000..aea02373b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_align_corners/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_align_corners/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_align_corners/model.mlir new file mode 100644 index 000000000..1be5a7f9c --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_align_corners/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_scales_linear_align_corners(%arg0: !torch.vtensor<[1,1,2,2],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,4,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.coordinate_transformation_mode = "align_corners", torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,2,2],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,4,4],f32> + return %0 : !torch.vtensor<[1,1,4,4],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_align_corners/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_align_corners/output_0.npy new file mode 100644 index 000000000..39f45454c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_align_corners/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_align_corners/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_align_corners/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_align_corners/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_half_pixel_symmetric/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_half_pixel_symmetric/input_0.npy new file mode 100644 index 000000000..12db14385 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_half_pixel_symmetric/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_half_pixel_symmetric/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_half_pixel_symmetric/input_1.npy new file mode 100644 index 000000000..2e8a1620b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_half_pixel_symmetric/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_half_pixel_symmetric/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_half_pixel_symmetric/model.mlir new file mode 100644 index 000000000..7f51eb225 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_half_pixel_symmetric/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_scales_linear_half_pixel_symmetric(%arg0: !torch.vtensor<[1,1,2,2],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,4,5],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.coordinate_transformation_mode = "half_pixel_symmetric", torch.onnx.mode = "linear"} : (!torch.vtensor<[1,1,2,2],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,4,5],f32> + return %0 : !torch.vtensor<[1,1,4,5],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_half_pixel_symmetric/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_half_pixel_symmetric/output_0.npy new file mode 100644 index 000000000..e54461a1f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_half_pixel_symmetric/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_half_pixel_symmetric/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_half_pixel_symmetric/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_linear_half_pixel_symmetric/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest/input_0.npy new file mode 100644 index 000000000..12db14385 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest/input_1.npy new file mode 100644 index 000000000..df870b7ca Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest/model.mlir new file mode 100644 index 000000000..5e0a338ff --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_scales_nearest(%arg0: !torch.vtensor<[1,1,2,2],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,4,6],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,2,2],f32>, !torch.none, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,4,6],f32> + return %0 : !torch.vtensor<[1,1,4,6],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest/output_0.npy new file mode 100644 index 000000000..3f26563c0 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_2_3/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_2_3/input_0.npy new file mode 100644 index 000000000..12db14385 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_2_3/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_2_3/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_2_3/input_1.npy new file mode 100644 index 000000000..0c34f578a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_2_3/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_2_3/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_2_3/model.mlir new file mode 100644 index 000000000..062abd186 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_2_3/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_scales_nearest_axes_2_3(%arg0: !torch.vtensor<[1,1,2,2],f32>, %arg1: !torch.vtensor<[2],f32>) -> !torch.vtensor<[1,1,4,6],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.axes = [2 : si64, 3 : si64], torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,2,2],f32>, !torch.none, !torch.vtensor<[2],f32>) -> !torch.vtensor<[1,1,4,6],f32> + return %0 : !torch.vtensor<[1,1,4,6],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_2_3/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_2_3/output_0.npy new file mode 100644 index 000000000..3f26563c0 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_2_3/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_2_3/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_2_3/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_2_3/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_3_2/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_3_2/input_0.npy new file mode 100644 index 000000000..12db14385 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_3_2/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_3_2/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_3_2/input_1.npy new file mode 100644 index 000000000..f6e702836 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_3_2/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_3_2/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_3_2/model.mlir new file mode 100644 index 000000000..066563c6a --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_3_2/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_scales_nearest_axes_3_2(%arg0: !torch.vtensor<[1,1,2,2],f32>, %arg1: !torch.vtensor<[2],f32>) -> !torch.vtensor<[1,1,4,6],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %arg1) {torch.onnx.axes = [3 : si64, 2 : si64], torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,2,2],f32>, !torch.none, !torch.vtensor<[2],f32>) -> !torch.vtensor<[1,1,4,6],f32> + return %0 : !torch.vtensor<[1,1,4,6],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_3_2/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_3_2/output_0.npy new file mode 100644 index 000000000..3f26563c0 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_3_2/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_3_2/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_3_2/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_scales_nearest_axes_3_2/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_cubic/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_cubic/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_cubic/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_cubic/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_cubic/input_1.npy new file mode 100644 index 000000000..691454087 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_cubic/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_cubic/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_cubic/model.mlir new file mode 100644 index 000000000..49648ae5d --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_cubic/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_sizes_cubic(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,9,10],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %none, %arg1) {torch.onnx.mode = "cubic"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.none, !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,9,10],f32> + return %0 : !torch.vtensor<[1,1,9,10],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_cubic/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_cubic/output_0.npy new file mode 100644 index 000000000..c50b49a61 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_cubic/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_cubic/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_cubic/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_cubic/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest/input_0.npy new file mode 100644 index 000000000..12db14385 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest/input_1.npy new file mode 100644 index 000000000..1688c5e21 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest/model.mlir new file mode 100644 index 000000000..4c02f3da1 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_sizes_nearest(%arg0: !torch.vtensor<[1,1,2,2],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,7,8],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %none, %arg1) {torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,2,2],f32>, !torch.none, !torch.none, !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,7,8],f32> + return %0 : !torch.vtensor<[1,1,7,8],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest/output_0.npy new file mode 100644 index 000000000..6765cf400 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_2_3/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_2_3/input_0.npy new file mode 100644 index 000000000..12db14385 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_2_3/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_2_3/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_2_3/input_1.npy new file mode 100644 index 000000000..625a34e3a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_2_3/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_2_3/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_2_3/model.mlir new file mode 100644 index 000000000..dd474ca69 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_2_3/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_sizes_nearest_axes_2_3(%arg0: !torch.vtensor<[1,1,2,2],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,7,8],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %none, %arg1) {torch.onnx.axes = [2 : si64, 3 : si64], torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,2,2],f32>, !torch.none, !torch.none, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,7,8],f32> + return %0 : !torch.vtensor<[1,1,7,8],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_2_3/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_2_3/output_0.npy new file mode 100644 index 000000000..6765cf400 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_2_3/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_2_3/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_2_3/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_2_3/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_3_2/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_3_2/input_0.npy new file mode 100644 index 000000000..12db14385 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_3_2/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_3_2/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_3_2/input_1.npy new file mode 100644 index 000000000..768a59b4b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_3_2/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_3_2/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_3_2/model.mlir new file mode 100644 index 000000000..736e664b2 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_3_2/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_sizes_nearest_axes_3_2(%arg0: !torch.vtensor<[1,1,2,2],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,7,8],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %none, %arg1) {torch.onnx.axes = [3 : si64, 2 : si64], torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,2,2],f32>, !torch.none, !torch.none, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,7,8],f32> + return %0 : !torch.vtensor<[1,1,7,8],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_3_2/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_3_2/output_0.npy new file mode 100644 index 000000000..6765cf400 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_3_2/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_3_2/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_3_2/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_axes_3_2/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_ceil_half_pixel/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_ceil_half_pixel/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_ceil_half_pixel/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_ceil_half_pixel/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_ceil_half_pixel/input_1.npy new file mode 100644 index 000000000..d1affa7bb Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_ceil_half_pixel/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_ceil_half_pixel/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_ceil_half_pixel/model.mlir new file mode 100644 index 000000000..f6aa3b671 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_ceil_half_pixel/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_sizes_nearest_ceil_half_pixel(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,8,8],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %none, %arg1) {torch.onnx.coordinate_transformation_mode = "half_pixel", torch.onnx.mode = "nearest", torch.onnx.nearest_mode = "ceil"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.none, !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,8,8],f32> + return %0 : !torch.vtensor<[1,1,8,8],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_ceil_half_pixel/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_ceil_half_pixel/output_0.npy new file mode 100644 index 000000000..04f9a3540 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_ceil_half_pixel/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_ceil_half_pixel/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_ceil_half_pixel/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_ceil_half_pixel/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_floor_align_corners/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_floor_align_corners/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_floor_align_corners/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_floor_align_corners/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_floor_align_corners/input_1.npy new file mode 100644 index 000000000..d1affa7bb Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_floor_align_corners/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_floor_align_corners/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_floor_align_corners/model.mlir new file mode 100644 index 000000000..c22fa419d --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_floor_align_corners/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_sizes_nearest_floor_align_corners(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,8,8],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %none, %arg1) {torch.onnx.coordinate_transformation_mode = "align_corners", torch.onnx.mode = "nearest", torch.onnx.nearest_mode = "floor"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.none, !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,8,8],f32> + return %0 : !torch.vtensor<[1,1,8,8],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_floor_align_corners/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_floor_align_corners/output_0.npy new file mode 100644 index 000000000..1bbfa5aeb Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_floor_align_corners/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_floor_align_corners/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_floor_align_corners/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_floor_align_corners/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_not_larger/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_not_larger/input_0.npy new file mode 100644 index 000000000..12db14385 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_not_larger/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_not_larger/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_not_larger/input_1.npy new file mode 100644 index 000000000..625a34e3a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_not_larger/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_not_larger/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_not_larger/model.mlir new file mode 100644 index 000000000..f9e943572 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_not_larger/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_sizes_nearest_not_larger(%arg0: !torch.vtensor<[1,1,2,2],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,8,8],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %none, %arg1) {torch.onnx.axes = [2 : si64, 3 : si64], torch.onnx.keep_aspect_ratio_policy = "not_smaller", torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,2,2],f32>, !torch.none, !torch.none, !torch.vtensor<[2],si64>) -> !torch.vtensor<[1,1,8,8],f32> + return %0 : !torch.vtensor<[1,1,8,8],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_not_larger/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_not_larger/output_0.npy new file mode 100644 index 000000000..d66a207ea Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_not_larger/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_not_larger/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_not_larger/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_not_larger/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric/input_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric/input_0.npy new file mode 100644 index 000000000..3303d785b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric/input_1.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric/input_1.npy new file mode 100644 index 000000000..d1affa7bb Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric/model.mlir b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric/model.mlir new file mode 100644 index 000000000..c5515a94c --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric(%arg0: !torch.vtensor<[1,1,4,4],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,8,8],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.Resize"(%arg0, %none, %none, %arg1) {torch.onnx.coordinate_transformation_mode = "asymmetric", torch.onnx.mode = "nearest", torch.onnx.nearest_mode = "round_prefer_ceil"} : (!torch.vtensor<[1,1,4,4],f32>, !torch.none, !torch.none, !torch.vtensor<[4],si64>) -> !torch.vtensor<[1,1,8,8],f32> + return %0 : !torch.vtensor<[1,1,8,8],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric/output_0.npy b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric/output_0.npy new file mode 100644 index 000000000..04f9a3540 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric/test_data_flags.txt b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_reversesequence_batch/model.mlir b/iree_tests/onnx/node/generated/test_reversesequence_batch/model.mlir index 63c1acad3..0436989e3 100644 --- a/iree_tests/onnx/node/generated/test_reversesequence_batch/model.mlir +++ b/iree_tests/onnx/node/generated/test_reversesequence_batch/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reversesequence_batch(%arg0: !torch.vtensor<[4,4],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[4,4],f32> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReverseSequence"(%arg0, %arg1) {torch.onnx.batch_axis = 0 : si64, torch.onnx.time_axis = 1 : si64} : (!torch.vtensor<[4,4],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[4,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReverseSequence"(%arg0, %arg1) {torch.onnx.batch_axis = 0 : si64, torch.onnx.time_axis = 1 : si64} : (!torch.vtensor<[4,4],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[4,4],f32> return %0 : !torch.vtensor<[4,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_reversesequence_time/model.mlir b/iree_tests/onnx/node/generated/test_reversesequence_time/model.mlir index 80cfdedab..35f85b53a 100644 --- a/iree_tests/onnx/node/generated/test_reversesequence_time/model.mlir +++ b/iree_tests/onnx/node/generated/test_reversesequence_time/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_reversesequence_time(%arg0: !torch.vtensor<[4,4],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[4,4],f32> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ReverseSequence"(%arg0, %arg1) {torch.onnx.batch_axis = 1 : si64, torch.onnx.time_axis = 0 : si64} : (!torch.vtensor<[4,4],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[4,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ReverseSequence"(%arg0, %arg1) {torch.onnx.batch_axis = 1 : si64, torch.onnx.time_axis = 0 : si64} : (!torch.vtensor<[4,4],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[4,4],f32> return %0 : !torch.vtensor<[4,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_rnn_seq_length/input_0.npy b/iree_tests/onnx/node/generated/test_rnn_seq_length/input_0.npy new file mode 100644 index 000000000..1be3eac92 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_rnn_seq_length/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_rnn_seq_length/input_1.npy b/iree_tests/onnx/node/generated/test_rnn_seq_length/input_1.npy new file mode 100644 index 000000000..ef200fdf6 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_rnn_seq_length/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_rnn_seq_length/input_2.npy b/iree_tests/onnx/node/generated/test_rnn_seq_length/input_2.npy new file mode 100644 index 000000000..af6acf77f Binary files /dev/null and b/iree_tests/onnx/node/generated/test_rnn_seq_length/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_rnn_seq_length/input_3.npy b/iree_tests/onnx/node/generated/test_rnn_seq_length/input_3.npy new file mode 100644 index 000000000..4e4c61c18 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_rnn_seq_length/input_3.npy differ diff --git a/iree_tests/onnx/node/generated/test_rnn_seq_length/model.mlir b/iree_tests/onnx/node/generated/test_rnn_seq_length/model.mlir new file mode 100644 index 000000000..133a37dca --- /dev/null +++ b/iree_tests/onnx/node/generated/test_rnn_seq_length/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_rnn_seq_length(%arg0: !torch.vtensor<[2,3,3],f32>, %arg1: !torch.vtensor<[1,5,3],f32>, %arg2: !torch.vtensor<[1,5,5],f32>, %arg3: !torch.vtensor<[1,10],f32>) -> !torch.vtensor<[1,3,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.RNN"(%arg0, %arg1, %arg2, %arg3) {torch.onnx.hidden_size = 5 : si64} : (!torch.vtensor<[2,3,3],f32>, !torch.vtensor<[1,5,3],f32>, !torch.vtensor<[1,5,5],f32>, !torch.vtensor<[1,10],f32>) -> (!torch.none, !torch.vtensor<[1,3,5],f32>) + return %0#1 : !torch.vtensor<[1,3,5],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_rnn_seq_length/output_0.npy b/iree_tests/onnx/node/generated/test_rnn_seq_length/output_0.npy new file mode 100644 index 000000000..e4d3b2d31 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_rnn_seq_length/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_rnn_seq_length/test_data_flags.txt b/iree_tests/onnx/node/generated/test_rnn_seq_length/test_data_flags.txt new file mode 100644 index 000000000..fad7bbb82 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_rnn_seq_length/test_data_flags.txt @@ -0,0 +1,5 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--input=@input_3.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_roialign_aligned_false/model.mlir b/iree_tests/onnx/node/generated/test_roialign_aligned_false/model.mlir index db15d0915..593f960e0 100644 --- a/iree_tests/onnx/node/generated/test_roialign_aligned_false/model.mlir +++ b/iree_tests/onnx/node/generated/test_roialign_aligned_false/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_roialign_aligned_false(%arg0: !torch.vtensor<[1,1,10,10],f32>, %arg1: !torch.vtensor<[3,4],f32>, %arg2: !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,1,5,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.RoiAlign"(%arg0, %arg1, %arg2) {torch.onnx.coordinate_transformation_mode = "output_half_pixel", torch.onnx.output_height = 5 : si64, torch.onnx.output_width = 5 : si64, torch.onnx.sampling_ratio = 2 : si64, torch.onnx.spatial_scale = 1.000000e+00 : f32} : (!torch.vtensor<[1,1,10,10],f32>, !torch.vtensor<[3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,1,5,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.RoiAlign"(%arg0, %arg1, %arg2) {torch.onnx.coordinate_transformation_mode = "output_half_pixel", torch.onnx.output_height = 5 : si64, torch.onnx.output_width = 5 : si64, torch.onnx.sampling_ratio = 2 : si64, torch.onnx.spatial_scale = 1.000000e+00 : f32} : (!torch.vtensor<[1,1,10,10],f32>, !torch.vtensor<[3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,1,5,5],f32> return %0 : !torch.vtensor<[3,1,5,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_roialign_aligned_true/model.mlir b/iree_tests/onnx/node/generated/test_roialign_aligned_true/model.mlir index 63fd12bd1..25a9171db 100644 --- a/iree_tests/onnx/node/generated/test_roialign_aligned_true/model.mlir +++ b/iree_tests/onnx/node/generated/test_roialign_aligned_true/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_roialign_aligned_true(%arg0: !torch.vtensor<[1,1,10,10],f32>, %arg1: !torch.vtensor<[3,4],f32>, %arg2: !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,1,5,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.RoiAlign"(%arg0, %arg1, %arg2) {torch.onnx.coordinate_transformation_mode = "half_pixel", torch.onnx.output_height = 5 : si64, torch.onnx.output_width = 5 : si64, torch.onnx.sampling_ratio = 2 : si64, torch.onnx.spatial_scale = 1.000000e+00 : f32} : (!torch.vtensor<[1,1,10,10],f32>, !torch.vtensor<[3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,1,5,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.RoiAlign"(%arg0, %arg1, %arg2) {torch.onnx.coordinate_transformation_mode = "half_pixel", torch.onnx.output_height = 5 : si64, torch.onnx.output_width = 5 : si64, torch.onnx.sampling_ratio = 2 : si64, torch.onnx.spatial_scale = 1.000000e+00 : f32} : (!torch.vtensor<[1,1,10,10],f32>, !torch.vtensor<[3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,1,5,5],f32> return %0 : !torch.vtensor<[3,1,5,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_roialign_mode_max/model.mlir b/iree_tests/onnx/node/generated/test_roialign_mode_max/model.mlir index a382a1b64..80683a152 100644 --- a/iree_tests/onnx/node/generated/test_roialign_mode_max/model.mlir +++ b/iree_tests/onnx/node/generated/test_roialign_mode_max/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_roialign_mode_max(%arg0: !torch.vtensor<[1,1,10,10],f32>, %arg1: !torch.vtensor<[3,4],f32>, %arg2: !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,1,5,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.RoiAlign"(%arg0, %arg1, %arg2) {torch.onnx.coordinate_transformation_mode = "output_half_pixel", torch.onnx.mode = "max", torch.onnx.output_height = 5 : si64, torch.onnx.output_width = 5 : si64, torch.onnx.sampling_ratio = 2 : si64, torch.onnx.spatial_scale = 1.000000e+00 : f32} : (!torch.vtensor<[1,1,10,10],f32>, !torch.vtensor<[3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,1,5,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.RoiAlign"(%arg0, %arg1, %arg2) {torch.onnx.coordinate_transformation_mode = "output_half_pixel", torch.onnx.mode = "max", torch.onnx.output_height = 5 : si64, torch.onnx.output_width = 5 : si64, torch.onnx.sampling_ratio = 2 : si64, torch.onnx.spatial_scale = 1.000000e+00 : f32} : (!torch.vtensor<[1,1,10,10],f32>, !torch.vtensor<[3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,1,5,5],f32> return %0 : !torch.vtensor<[3,1,5,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_round/model.mlir b/iree_tests/onnx/node/generated/test_round/model.mlir index 401ff06d0..30890342c 100644 --- a/iree_tests/onnx/node/generated/test_round/model.mlir +++ b/iree_tests/onnx/node/generated/test_round/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_round(%arg0: !torch.vtensor<[15],f32>) -> !torch.vtensor<[15],f32> attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Round"(%arg0) : (!torch.vtensor<[15],f32>) -> !torch.vtensor<[15],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Round"(%arg0) : (!torch.vtensor<[15],f32>) -> !torch.vtensor<[15],f32> return %0 : !torch.vtensor<[15],f32> } } diff --git a/iree_tests/onnx/node/generated/test_scan9_sum/input_0.npy b/iree_tests/onnx/node/generated/test_scan9_sum/input_0.npy new file mode 100644 index 000000000..e0a86acf2 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_scan9_sum/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_scan9_sum/input_1.npy b/iree_tests/onnx/node/generated/test_scan9_sum/input_1.npy new file mode 100644 index 000000000..4900bf5f0 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_scan9_sum/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_scan9_sum/model.mlir b/iree_tests/onnx/node/generated/test_scan9_sum/model.mlir new file mode 100644 index 000000000..55ffc1c5f --- /dev/null +++ b/iree_tests/onnx/node/generated/test_scan9_sum/model.mlir @@ -0,0 +1,13 @@ +module { + func.func @test_scan9_sum(%arg0: !torch.vtensor<[2],f32>, %arg1: !torch.vtensor<[3,2],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[3,2],f32>) attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.Scan"(%arg0, %arg1) {torch.onnx.num_scan_inputs = 1 : si64} : (!torch.vtensor<[2],f32>, !torch.vtensor<[3,2],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[3,2],f32>) { + ^bb0(%arg2: !torch.vtensor<[2],f32>, %arg3: !torch.vtensor<[2],f32>): + %1 = torch.operator "onnx.Add"(%arg2, %arg3) : (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> + %2 = torch.operator "onnx.Identity"(%1) : (!torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> + torch.operator_terminator %1, %2 : !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32> + } + return %0#0, %0#1 : !torch.vtensor<[2],f32>, !torch.vtensor<[3,2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_scan9_sum/output_0.npy b/iree_tests/onnx/node/generated/test_scan9_sum/output_0.npy new file mode 100644 index 000000000..65c866c55 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_scan9_sum/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_scan9_sum/output_1.npy b/iree_tests/onnx/node/generated/test_scan9_sum/output_1.npy new file mode 100644 index 000000000..414be8335 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_scan9_sum/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_scan9_sum/test_data_flags.txt b/iree_tests/onnx/node/generated/test_scan9_sum/test_data_flags.txt new file mode 100644 index 000000000..54770adc1 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_scan9_sum/test_data_flags.txt @@ -0,0 +1,4 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy diff --git a/iree_tests/onnx/node/generated/test_scan_sum/input_0.npy b/iree_tests/onnx/node/generated/test_scan_sum/input_0.npy new file mode 100644 index 000000000..b92aa732b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_scan_sum/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_scan_sum/input_1.npy b/iree_tests/onnx/node/generated/test_scan_sum/input_1.npy new file mode 100644 index 000000000..05b4233c9 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_scan_sum/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_scan_sum/model.mlir b/iree_tests/onnx/node/generated/test_scan_sum/model.mlir new file mode 100644 index 000000000..27cb24b3f --- /dev/null +++ b/iree_tests/onnx/node/generated/test_scan_sum/model.mlir @@ -0,0 +1,13 @@ +module { + func.func @test_scan_sum(%arg0: !torch.vtensor<[1,2],f32>, %arg1: !torch.vtensor<[1,3,2],f32>) -> (!torch.vtensor<[1,2],f32>, !torch.vtensor<[1,3,2],f32>) attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 8 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.Scan"(%none, %arg0, %arg1) {torch.onnx.num_scan_inputs = 1 : si64} : (!torch.none, !torch.vtensor<[1,2],f32>, !torch.vtensor<[1,3,2],f32>) -> (!torch.vtensor<[1,2],f32>, !torch.vtensor<[1,3,2],f32>) { + ^bb0(%arg2: !torch.vtensor<[2],f32>, %arg3: !torch.vtensor<[2],f32>): + %1 = torch.operator "onnx.Add"(%arg2, %arg3) : (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> + %2 = torch.operator "onnx.Identity"(%1) : (!torch.vtensor<[2],f32>) -> !torch.vtensor<[2],f32> + torch.operator_terminator %1, %2 : !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32> + } + return %0#0, %0#1 : !torch.vtensor<[1,2],f32>, !torch.vtensor<[1,3,2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_scan_sum/output_0.npy b/iree_tests/onnx/node/generated/test_scan_sum/output_0.npy new file mode 100644 index 000000000..e93edf899 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_scan_sum/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_scan_sum/output_1.npy b/iree_tests/onnx/node/generated/test_scan_sum/output_1.npy new file mode 100644 index 000000000..78d0a6085 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_scan_sum/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_scan_sum/test_data_flags.txt b/iree_tests/onnx/node/generated/test_scan_sum/test_data_flags.txt new file mode 100644 index 000000000..54770adc1 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_scan_sum/test_data_flags.txt @@ -0,0 +1,4 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy diff --git a/iree_tests/onnx/node/generated/test_scatter_elements_with_axis/model.mlir b/iree_tests/onnx/node/generated/test_scatter_elements_with_axis/model.mlir index a2e51f075..09a9a92e5 100644 --- a/iree_tests/onnx/node/generated/test_scatter_elements_with_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_scatter_elements_with_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_scatter_elements_with_axis(%arg0: !torch.vtensor<[1,5],f32>, %arg1: !torch.vtensor<[1,2],si64>, %arg2: !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ScatterElements"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[1,5],f32>, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ScatterElements"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[1,5],f32>, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> return %0 : !torch.vtensor<[1,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_scatter_elements_with_duplicate_indices/model.mlir b/iree_tests/onnx/node/generated/test_scatter_elements_with_duplicate_indices/model.mlir index 66cdff4ae..c96afeac4 100644 --- a/iree_tests/onnx/node/generated/test_scatter_elements_with_duplicate_indices/model.mlir +++ b/iree_tests/onnx/node/generated/test_scatter_elements_with_duplicate_indices/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_scatter_elements_with_duplicate_indices(%arg0: !torch.vtensor<[1,5],f32>, %arg1: !torch.vtensor<[1,2],si64>, %arg2: !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ScatterElements"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64, torch.onnx.reduction = "add"} : (!torch.vtensor<[1,5],f32>, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ScatterElements"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64, torch.onnx.reduction = "add"} : (!torch.vtensor<[1,5],f32>, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> return %0 : !torch.vtensor<[1,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_scatter_elements_with_negative_indices/model.mlir b/iree_tests/onnx/node/generated/test_scatter_elements_with_negative_indices/model.mlir index 6d25388ab..8047a482c 100644 --- a/iree_tests/onnx/node/generated/test_scatter_elements_with_negative_indices/model.mlir +++ b/iree_tests/onnx/node/generated/test_scatter_elements_with_negative_indices/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_scatter_elements_with_negative_indices(%arg0: !torch.vtensor<[1,5],f32>, %arg1: !torch.vtensor<[1,2],si64>, %arg2: !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ScatterElements"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[1,5],f32>, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ScatterElements"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[1,5],f32>, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> return %0 : !torch.vtensor<[1,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_scatter_elements_with_reduction_max/model.mlir b/iree_tests/onnx/node/generated/test_scatter_elements_with_reduction_max/model.mlir index 362351645..f073d975a 100644 --- a/iree_tests/onnx/node/generated/test_scatter_elements_with_reduction_max/model.mlir +++ b/iree_tests/onnx/node/generated/test_scatter_elements_with_reduction_max/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_scatter_elements_with_reduction_max(%arg0: !torch.vtensor<[1,5],f32>, %arg1: !torch.vtensor<[1,2],si64>, %arg2: !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ScatterElements"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64, torch.onnx.reduction = "max"} : (!torch.vtensor<[1,5],f32>, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ScatterElements"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64, torch.onnx.reduction = "max"} : (!torch.vtensor<[1,5],f32>, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> return %0 : !torch.vtensor<[1,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_scatter_elements_with_reduction_min/model.mlir b/iree_tests/onnx/node/generated/test_scatter_elements_with_reduction_min/model.mlir index dc8ff1464..38d577603 100644 --- a/iree_tests/onnx/node/generated/test_scatter_elements_with_reduction_min/model.mlir +++ b/iree_tests/onnx/node/generated/test_scatter_elements_with_reduction_min/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_scatter_elements_with_reduction_min(%arg0: !torch.vtensor<[1,5],f32>, %arg1: !torch.vtensor<[1,2],si64>, %arg2: !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ScatterElements"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64, torch.onnx.reduction = "min"} : (!torch.vtensor<[1,5],f32>, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ScatterElements"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64, torch.onnx.reduction = "min"} : (!torch.vtensor<[1,5],f32>, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> return %0 : !torch.vtensor<[1,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_scatter_elements_without_axis/model.mlir b/iree_tests/onnx/node/generated/test_scatter_elements_without_axis/model.mlir index 4a27ebe06..5ba9741be 100644 --- a/iree_tests/onnx/node/generated/test_scatter_elements_without_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_scatter_elements_without_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_scatter_elements_without_axis(%arg0: !torch.vtensor<[3,3],f32>, %arg1: !torch.vtensor<[2,3],si64>, %arg2: !torch.vtensor<[2,3],f32>) -> !torch.vtensor<[3,3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ScatterElements"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3,3],f32>, !torch.vtensor<[2,3],si64>, !torch.vtensor<[2,3],f32>) -> !torch.vtensor<[3,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ScatterElements"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3,3],f32>, !torch.vtensor<[2,3],si64>, !torch.vtensor<[2,3],f32>) -> !torch.vtensor<[3,3],f32> return %0 : !torch.vtensor<[3,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_scatter_with_axis/model.mlir b/iree_tests/onnx/node/generated/test_scatter_with_axis/model.mlir index b0fff21de..889171587 100644 --- a/iree_tests/onnx/node/generated/test_scatter_with_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_scatter_with_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_scatter_with_axis(%arg0: !torch.vtensor<[1,5],f32>, %arg1: !torch.vtensor<[1,2],si64>, %arg2: !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Scatter"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[1,5],f32>, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Scatter"(%arg0, %arg1, %arg2) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[1,5],f32>, !torch.vtensor<[1,2],si64>, !torch.vtensor<[1,2],f32>) -> !torch.vtensor<[1,5],f32> return %0 : !torch.vtensor<[1,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_scatter_without_axis/model.mlir b/iree_tests/onnx/node/generated/test_scatter_without_axis/model.mlir index 02679c370..8a9afc927 100644 --- a/iree_tests/onnx/node/generated/test_scatter_without_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_scatter_without_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_scatter_without_axis(%arg0: !torch.vtensor<[3,3],f32>, %arg1: !torch.vtensor<[2,3],si64>, %arg2: !torch.vtensor<[2,3],f32>) -> !torch.vtensor<[3,3],f32> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Scatter"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3,3],f32>, !torch.vtensor<[2,3],si64>, !torch.vtensor<[2,3],f32>) -> !torch.vtensor<[3,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Scatter"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3,3],f32>, !torch.vtensor<[2,3],si64>, !torch.vtensor<[2,3],f32>) -> !torch.vtensor<[3,3],f32> return %0 : !torch.vtensor<[3,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_scatternd/model.mlir b/iree_tests/onnx/node/generated/test_scatternd/model.mlir index 8a3ac11ab..4386c6866 100644 --- a/iree_tests/onnx/node/generated/test_scatternd/model.mlir +++ b/iree_tests/onnx/node/generated/test_scatternd/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_scatternd(%arg0: !torch.vtensor<[4,4,4],f32>, %arg1: !torch.vtensor<[2,1],si64>, %arg2: !torch.vtensor<[2,4,4],f32>) -> !torch.vtensor<[4,4,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ScatterND"(%arg0, %arg1, %arg2) : (!torch.vtensor<[4,4,4],f32>, !torch.vtensor<[2,1],si64>, !torch.vtensor<[2,4,4],f32>) -> !torch.vtensor<[4,4,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ScatterND"(%arg0, %arg1, %arg2) : (!torch.vtensor<[4,4,4],f32>, !torch.vtensor<[2,1],si64>, !torch.vtensor<[2,4,4],f32>) -> !torch.vtensor<[4,4,4],f32> return %0 : !torch.vtensor<[4,4,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_scatternd_add/model.mlir b/iree_tests/onnx/node/generated/test_scatternd_add/model.mlir index 313acf7d3..a8273a8e1 100644 --- a/iree_tests/onnx/node/generated/test_scatternd_add/model.mlir +++ b/iree_tests/onnx/node/generated/test_scatternd_add/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_scatternd_add(%arg0: !torch.vtensor<[4,4,4],f32>, %arg1: !torch.vtensor<[2,1],si64>, %arg2: !torch.vtensor<[2,4,4],f32>) -> !torch.vtensor<[4,4,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ScatterND"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "add"} : (!torch.vtensor<[4,4,4],f32>, !torch.vtensor<[2,1],si64>, !torch.vtensor<[2,4,4],f32>) -> !torch.vtensor<[4,4,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ScatterND"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "add"} : (!torch.vtensor<[4,4,4],f32>, !torch.vtensor<[2,1],si64>, !torch.vtensor<[2,4,4],f32>) -> !torch.vtensor<[4,4,4],f32> return %0 : !torch.vtensor<[4,4,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_scatternd_max/model.mlir b/iree_tests/onnx/node/generated/test_scatternd_max/model.mlir index 024f38642..56a40100a 100644 --- a/iree_tests/onnx/node/generated/test_scatternd_max/model.mlir +++ b/iree_tests/onnx/node/generated/test_scatternd_max/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_scatternd_max(%arg0: !torch.vtensor<[4,4,4],f32>, %arg1: !torch.vtensor<[2,1],si64>, %arg2: !torch.vtensor<[2,4,4],f32>) -> !torch.vtensor<[4,4,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ScatterND"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "max"} : (!torch.vtensor<[4,4,4],f32>, !torch.vtensor<[2,1],si64>, !torch.vtensor<[2,4,4],f32>) -> !torch.vtensor<[4,4,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ScatterND"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "max"} : (!torch.vtensor<[4,4,4],f32>, !torch.vtensor<[2,1],si64>, !torch.vtensor<[2,4,4],f32>) -> !torch.vtensor<[4,4,4],f32> return %0 : !torch.vtensor<[4,4,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_scatternd_min/model.mlir b/iree_tests/onnx/node/generated/test_scatternd_min/model.mlir index 2d9a1cb9b..7b9f258d4 100644 --- a/iree_tests/onnx/node/generated/test_scatternd_min/model.mlir +++ b/iree_tests/onnx/node/generated/test_scatternd_min/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_scatternd_min(%arg0: !torch.vtensor<[4,4,4],f32>, %arg1: !torch.vtensor<[2,1],si64>, %arg2: !torch.vtensor<[2,4,4],f32>) -> !torch.vtensor<[4,4,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ScatterND"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "min"} : (!torch.vtensor<[4,4,4],f32>, !torch.vtensor<[2,1],si64>, !torch.vtensor<[2,4,4],f32>) -> !torch.vtensor<[4,4,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ScatterND"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "min"} : (!torch.vtensor<[4,4,4],f32>, !torch.vtensor<[2,1],si64>, !torch.vtensor<[2,4,4],f32>) -> !torch.vtensor<[4,4,4],f32> return %0 : !torch.vtensor<[4,4,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_scatternd_multiply/model.mlir b/iree_tests/onnx/node/generated/test_scatternd_multiply/model.mlir index 999628e79..2e3499dda 100644 --- a/iree_tests/onnx/node/generated/test_scatternd_multiply/model.mlir +++ b/iree_tests/onnx/node/generated/test_scatternd_multiply/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_scatternd_multiply(%arg0: !torch.vtensor<[4,4,4],f32>, %arg1: !torch.vtensor<[2,1],si64>, %arg2: !torch.vtensor<[2,4,4],f32>) -> !torch.vtensor<[4,4,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ScatterND"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "mul"} : (!torch.vtensor<[4,4,4],f32>, !torch.vtensor<[2,1],si64>, !torch.vtensor<[2,4,4],f32>) -> !torch.vtensor<[4,4,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ScatterND"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "mul"} : (!torch.vtensor<[4,4,4],f32>, !torch.vtensor<[2,1],si64>, !torch.vtensor<[2,4,4],f32>) -> !torch.vtensor<[4,4,4],f32> return %0 : !torch.vtensor<[4,4,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1_mean_weight_negative_ii/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1_mean_weight_negative_ii/model.mlir index 92f340f6e..273e62bec 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1_mean_weight_negative_ii/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1_mean_weight_negative_ii/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_NCd1_mean_weight_negative_ii(%arg0: !torch.vtensor<[3,5,6],f32>, %arg1: !torch.vtensor<[3,6],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = -1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6],f32>, !torch.vtensor<[3,6],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = -1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6],f32>, !torch.vtensor<[3,6],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1_mean_weight_negative_ii_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1_mean_weight_negative_ii_expanded/model.mlir index 9e70e2090..fad236a2d 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1_mean_weight_negative_ii_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1_mean_weight_negative_ii_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_NCd1_mean_weight_negative_ii_expanded(%arg0: !torch.vtensor<[3,5,6],f32>, %arg1: !torch.vtensor<[3,6],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,6],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,6],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,6],f32>) -> !torch.vtensor<[3,6,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,6,5],f32>) -> !torch.vtensor<[3,6,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,6,5],f32>) -> !torch.vtensor<[3,5,6],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,6],f32>) -> !torch.vtensor<[3],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,6],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = -1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,6],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,6],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,6],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,6],f32>) -> !torch.vtensor<[3,6,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,6,5],f32>) -> !torch.vtensor<[3,6,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,6,5],f32>) -> !torch.vtensor<[3,5,6],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,6],f32>) -> !torch.vtensor<[3],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,6],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = -1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,6],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %7 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1_mean_weight_negative_ii_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1_mean_weight_negative_ii_log_prob/model.mlir index a6df9ed03..f3d86d1b3 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1_mean_weight_negative_ii_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1_mean_weight_negative_ii_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_NCd1_mean_weight_negative_ii_log_prob(%arg0: !torch.vtensor<[3,5,6],f32>, %arg1: !torch.vtensor<[3,6],si64>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,6],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = -1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6],f32>, !torch.vtensor<[3,6],si64>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,6],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = -1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6],f32>, !torch.vtensor<[3,6],si64>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,6],f32>) return %0#0, %0#1 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5,6],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1_mean_weight_negative_ii_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1_mean_weight_negative_ii_log_prob_expanded/model.mlir index aea931c12..9d51cccdb 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1_mean_weight_negative_ii_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1_mean_weight_negative_ii_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_NCd1_mean_weight_negative_ii_log_prob_expanded(%arg0: !torch.vtensor<[3,5,6],f32>, %arg1: !torch.vtensor<[3,6],si64>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,6],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,6],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,6],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,6],f32>) -> !torch.vtensor<[3,6,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,6,5],f32>) -> !torch.vtensor<[3,6,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,6,5],f32>) -> !torch.vtensor<[3,5,6],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,6],f32>) -> !torch.vtensor<[3],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,6],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,6],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = -1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,6],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,6],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,6],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,6],f32>) -> !torch.vtensor<[3,6,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,6,5],f32>) -> !torch.vtensor<[3,6,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,6,5],f32>) -> !torch.vtensor<[3,5,6],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,6],f32>) -> !torch.vtensor<[3],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,6],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,6],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = -1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,6],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %8, %7 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5,6],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_none_no_weight_negative_ii/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_none_no_weight_negative_ii/model.mlir index 8c830ac4a..39507d1be 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_none_no_weight_negative_ii/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_none_no_weight_negative_ii/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_NCd1d2d3_none_no_weight_negative_ii(%arg0: !torch.vtensor<[3,5,6,6,5],f32>, %arg1: !torch.vtensor<[3,6,6,5],si64>) -> !torch.vtensor<[3,6,6,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.ignore_index = -5 : si64, torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5,6,6,5],f32>, !torch.vtensor<[3,6,6,5],si64>) -> !torch.vtensor<[3,6,6,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.ignore_index = -5 : si64, torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5,6,6,5],f32>, !torch.vtensor<[3,6,6,5],si64>) -> !torch.vtensor<[3,6,6,5],f32> return %0 : !torch.vtensor<[3,6,6,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_none_no_weight_negative_ii_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_none_no_weight_negative_ii_expanded/model.mlir index 899d5bda1..944b3d755 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_none_no_weight_negative_ii_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_none_no_weight_negative_ii_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_NCd1d2d3_none_no_weight_negative_ii_expanded(%arg0: !torch.vtensor<[3,5,6,6,5],f32>, %arg1: !torch.vtensor<[3,6,6,5],si64>) -> !torch.vtensor<[3,6,6,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,6,6,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,180],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,180],f32>) -> !torch.vtensor<[3,180,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,180,5],f32>) -> !torch.vtensor<[3,180,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,180,5],f32>) -> !torch.vtensor<[3,5,180],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,6,6,5],f32>) -> !torch.vtensor<[5],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,180],f32>, !torch.vtensor<[5],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.ignore_index = -5 : si64, torch.onnx.reduction = "none"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,6,6,5],si64>) -> !torch.vtensor<[3,6,6,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,6,6,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,180],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,180],f32>) -> !torch.vtensor<[3,180,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,180,5],f32>) -> !torch.vtensor<[3,180,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,180,5],f32>) -> !torch.vtensor<[3,5,180],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,6,6,5],f32>) -> !torch.vtensor<[5],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,180],f32>, !torch.vtensor<[5],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.ignore_index = -5 : si64, torch.onnx.reduction = "none"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,6,6,5],si64>) -> !torch.vtensor<[3,6,6,5],f32> return %7 : !torch.vtensor<[3,6,6,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob/model.mlir index 9e9957c04..96cca2bea 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob(%arg0: !torch.vtensor<[3,5,6,6,5],f32>, %arg1: !torch.vtensor<[3,6,6,5],si64>) -> (!torch.vtensor<[3,6,6,5],f32>, !torch.vtensor<[3,5,6,6,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.ignore_index = -5 : si64, torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5,6,6,5],f32>, !torch.vtensor<[3,6,6,5],si64>) -> (!torch.vtensor<[3,6,6,5],f32>, !torch.vtensor<[3,5,6,6,5],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.ignore_index = -5 : si64, torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5,6,6,5],f32>, !torch.vtensor<[3,6,6,5],si64>) -> (!torch.vtensor<[3,6,6,5],f32>, !torch.vtensor<[3,5,6,6,5],f32>) return %0#0, %0#1 : !torch.vtensor<[3,6,6,5],f32>, !torch.vtensor<[3,5,6,6,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob_expanded/model.mlir index c78834b33..bbe594621 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob_expanded(%arg0: !torch.vtensor<[3,5,6,6,5],f32>, %arg1: !torch.vtensor<[3,6,6,5],si64>) -> (!torch.vtensor<[3,6,6,5],f32>, !torch.vtensor<[3,5,6,6,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,6,6,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,180],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,180],f32>) -> !torch.vtensor<[3,180,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,180,5],f32>) -> !torch.vtensor<[3,180,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,180,5],f32>) -> !torch.vtensor<[3,5,180],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,6,6,5],f32>) -> !torch.vtensor<[5],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,180],f32>, !torch.vtensor<[5],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,6,6,5],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.ignore_index = -5 : si64, torch.onnx.reduction = "none"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,6,6,5],si64>) -> !torch.vtensor<[3,6,6,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,6,6,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,180],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,180],f32>) -> !torch.vtensor<[3,180,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,180,5],f32>) -> !torch.vtensor<[3,180,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,180,5],f32>) -> !torch.vtensor<[3,5,180],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,6,6,5],f32>) -> !torch.vtensor<[5],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,180],f32>, !torch.vtensor<[5],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,6,6,5],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.ignore_index = -5 : si64, torch.onnx.reduction = "none"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,6,6,5],si64>) -> !torch.vtensor<[3,6,6,5],f32> return %8, %7 : !torch.vtensor<[3,6,6,5],f32>, !torch.vtensor<[3,5,6,6,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_sum_weight_high_ii/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_sum_weight_high_ii/model.mlir index 6f46d64b9..7673851e5 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_sum_weight_high_ii/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_sum_weight_high_ii/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_NCd1d2d3_sum_weight_high_ii(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 10 : si64, torch.onnx.reduction = "sum"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 10 : si64, torch.onnx.reduction = "sum"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_sum_weight_high_ii_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_sum_weight_high_ii_expanded/model.mlir index 76ca92de8..1301e1b95 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_sum_weight_high_ii_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_sum_weight_high_ii_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_NCd1d2d3_sum_weight_high_ii_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = 10 : si64, torch.onnx.reduction = "sum"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = 10 : si64, torch.onnx.reduction = "sum"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %7 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_sum_weight_high_ii_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_sum_weight_high_ii_log_prob/model.mlir index d2840079c..afa0b61b0 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_sum_weight_high_ii_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_sum_weight_high_ii_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_NCd1d2d3_sum_weight_high_ii_log_prob(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 10 : si64, torch.onnx.reduction = "sum"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 10 : si64, torch.onnx.reduction = "sum"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) return %0#0, %0#1 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_sum_weight_high_ii_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_sum_weight_high_ii_log_prob_expanded/model.mlir index e4531f386..3372e61bb 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_sum_weight_high_ii_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3_sum_weight_high_ii_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_NCd1d2d3_sum_weight_high_ii_log_prob_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = 10 : si64, torch.onnx.reduction = "sum"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = 10 : si64, torch.onnx.reduction = "sum"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %8, %7 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_mean_weight/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_mean_weight/model.mlir index f9215cf96..e32ac302e 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_mean_weight/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_mean_weight/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_NCd1d2d3d4d5_mean_weight(%arg0: !torch.vtensor<[3,5,6,6,5,3,4],f32>, %arg1: !torch.vtensor<[3,6,6,5,3,4],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_mean_weight_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_mean_weight_expanded/model.mlir index 8ef42ed9d..c9ceee159 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_mean_weight_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_mean_weight_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_NCd1d2d3d4d5_mean_weight_expanded(%arg0: !torch.vtensor<[3,5,6,6,5,3,4],f32>, %arg1: !torch.vtensor<[3,6,6,5,3,4],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2160],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2160],f32>) -> !torch.vtensor<[3,2160,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2160,5],f32>) -> !torch.vtensor<[3,2160,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2160,5],f32>) -> !torch.vtensor<[3,5,2160],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,6,6,5,3,4],f32>) -> !torch.vtensor<[7],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2160],f32>, !torch.vtensor<[7],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2160],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2160],f32>) -> !torch.vtensor<[3,2160,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2160,5],f32>) -> !torch.vtensor<[3,2160,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2160,5],f32>) -> !torch.vtensor<[3,5,2160],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,6,6,5,3,4],f32>) -> !torch.vtensor<[7],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2160],f32>, !torch.vtensor<[7],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %7 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_mean_weight_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_mean_weight_log_prob/model.mlir index 2091461fd..a63a8914c 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_mean_weight_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_mean_weight_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_NCd1d2d3d4d5_mean_weight_log_prob(%arg0: !torch.vtensor<[3,5,6,6,5,3,4],f32>, %arg1: !torch.vtensor<[3,6,6,5,3,4],si64>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,6,6,5,3,4],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,6,6,5,3,4],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,6,6,5,3,4],f32>) return %0#0, %0#1 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5,6,6,5,3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_mean_weight_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_mean_weight_log_prob_expanded/model.mlir index 09bc334c6..cc7cc9c36 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_mean_weight_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_mean_weight_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_NCd1d2d3d4d5_mean_weight_log_prob_expanded(%arg0: !torch.vtensor<[3,5,6,6,5,3,4],f32>, %arg1: !torch.vtensor<[3,6,6,5,3,4],si64>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,6,6,5,3,4],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2160],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2160],f32>) -> !torch.vtensor<[3,2160,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2160,5],f32>) -> !torch.vtensor<[3,2160,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2160,5],f32>) -> !torch.vtensor<[3,5,2160],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,6,6,5,3,4],f32>) -> !torch.vtensor<[7],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2160],f32>, !torch.vtensor<[7],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,6,6,5,3,4],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2160],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2160],f32>) -> !torch.vtensor<[3,2160,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2160,5],f32>) -> !torch.vtensor<[3,2160,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2160,5],f32>) -> !torch.vtensor<[3,5,2160],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,6,6,5,3,4],f32>) -> !torch.vtensor<[7],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2160],f32>, !torch.vtensor<[7],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,6,6,5,3,4],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %8, %7 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5,6,6,5,3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_none_no_weight/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_none_no_weight/model.mlir index 0c8210889..0c8158da3 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_none_no_weight/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_none_no_weight/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_NCd1d2d3d4d5_none_no_weight(%arg0: !torch.vtensor<[3,5,6,6,5,3,4],f32>, %arg1: !torch.vtensor<[3,6,6,5,3,4],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> return %0 : !torch.vtensor<[3,6,6,5,3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_none_no_weight_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_none_no_weight_expanded/model.mlir index 566ceace1..86a9eeabd 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_none_no_weight_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_none_no_weight_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_NCd1d2d3d4d5_none_no_weight_expanded(%arg0: !torch.vtensor<[3,5,6,6,5,3,4],f32>, %arg1: !torch.vtensor<[3,6,6,5,3,4],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2160],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2160],f32>) -> !torch.vtensor<[3,2160,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2160,5],f32>) -> !torch.vtensor<[3,2160,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2160,5],f32>) -> !torch.vtensor<[3,5,2160],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,6,6,5,3,4],f32>) -> !torch.vtensor<[7],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2160],f32>, !torch.vtensor<[7],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2160],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2160],f32>) -> !torch.vtensor<[3,2160,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2160,5],f32>) -> !torch.vtensor<[3,2160,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2160,5],f32>) -> !torch.vtensor<[3,5,2160],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,6,6,5,3,4],f32>) -> !torch.vtensor<[7],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2160],f32>, !torch.vtensor<[7],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> return %7 : !torch.vtensor<[3,6,6,5,3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_none_no_weight_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_none_no_weight_log_prob/model.mlir index 4377d9f30..87d2d0ded 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_none_no_weight_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_none_no_weight_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_NCd1d2d3d4d5_none_no_weight_log_prob(%arg0: !torch.vtensor<[3,5,6,6,5,3,4],f32>, %arg1: !torch.vtensor<[3,6,6,5,3,4],si64>) -> (!torch.vtensor<[3,6,6,5,3,4],f32>, !torch.vtensor<[3,5,6,6,5,3,4],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>) -> (!torch.vtensor<[3,6,6,5,3,4],f32>, !torch.vtensor<[3,5,6,6,5,3,4],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>) -> (!torch.vtensor<[3,6,6,5,3,4],f32>, !torch.vtensor<[3,5,6,6,5,3,4],f32>) return %0#0, %0#1 : !torch.vtensor<[3,6,6,5,3,4],f32>, !torch.vtensor<[3,5,6,6,5,3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_none_no_weight_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_none_no_weight_log_prob_expanded/model.mlir index 2666b4b8a..3c6c3e79a 100644 --- a/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_none_no_weight_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_NCd1d2d3d4d5_none_no_weight_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_NCd1d2d3d4d5_none_no_weight_log_prob_expanded(%arg0: !torch.vtensor<[3,5,6,6,5,3,4],f32>, %arg1: !torch.vtensor<[3,6,6,5,3,4],si64>) -> (!torch.vtensor<[3,6,6,5,3,4],f32>, !torch.vtensor<[3,5,6,6,5,3,4],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2160],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2160],f32>) -> !torch.vtensor<[3,2160,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2160,5],f32>) -> !torch.vtensor<[3,2160,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2160,5],f32>) -> !torch.vtensor<[3,5,2160],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,6,6,5,3,4],f32>) -> !torch.vtensor<[7],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2160],f32>, !torch.vtensor<[7],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,6,6,5,3,4],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,6,6,5,3,4],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2160],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2160],f32>) -> !torch.vtensor<[3,2160,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2160,5],f32>) -> !torch.vtensor<[3,2160,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2160,5],f32>) -> !torch.vtensor<[3,5,2160],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,6,6,5,3,4],f32>) -> !torch.vtensor<[7],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2160],f32>, !torch.vtensor<[7],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,6,6,5,3,4],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,6,6,5,3,4],si64>) -> !torch.vtensor<[3,6,6,5,3,4],f32> return %8, %7 : !torch.vtensor<[3,6,6,5,3,4],f32>, !torch.vtensor<[3,5,6,6,5,3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean/model.mlir index 76010d862..6e85a410f 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_3d/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_3d/model.mlir index cc01b2055..f75287b73 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_3d(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_3d_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_3d_expanded/model.mlir index 496ff6e9a..89cf19e51 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_3d_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_3d_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_mean_3d_expanded(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3,2,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,2,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,5,2],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3,2,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,2,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,5,2],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> return %7 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_3d_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_3d_log_prob/model.mlir index 974de00fa..28e78f823 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_3d_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_3d_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_3d_log_prob(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32>) return %0#0, %0#1 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_3d_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_3d_log_prob_expanded/model.mlir index b0b9793d3..cfc174544 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_3d_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_3d_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_mean_3d_log_prob_expanded(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3,2,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,2,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,5,2],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,2],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3,2,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,2,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,5,2],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,2],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> return %8, %7 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_expanded/model.mlir index 8901be8b9..1fc2a48fc 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_mean_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> return %7 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_log_prob/model.mlir index 53a3ebeca..3efc74a92 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_log_prob(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) return %0#0, %0#1 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_log_prob_expanded/model.mlir index 5cf0be6dc..c9d83dbab 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_mean_log_prob_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> return %8, %7 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii/model.mlir index 5dd0b2b76..e66e26904 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_no_weight_ii(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_3d/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_3d/model.mlir index 7b638ae60..52dee987a 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_no_weight_ii_3d(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_3d_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_3d_expanded/model.mlir index c1f097515..99f1fa23e 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_3d_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_3d_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_mean_no_weight_ii_3d_expanded(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3,2,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,2,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,5,2],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3,2,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,2,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,5,2],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> return %7 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_3d_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_3d_log_prob/model.mlir index 015b7f972..f900da20a 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_3d_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_3d_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_no_weight_ii_3d_log_prob(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32>) return %0#0, %0#1 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_3d_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_3d_log_prob_expanded/model.mlir index c1aa05dc4..b6e5abfcb 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_3d_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_3d_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_mean_no_weight_ii_3d_log_prob_expanded(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3,2,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,2,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,5,2],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,2],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3,2,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,2,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,5,2],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,2],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2],si64>) -> !torch.vtensor<[],f32> return %8, %7 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_4d/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_4d/model.mlir index 31b237675..2ac3dd153 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_4d/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_4d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_no_weight_ii_4d(%arg0: !torch.vtensor<[3,5,2,7],f32>, %arg1: !torch.vtensor<[3,2,7],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2,7],f32>, !torch.vtensor<[3,2,7],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2,7],f32>, !torch.vtensor<[3,2,7],si64>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_4d_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_4d_expanded/model.mlir index 11e7e5b17..736d6b593 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_4d_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_4d_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_mean_no_weight_ii_4d_expanded(%arg0: !torch.vtensor<[3,5,2,7],f32>, %arg1: !torch.vtensor<[3,2,7],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2,7],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,14],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,14],f32>) -> !torch.vtensor<[3,14,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,14,5],f32>) -> !torch.vtensor<[3,14,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,14,5],f32>) -> !torch.vtensor<[3,5,14],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2,7],f32>) -> !torch.vtensor<[4],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,14],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,7],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2,7],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,14],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,14],f32>) -> !torch.vtensor<[3,14,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,14,5],f32>) -> !torch.vtensor<[3,14,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,14,5],f32>) -> !torch.vtensor<[3,5,14],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2,7],f32>) -> !torch.vtensor<[4],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,14],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,7],si64>) -> !torch.vtensor<[],f32> return %7 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_4d_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_4d_log_prob/model.mlir index bde0032cd..5662787df 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_4d_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_4d_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_no_weight_ii_4d_log_prob(%arg0: !torch.vtensor<[3,5,2,7],f32>, %arg1: !torch.vtensor<[3,2,7],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2,7],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2,7],f32>, !torch.vtensor<[3,2,7],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2,7],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2,7],f32>, !torch.vtensor<[3,2,7],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2,7],f32>) return %0#0, %0#1 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5,2,7],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_4d_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_4d_log_prob_expanded/model.mlir index 17945124a..0eabd1e7e 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_4d_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_4d_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_mean_no_weight_ii_4d_log_prob_expanded(%arg0: !torch.vtensor<[3,5,2,7],f32>, %arg1: !torch.vtensor<[3,2,7],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2,7],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2,7],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,14],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,14],f32>) -> !torch.vtensor<[3,14,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,14,5],f32>) -> !torch.vtensor<[3,14,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,14,5],f32>) -> !torch.vtensor<[3,5,14],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2,7],f32>) -> !torch.vtensor<[4],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,14],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,2,7],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,7],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2,7],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,14],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,14],f32>) -> !torch.vtensor<[3,14,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,14,5],f32>) -> !torch.vtensor<[3,14,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,14,5],f32>) -> !torch.vtensor<[3,5,14],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2,7],f32>) -> !torch.vtensor<[4],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,14],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,2,7],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,7],si64>) -> !torch.vtensor<[],f32> return %8, %7 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5,2,7],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_expanded/model.mlir index 791cdb4f9..ba1c59f7b 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_mean_no_weight_ii_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> return %7 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_log_prob/model.mlir index ccf04fbb4..ac5d0a562 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_no_weight_ii_log_prob(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) return %0#0, %0#1 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_log_prob_expanded/model.mlir index 254531ded..a9ba17b8b 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_no_weight_ii_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_mean_no_weight_ii_log_prob_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> return %8, %7 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_weight/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_weight/model.mlir index 017050ff3..70cef1d7a 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_weight/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_weight/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_weight(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_weight_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_weight_expanded/model.mlir index c8e76b807..04c2bfc1f 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_weight_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_weight_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_mean_weight_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %7 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii/model.mlir index fa2565f6b..859b2ca1a 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_weight_ii(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 0 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 0 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_3d/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_3d/model.mlir index 72826b24a..73e6bdb60 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_weight_ii_3d(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_3d_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_3d_expanded/model.mlir index d6ebbe3b1..59d0621b3 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_3d_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_3d_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_mean_weight_ii_3d_expanded(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3,2,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,2,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,5,2],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = 1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3,2,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,2,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,5,2],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = 1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %7 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_3d_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_3d_log_prob/model.mlir index 7379e9643..67ebcd0a6 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_3d_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_3d_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_weight_ii_3d_log_prob(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3,2],si64>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32>) return %0#0, %0#1 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_3d_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_3d_log_prob_expanded/model.mlir index 6e561dd56..2da661f95 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_3d_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_3d_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_mean_weight_ii_3d_log_prob_expanded(%arg0: !torch.vtensor<[3,5,2],f32>, %arg1: !torch.vtensor<[3,2],si64>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3,2,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,2,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,5,2],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,2],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = 1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,2],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3,2,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,2,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,2,5],f32>) -> !torch.vtensor<[3,5,2],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2],f32>) -> !torch.vtensor<[3],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,2],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,2],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = 1 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %8, %7 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_4d/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_4d/model.mlir index 7d65fe64b..685b481a2 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_4d/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_4d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_weight_ii_4d(%arg0: !torch.vtensor<[3,5,2,7],f32>, %arg1: !torch.vtensor<[3,2,7],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2,7],f32>, !torch.vtensor<[3,2,7],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2,7],f32>, !torch.vtensor<[3,2,7],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_4d_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_4d_expanded/model.mlir index 8f214a15a..45fd9296e 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_4d_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_4d_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_mean_weight_ii_4d_expanded(%arg0: !torch.vtensor<[3,5,2,7],f32>, %arg1: !torch.vtensor<[3,2,7],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2,7],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,14],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,14],f32>) -> !torch.vtensor<[3,14,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,14,5],f32>) -> !torch.vtensor<[3,14,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,14,5],f32>) -> !torch.vtensor<[3,5,14],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2,7],f32>) -> !torch.vtensor<[4],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,14],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,7],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2,7],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,14],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,14],f32>) -> !torch.vtensor<[3,14,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,14,5],f32>) -> !torch.vtensor<[3,14,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,14,5],f32>) -> !torch.vtensor<[3,5,14],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2,7],f32>) -> !torch.vtensor<[4],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,14],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,7],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %7 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_4d_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_4d_log_prob/model.mlir index 99e2ac1bb..2304386ab 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_4d_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_4d_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_weight_ii_4d_log_prob(%arg0: !torch.vtensor<[3,5,2,7],f32>, %arg1: !torch.vtensor<[3,2,7],si64>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2,7],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2,7],f32>, !torch.vtensor<[3,2,7],si64>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2,7],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5,2,7],f32>, !torch.vtensor<[3,2,7],si64>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2,7],f32>) return %0#0, %0#1 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5,2,7],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_4d_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_4d_log_prob_expanded/model.mlir index 5a81effb6..a76df3959 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_4d_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_4d_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_mean_weight_ii_4d_log_prob_expanded(%arg0: !torch.vtensor<[3,5,2,7],f32>, %arg1: !torch.vtensor<[3,2,7],si64>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5,2,7],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2,7],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,14],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,14],f32>) -> !torch.vtensor<[3,14,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,14,5],f32>) -> !torch.vtensor<[3,14,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,14,5],f32>) -> !torch.vtensor<[3,5,14],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2,7],f32>) -> !torch.vtensor<[4],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,14],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,2,7],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,7],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5,2,7],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,14],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,14],f32>) -> !torch.vtensor<[3,14,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,14,5],f32>) -> !torch.vtensor<[3,14,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,14,5],f32>) -> !torch.vtensor<[3,5,14],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5,2,7],f32>) -> !torch.vtensor<[4],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,14],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5,2,7],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = 2 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3,2,7],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %8, %7 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5,2,7],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_expanded/model.mlir index 1141d359b..25bd0f8d8 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_mean_weight_ii_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = 0 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = 0 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %7 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_log_prob/model.mlir index 2540ad15b..7a1bbe076 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_weight_ii_log_prob(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 0 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.ignore_index = 0 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) return %0#0, %0#1 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_log_prob_expanded/model.mlir index 496d05df7..0a7585f66 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_weight_ii_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_mean_weight_ii_log_prob_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = 0 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.ignore_index = 0 : si64, torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %8, %7 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_weight_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_weight_log_prob/model.mlir index 016785d18..a392b710c 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_weight_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_weight_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_mean_weight_log_prob(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) return %0#0, %0#1 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_mean_weight_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_mean_weight_log_prob_expanded/model.mlir index 433cabff4..2aca0f9a5 100644 --- a/iree_tests/onnx/node/generated/test_sce_mean_weight_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_mean_weight_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_mean_weight_log_prob_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.reduction = "mean"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> return %8, %7 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_none/model.mlir b/iree_tests/onnx/node/generated/test_sce_none/model.mlir index 1c22f5035..fb86a5de7 100644 --- a/iree_tests/onnx/node/generated/test_sce_none/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_none/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_none(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_none_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_none_expanded/model.mlir index 45cf2fda3..ab6f4e474 100644 --- a/iree_tests/onnx/node/generated/test_sce_none_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_none_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_none_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> return %7 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_none_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_none_log_prob/model.mlir index d1bf720f8..330a4da35 100644 --- a/iree_tests/onnx/node/generated/test_sce_none_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_none_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_none_log_prob(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> (!torch.vtensor<[3],f32>, !torch.vtensor<[3,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> (!torch.vtensor<[3],f32>, !torch.vtensor<[3,5],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> (!torch.vtensor<[3],f32>, !torch.vtensor<[3,5],f32>) return %0#0, %0#1 : !torch.vtensor<[3],f32>, !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_none_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_none_log_prob_expanded/model.mlir index 24357eb90..0213d1f6a 100644 --- a/iree_tests/onnx/node/generated/test_sce_none_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_none_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_none_log_prob_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> (!torch.vtensor<[3],f32>, !torch.vtensor<[3,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "none"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3],f32> return %8, %7 : !torch.vtensor<[3],f32>, !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_none_weights/model.mlir b/iree_tests/onnx/node/generated/test_sce_none_weights/model.mlir index 99335b2ea..0682b70c0 100644 --- a/iree_tests/onnx/node/generated/test_sce_none_weights/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_none_weights/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_none_weights(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_none_weights_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_none_weights_expanded/model.mlir index 2465a8519..eef7c6252 100644 --- a/iree_tests/onnx/node/generated/test_sce_none_weights_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_none_weights_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_none_weights_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.reduction = "none"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.reduction = "none"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3],f32> return %7 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_none_weights_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_none_weights_log_prob/model.mlir index de196c00b..061cc66d6 100644 --- a/iree_tests/onnx/node/generated/test_sce_none_weights_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_none_weights_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_none_weights_log_prob(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[3],f32>, !torch.vtensor<[3,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[3],f32>, !torch.vtensor<[3,5],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1, %arg2) {torch.onnx.reduction = "none"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> (!torch.vtensor<[3],f32>, !torch.vtensor<[3,5],f32>) return %0#0, %0#1 : !torch.vtensor<[3],f32>, !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_none_weights_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_none_weights_log_prob_expanded/model.mlir index 8ddbf5b06..14a84cc6b 100644 --- a/iree_tests/onnx/node/generated/test_sce_none_weights_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_none_weights_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_none_weights_log_prob_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[5],f32>) -> (!torch.vtensor<[3],f32>, !torch.vtensor<[3,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.reduction = "none"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1, %arg2) {torch.onnx.reduction = "none"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3],f32> return %8, %7 : !torch.vtensor<[3],f32>, !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_sum/model.mlir b/iree_tests/onnx/node/generated/test_sce_sum/model.mlir index 72bdbb736..d8e558d86 100644 --- a/iree_tests/onnx/node/generated/test_sce_sum/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_sum/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_sum(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "sum"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "sum"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> return %0 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_sum_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_sum_expanded/model.mlir index 2bae4d0fa..b107fbad3 100644 --- a/iree_tests/onnx/node/generated/test_sce_sum_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_sum_expanded/model.mlir @@ -1,13 +1,14 @@ module { func.func @test_sce_sum_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "sum"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "sum"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> return %7 : !torch.vtensor<[],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_sum_log_prob/model.mlir b/iree_tests/onnx/node/generated/test_sce_sum_log_prob/model.mlir index 2515631c2..f17934081 100644 --- a/iree_tests/onnx/node/generated/test_sce_sum_log_prob/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_sum_log_prob/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sce_sum_log_prob(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "sum"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.SoftmaxCrossEntropyLoss"(%arg0, %arg1) {torch.onnx.reduction = "sum"} : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) return %0#0, %0#1 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sce_sum_log_prob_expanded/model.mlir b/iree_tests/onnx/node/generated/test_sce_sum_log_prob_expanded/model.mlir index 3d130cba9..b2f41e87b 100644 --- a/iree_tests/onnx/node/generated/test_sce_sum_log_prob_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_sce_sum_log_prob_expanded/model.mlir @@ -1,14 +1,15 @@ module { func.func @test_sce_sum_log_prob_expanded(%arg0: !torch.vtensor<[3,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> (!torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<[0, 0, -1]> : tensor<3xsi64>) : !torch.vtensor<[3],si64> - %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> - %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> - %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> - %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> - %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5],f32> - %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "sum"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<[0, 0, -1]> : tensor<3xsi64>} : () -> !torch.vtensor<[3],si64> + %1 = torch.operator "onnx.Reshape"(%arg0, %0) : (!torch.vtensor<[3,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,5,1],f32> + %2 = torch.operator "onnx.Transpose"(%1) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,5,1],f32>) -> !torch.vtensor<[3,1,5],f32> + %3 = torch.operator "onnx.LogSoftmax"(%2) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %4 = torch.operator "onnx.Transpose"(%3) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,5,1],f32> + %5 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,5],f32>) -> !torch.vtensor<[2],si64> + %6 = torch.operator "onnx.Reshape"(%4, %5) : (!torch.vtensor<[3,5,1],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Identity"(%6) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[3,5],f32> + %8 = torch.operator "onnx.NegativeLogLikelihoodLoss"(%6, %arg1) {torch.onnx.reduction = "sum"} : (!torch.vtensor<[],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[],f32> return %8, %7 : !torch.vtensor<[],f32>, !torch.vtensor<[3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_selu/model.mlir b/iree_tests/onnx/node/generated/test_selu/model.mlir index c084ebcfd..be2b33de8 100644 --- a/iree_tests/onnx/node/generated/test_selu/model.mlir +++ b/iree_tests/onnx/node/generated/test_selu/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_selu(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 6 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Selu"(%arg0) {torch.onnx.alpha = 2.000000e+00 : f32, torch.onnx.gamma = 3.000000e+00 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Selu"(%arg0) {torch.onnx.alpha = 2.000000e+00 : f32, torch.onnx.gamma = 3.000000e+00 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_selu_default/model.mlir b/iree_tests/onnx/node/generated/test_selu_default/model.mlir index 6e078584d..b3ebb5e15 100644 --- a/iree_tests/onnx/node/generated/test_selu_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_selu_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_selu_default(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 6 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Selu"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Selu"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_selu_default_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_selu_default_expanded_ver18/model.mlir index 1570d1801..074d99a3c 100644 --- a/iree_tests/onnx/node/generated/test_selu_default_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_selu_default_expanded_ver18/model.mlir @@ -1,18 +1,19 @@ module { func.func @test_selu_default_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.67326319 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.05070102 : f32} : () -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %6 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %7 = torch.operator "onnx.Mul"(%1, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %8 = torch.operator "onnx.Sub"(%7, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> - %9 = torch.operator "onnx.Mul"(%3, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %10 = torch.operator "onnx.Mul"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %11 = torch.operator "onnx.Less"(%arg0, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> - %12 = torch.operator "onnx.Where"(%11, %9, %10) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.67326319 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.05070102 : f32} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %7 = torch.operator "onnx.Mul"(%1, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %8 = torch.operator "onnx.Sub"(%7, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %9 = torch.operator "onnx.Mul"(%3, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %10 = torch.operator "onnx.Mul"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %11 = torch.operator "onnx.Less"(%arg0, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> + %12 = torch.operator "onnx.Where"(%11, %9, %10) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %12 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_selu_example/model.mlir b/iree_tests/onnx/node/generated/test_selu_example/model.mlir index 3e880e407..12d094772 100644 --- a/iree_tests/onnx/node/generated/test_selu_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_selu_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_selu_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 6 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Selu"(%arg0) {torch.onnx.alpha = 2.000000e+00 : f32, torch.onnx.gamma = 3.000000e+00 : f32} : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Selu"(%arg0) {torch.onnx.alpha = 2.000000e+00 : f32, torch.onnx.gamma = 3.000000e+00 : f32} : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_selu_example_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_selu_example_expanded_ver18/model.mlir index 01e759c4d..8922e096d 100644 --- a/iree_tests/onnx/node/generated/test_selu_example_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_selu_example_expanded_ver18/model.mlir @@ -1,18 +1,19 @@ module { func.func @test_selu_example_expanded_ver18(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 2.000000e+00 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 3.000000e+00 : f32} : () -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %6 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %7 = torch.operator "onnx.Mul"(%1, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %8 = torch.operator "onnx.Sub"(%7, %1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> - %9 = torch.operator "onnx.Mul"(%3, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %10 = torch.operator "onnx.Mul"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %11 = torch.operator "onnx.Less"(%arg0, %5) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],i1> - %12 = torch.operator "onnx.Where"(%11, %9, %10) : (!torch.vtensor<[3],i1>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 2.000000e+00 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 3.000000e+00 : f32} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %7 = torch.operator "onnx.Mul"(%1, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %8 = torch.operator "onnx.Sub"(%7, %1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> + %9 = torch.operator "onnx.Mul"(%3, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %10 = torch.operator "onnx.Mul"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %11 = torch.operator "onnx.Less"(%arg0, %5) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],i1> + %12 = torch.operator "onnx.Where"(%11, %9, %10) : (!torch.vtensor<[3],i1>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %12 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_selu_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_selu_expanded_ver18/model.mlir index 45103f691..76fb88460 100644 --- a/iree_tests/onnx/node/generated/test_selu_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_selu_expanded_ver18/model.mlir @@ -1,18 +1,19 @@ module { func.func @test_selu_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 2.000000e+00 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 3.000000e+00 : f32} : () -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %6 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %7 = torch.operator "onnx.Mul"(%1, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %8 = torch.operator "onnx.Sub"(%7, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> - %9 = torch.operator "onnx.Mul"(%3, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %10 = torch.operator "onnx.Mul"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %11 = torch.operator "onnx.Less"(%arg0, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> - %12 = torch.operator "onnx.Where"(%11, %9, %10) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 2.000000e+00 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 3.000000e+00 : f32} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %7 = torch.operator "onnx.Mul"(%1, %6) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %8 = torch.operator "onnx.Sub"(%7, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %9 = torch.operator "onnx.Mul"(%3, %8) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %10 = torch.operator "onnx.Mul"(%3, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %11 = torch.operator "onnx.Less"(%arg0, %5) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],i1> + %12 = torch.operator "onnx.Where"(%11, %9, %10) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %12 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_shape/model.mlir b/iree_tests/onnx/node/generated/test_shape/model.mlir index fbfec8cf8..729868339 100644 --- a/iree_tests/onnx/node/generated/test_shape/model.mlir +++ b/iree_tests/onnx/node/generated/test_shape/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_shape(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3],si64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3],si64> return %0 : !torch.vtensor<[3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_shape_clip_end/model.mlir b/iree_tests/onnx/node/generated/test_shape_clip_end/model.mlir index b88e74584..1ca5eab1f 100644 --- a/iree_tests/onnx/node/generated/test_shape_clip_end/model.mlir +++ b/iree_tests/onnx/node/generated/test_shape_clip_end/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_shape_clip_end(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3],si64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = 10 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = 10 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3],si64> return %0 : !torch.vtensor<[3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_shape_clip_start/model.mlir b/iree_tests/onnx/node/generated/test_shape_clip_start/model.mlir index 8bee7d30a..b7c7fec04 100644 --- a/iree_tests/onnx/node/generated/test_shape_clip_start/model.mlir +++ b/iree_tests/onnx/node/generated/test_shape_clip_start/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_shape_clip_start(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3],si64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.start = -10 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.start = -10 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3],si64> return %0 : !torch.vtensor<[3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_shape_end_1/model.mlir b/iree_tests/onnx/node/generated/test_shape_end_1/model.mlir index 8e29e5947..fe6994e41 100644 --- a/iree_tests/onnx/node/generated/test_shape_end_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_shape_end_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_shape_end_1(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1],si64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1],si64> return %0 : !torch.vtensor<[1],si64> } } diff --git a/iree_tests/onnx/node/generated/test_shape_end_negative_1/model.mlir b/iree_tests/onnx/node/generated/test_shape_end_negative_1/model.mlir index 1c0bcade1..7390fbcda 100644 --- a/iree_tests/onnx/node/generated/test_shape_end_negative_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_shape_end_negative_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_shape_end_negative_1(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[2],si64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = -1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[2],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = -1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[2],si64> return %0 : !torch.vtensor<[2],si64> } } diff --git a/iree_tests/onnx/node/generated/test_shape_example/model.mlir b/iree_tests/onnx/node/generated/test_shape_example/model.mlir index def4e4443..64e179c9b 100644 --- a/iree_tests/onnx/node/generated/test_shape_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_shape_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_shape_example(%arg0: !torch.vtensor<[2,3],f32>) -> !torch.vtensor<[2],si64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3],f32>) -> !torch.vtensor<[2],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Shape"(%arg0) : (!torch.vtensor<[2,3],f32>) -> !torch.vtensor<[2],si64> return %0 : !torch.vtensor<[2],si64> } } diff --git a/iree_tests/onnx/node/generated/test_shape_start_1/model.mlir b/iree_tests/onnx/node/generated/test_shape_start_1/model.mlir index 4a2ac6f51..637b32507 100644 --- a/iree_tests/onnx/node/generated/test_shape_start_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_shape_start_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_shape_start_1(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[2],si64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.start = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[2],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.start = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[2],si64> return %0 : !torch.vtensor<[2],si64> } } diff --git a/iree_tests/onnx/node/generated/test_shape_start_1_end_2/model.mlir b/iree_tests/onnx/node/generated/test_shape_start_1_end_2/model.mlir index d56524b65..5b1894c2e 100644 --- a/iree_tests/onnx/node/generated/test_shape_start_1_end_2/model.mlir +++ b/iree_tests/onnx/node/generated/test_shape_start_1_end_2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_shape_start_1_end_2(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1],si64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = 2 : si64, torch.onnx.start = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = 2 : si64, torch.onnx.start = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1],si64> return %0 : !torch.vtensor<[1],si64> } } diff --git a/iree_tests/onnx/node/generated/test_shape_start_1_end_negative_1/model.mlir b/iree_tests/onnx/node/generated/test_shape_start_1_end_negative_1/model.mlir index f579406fc..e049f7937 100644 --- a/iree_tests/onnx/node/generated/test_shape_start_1_end_negative_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_shape_start_1_end_negative_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_shape_start_1_end_negative_1(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1],si64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = -1 : si64, torch.onnx.start = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.end = -1 : si64, torch.onnx.start = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1],si64> return %0 : !torch.vtensor<[1],si64> } } diff --git a/iree_tests/onnx/node/generated/test_shape_start_negative_1/model.mlir b/iree_tests/onnx/node/generated/test_shape_start_negative_1/model.mlir index 5767ca387..42cf0aa75 100644 --- a/iree_tests/onnx/node/generated/test_shape_start_negative_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_shape_start_negative_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_shape_start_negative_1(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1],si64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.start = -1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Shape"(%arg0) {torch.onnx.start = -1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1],si64> return %0 : !torch.vtensor<[1],si64> } } diff --git a/iree_tests/onnx/node/generated/test_shrink_hard/model.mlir b/iree_tests/onnx/node/generated/test_shrink_hard/model.mlir index 56dcbfb61..d6320bc15 100644 --- a/iree_tests/onnx/node/generated/test_shrink_hard/model.mlir +++ b/iree_tests/onnx/node/generated/test_shrink_hard/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_shrink_hard(%arg0: !torch.vtensor<[5],f32>) -> !torch.vtensor<[5],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Shrink"(%arg0) {torch.onnx.lambd = 1.500000e+00 : f32} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Shrink"(%arg0) {torch.onnx.lambd = 1.500000e+00 : f32} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[5],f32> return %0 : !torch.vtensor<[5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_shrink_hard_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_shrink_hard_expanded_ver18/model.mlir index 4a65dc03d..4e2c54320 100644 --- a/iree_tests/onnx/node/generated/test_shrink_hard_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_shrink_hard_expanded_ver18/model.mlir @@ -1,18 +1,19 @@ module { func.func @test_shrink_hard_expanded_ver18(%arg0: !torch.vtensor<[5],f32>) -> !torch.vtensor<[5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.500000e+00 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 0.000000e+00 : f32} : () -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> - %6 = torch.operator "onnx.Neg"(%1) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Less"(%arg0, %6) : (!torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],i1> - %8 = torch.operator "onnx.Add"(%arg0, %3) : (!torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> - %9 = torch.operator "onnx.Sub"(%arg0, %3) : (!torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> - %10 = torch.operator "onnx.Less"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[5],i1> - %11 = torch.operator "onnx.Where"(%10, %9, %5) : (!torch.vtensor<[5],i1>, !torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> - %12 = torch.operator "onnx.Where"(%7, %8, %11) : (!torch.vtensor<[5],i1>, !torch.vtensor<[5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.500000e+00 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 0.000000e+00 : f32} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Neg"(%1) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Less"(%arg0, %6) : (!torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],i1> + %8 = torch.operator "onnx.Add"(%arg0, %3) : (!torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> + %9 = torch.operator "onnx.Sub"(%arg0, %3) : (!torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> + %10 = torch.operator "onnx.Less"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[5],i1> + %11 = torch.operator "onnx.Where"(%10, %9, %5) : (!torch.vtensor<[5],i1>, !torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> + %12 = torch.operator "onnx.Where"(%7, %8, %11) : (!torch.vtensor<[5],i1>, !torch.vtensor<[5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[5],f32> return %12 : !torch.vtensor<[5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_shrink_soft/model.mlir b/iree_tests/onnx/node/generated/test_shrink_soft/model.mlir index daa9282ad..33cd54a0a 100644 --- a/iree_tests/onnx/node/generated/test_shrink_soft/model.mlir +++ b/iree_tests/onnx/node/generated/test_shrink_soft/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_shrink_soft(%arg0: !torch.vtensor<[5],f32>) -> !torch.vtensor<[5],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Shrink"(%arg0) {torch.onnx.bias = 1.500000e+00 : f32, torch.onnx.lambd = 1.500000e+00 : f32} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Shrink"(%arg0) {torch.onnx.bias = 1.500000e+00 : f32, torch.onnx.lambd = 1.500000e+00 : f32} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[5],f32> return %0 : !torch.vtensor<[5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_shrink_soft_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_shrink_soft_expanded_ver18/model.mlir index 7b5b9b98d..bc1fe3d9c 100644 --- a/iree_tests/onnx/node/generated/test_shrink_soft_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_shrink_soft_expanded_ver18/model.mlir @@ -1,18 +1,19 @@ module { func.func @test_shrink_soft_expanded_ver18(%arg0: !torch.vtensor<[5],f32>) -> !torch.vtensor<[5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.500000e+00 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.500000e+00 : f32} : () -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> - %4 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> - %6 = torch.operator "onnx.Neg"(%1) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> - %7 = torch.operator "onnx.Less"(%arg0, %6) : (!torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],i1> - %8 = torch.operator "onnx.Add"(%arg0, %3) : (!torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> - %9 = torch.operator "onnx.Sub"(%arg0, %3) : (!torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> - %10 = torch.operator "onnx.Less"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[5],i1> - %11 = torch.operator "onnx.Where"(%10, %9, %5) : (!torch.vtensor<[5],i1>, !torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> - %12 = torch.operator "onnx.Where"(%7, %8, %11) : (!torch.vtensor<[5],i1>, !torch.vtensor<[5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.500000e+00 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.500000e+00 : f32} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %5 = torch.operator "onnx.CastLike"(%4, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %6 = torch.operator "onnx.Neg"(%1) : (!torch.vtensor<[],f32>) -> !torch.vtensor<[],f32> + %7 = torch.operator "onnx.Less"(%arg0, %6) : (!torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],i1> + %8 = torch.operator "onnx.Add"(%arg0, %3) : (!torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> + %9 = torch.operator "onnx.Sub"(%arg0, %3) : (!torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> + %10 = torch.operator "onnx.Less"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[5],i1> + %11 = torch.operator "onnx.Where"(%10, %9, %5) : (!torch.vtensor<[5],i1>, !torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> + %12 = torch.operator "onnx.Where"(%7, %8, %11) : (!torch.vtensor<[5],i1>, !torch.vtensor<[5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[5],f32> return %12 : !torch.vtensor<[5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sigmoid/model.mlir b/iree_tests/onnx/node/generated/test_sigmoid/model.mlir index e98423dac..19c6637cc 100644 --- a/iree_tests/onnx/node/generated/test_sigmoid/model.mlir +++ b/iree_tests/onnx/node/generated/test_sigmoid/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sigmoid(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Sigmoid"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Sigmoid"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sigmoid_example/model.mlir b/iree_tests/onnx/node/generated/test_sigmoid_example/model.mlir index 2c06f27c3..5bbadbf87 100644 --- a/iree_tests/onnx/node/generated/test_sigmoid_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_sigmoid_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sigmoid_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Sigmoid"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Sigmoid"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sign/model.mlir b/iree_tests/onnx/node/generated/test_sign/model.mlir index 2cb528e43..e23d9d14c 100644 --- a/iree_tests/onnx/node/generated/test_sign/model.mlir +++ b/iree_tests/onnx/node/generated/test_sign/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sign(%arg0: !torch.vtensor<[11],f32>) -> !torch.vtensor<[11],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Sign"(%arg0) : (!torch.vtensor<[11],f32>) -> !torch.vtensor<[11],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Sign"(%arg0) : (!torch.vtensor<[11],f32>) -> !torch.vtensor<[11],f32> return %0 : !torch.vtensor<[11],f32> } } diff --git a/iree_tests/onnx/node/generated/test_simple_rnn_batchwise/model.mlir b/iree_tests/onnx/node/generated/test_simple_rnn_batchwise/model.mlir index f4e787f51..6f417f19a 100644 --- a/iree_tests/onnx/node/generated/test_simple_rnn_batchwise/model.mlir +++ b/iree_tests/onnx/node/generated/test_simple_rnn_batchwise/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_simple_rnn_batchwise(%arg0: !torch.vtensor<[3,1,2],f32>, %arg1: !torch.vtensor<[1,4,2],f32>, %arg2: !torch.vtensor<[1,4,4],f32>) -> (!torch.vtensor<[3,1,1,4],f32>, !torch.vtensor<[3,1,4],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.RNN"(%arg0, %arg1, %arg2) {torch.onnx.hidden_size = 4 : si64, torch.onnx.layout = 1 : si64} : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1,4,2],f32>, !torch.vtensor<[1,4,4],f32>) -> (!torch.vtensor<[3,1,1,4],f32>, !torch.vtensor<[3,1,4],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.RNN"(%arg0, %arg1, %arg2) {torch.onnx.hidden_size = 4 : si64, torch.onnx.layout = 1 : si64} : (!torch.vtensor<[3,1,2],f32>, !torch.vtensor<[1,4,2],f32>, !torch.vtensor<[1,4,4],f32>) -> (!torch.vtensor<[3,1,1,4],f32>, !torch.vtensor<[3,1,4],f32>) return %0#0, %0#1 : !torch.vtensor<[3,1,1,4],f32>, !torch.vtensor<[3,1,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_simple_rnn_defaults/input_0.npy b/iree_tests/onnx/node/generated/test_simple_rnn_defaults/input_0.npy new file mode 100644 index 000000000..05b4233c9 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_simple_rnn_defaults/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_simple_rnn_defaults/input_1.npy b/iree_tests/onnx/node/generated/test_simple_rnn_defaults/input_1.npy new file mode 100644 index 000000000..7746f1eb7 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_simple_rnn_defaults/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_simple_rnn_defaults/input_2.npy b/iree_tests/onnx/node/generated/test_simple_rnn_defaults/input_2.npy new file mode 100644 index 000000000..7601ef70d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_simple_rnn_defaults/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_simple_rnn_defaults/model.mlir b/iree_tests/onnx/node/generated/test_simple_rnn_defaults/model.mlir new file mode 100644 index 000000000..a852f56f7 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_simple_rnn_defaults/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_simple_rnn_defaults(%arg0: !torch.vtensor<[1,3,2],f32>, %arg1: !torch.vtensor<[1,4,2],f32>, %arg2: !torch.vtensor<[1,4,4],f32>) -> !torch.vtensor<[1,3,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.RNN"(%arg0, %arg1, %arg2) {torch.onnx.hidden_size = 4 : si64} : (!torch.vtensor<[1,3,2],f32>, !torch.vtensor<[1,4,2],f32>, !torch.vtensor<[1,4,4],f32>) -> (!torch.none, !torch.vtensor<[1,3,4],f32>) + return %0#1 : !torch.vtensor<[1,3,4],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_simple_rnn_defaults/output_0.npy b/iree_tests/onnx/node/generated/test_simple_rnn_defaults/output_0.npy new file mode 100644 index 000000000..c92afbb4a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_simple_rnn_defaults/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_simple_rnn_defaults/test_data_flags.txt b/iree_tests/onnx/node/generated/test_simple_rnn_defaults/test_data_flags.txt new file mode 100644 index 000000000..cb3b7ab77 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_simple_rnn_defaults/test_data_flags.txt @@ -0,0 +1,4 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/input_0.npy b/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/input_0.npy new file mode 100644 index 000000000..b91e0ac1b Binary files /dev/null and b/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/input_1.npy b/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/input_1.npy new file mode 100644 index 000000000..ec6244757 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/input_2.npy b/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/input_2.npy new file mode 100644 index 000000000..ed85a5f51 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/input_3.npy b/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/input_3.npy new file mode 100644 index 000000000..22d28c777 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/input_3.npy differ diff --git a/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/model.mlir b/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/model.mlir new file mode 100644 index 000000000..76b3e7d76 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_simple_rnn_with_initial_bias(%arg0: !torch.vtensor<[1,3,3],f32>, %arg1: !torch.vtensor<[1,5,3],f32>, %arg2: !torch.vtensor<[1,5,5],f32>, %arg3: !torch.vtensor<[1,10],f32>) -> !torch.vtensor<[1,3,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.RNN"(%arg0, %arg1, %arg2, %arg3) {torch.onnx.hidden_size = 5 : si64} : (!torch.vtensor<[1,3,3],f32>, !torch.vtensor<[1,5,3],f32>, !torch.vtensor<[1,5,5],f32>, !torch.vtensor<[1,10],f32>) -> (!torch.none, !torch.vtensor<[1,3,5],f32>) + return %0#1 : !torch.vtensor<[1,3,5],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/output_0.npy b/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/output_0.npy new file mode 100644 index 000000000..d08f49d21 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/test_data_flags.txt b/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/test_data_flags.txt new file mode 100644 index 000000000..fad7bbb82 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_simple_rnn_with_initial_bias/test_data_flags.txt @@ -0,0 +1,5 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--input=@input_3.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_sin/model.mlir b/iree_tests/onnx/node/generated/test_sin/model.mlir index 8e2c55b29..928aa896b 100644 --- a/iree_tests/onnx/node/generated/test_sin/model.mlir +++ b/iree_tests/onnx/node/generated/test_sin/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sin(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Sin"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Sin"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sin_example/model.mlir b/iree_tests/onnx/node/generated/test_sin_example/model.mlir index fb7f3e6e7..e635d3808 100644 --- a/iree_tests/onnx/node/generated/test_sin_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_sin_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sin_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Sin"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Sin"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sinh/model.mlir b/iree_tests/onnx/node/generated/test_sinh/model.mlir index b46de14be..3b5e11d4f 100644 --- a/iree_tests/onnx/node/generated/test_sinh/model.mlir +++ b/iree_tests/onnx/node/generated/test_sinh/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sinh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Sinh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Sinh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sinh_example/model.mlir b/iree_tests/onnx/node/generated/test_sinh_example/model.mlir index 48cb53271..2e6bd657c 100644 --- a/iree_tests/onnx/node/generated/test_sinh_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_sinh_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sinh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Sinh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Sinh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_size/model.mlir b/iree_tests/onnx/node/generated/test_size/model.mlir index 664a6aea4..11ee4ac42 100644 --- a/iree_tests/onnx/node/generated/test_size/model.mlir +++ b/iree_tests/onnx/node/generated/test_size/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_size(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],si64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Size"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Size"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],si64> return %0 : !torch.vtensor<[],si64> } } diff --git a/iree_tests/onnx/node/generated/test_size_example/model.mlir b/iree_tests/onnx/node/generated/test_size_example/model.mlir index 770a368d3..d8867d71c 100644 --- a/iree_tests/onnx/node/generated/test_size_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_size_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_size_example(%arg0: !torch.vtensor<[2,3],f32>) -> !torch.vtensor<[],si64> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Size"(%arg0) : (!torch.vtensor<[2,3],f32>) -> !torch.vtensor<[],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Size"(%arg0) : (!torch.vtensor<[2,3],f32>) -> !torch.vtensor<[],si64> return %0 : !torch.vtensor<[],si64> } } diff --git a/iree_tests/onnx/node/generated/test_slice/model.mlir b/iree_tests/onnx/node/generated/test_slice/model.mlir index c1a1e2597..5188678cd 100644 --- a/iree_tests/onnx/node/generated/test_slice/model.mlir +++ b/iree_tests/onnx/node/generated/test_slice/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_slice(%arg0: !torch.vtensor<[20,10,5],f32>, %arg1: !torch.vtensor<[2],si64>, %arg2: !torch.vtensor<[2],si64>, %arg3: !torch.vtensor<[2],si64>, %arg4: !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,10,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Slice"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[20,10,5],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,10,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Slice"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[20,10,5],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,10,5],f32> return %0 : !torch.vtensor<[3,10,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_slice_default_axes/model.mlir b/iree_tests/onnx/node/generated/test_slice_default_axes/model.mlir index b31b13a46..4ddaf07a2 100644 --- a/iree_tests/onnx/node/generated/test_slice_default_axes/model.mlir +++ b/iree_tests/onnx/node/generated/test_slice_default_axes/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_slice_default_axes(%arg0: !torch.vtensor<[20,10,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[3],si64>) -> !torch.vtensor<[20,10,1],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Slice"(%arg0, %arg1, %arg2) : (!torch.vtensor<[20,10,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[20,10,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Slice"(%arg0, %arg1, %arg2) : (!torch.vtensor<[20,10,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[20,10,1],f32> return %0 : !torch.vtensor<[20,10,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_slice_default_steps/model.mlir b/iree_tests/onnx/node/generated/test_slice_default_steps/model.mlir index 91317d0c0..daf02110a 100644 --- a/iree_tests/onnx/node/generated/test_slice_default_steps/model.mlir +++ b/iree_tests/onnx/node/generated/test_slice_default_steps/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_slice_default_steps(%arg0: !torch.vtensor<[20,10,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[3],si64>, %arg3: !torch.vtensor<[3],si64>) -> !torch.vtensor<[20,10,1],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Slice"(%arg0, %arg1, %arg2, %arg3) : (!torch.vtensor<[20,10,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[20,10,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Slice"(%arg0, %arg1, %arg2, %arg3) : (!torch.vtensor<[20,10,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[20,10,1],f32> return %0 : !torch.vtensor<[20,10,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_slice_end_out_of_bounds/model.mlir b/iree_tests/onnx/node/generated/test_slice_end_out_of_bounds/model.mlir index b64f30b67..64fe48e66 100644 --- a/iree_tests/onnx/node/generated/test_slice_end_out_of_bounds/model.mlir +++ b/iree_tests/onnx/node/generated/test_slice_end_out_of_bounds/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_slice_end_out_of_bounds(%arg0: !torch.vtensor<[20,10,5],f32>, %arg1: !torch.vtensor<[1],si64>, %arg2: !torch.vtensor<[1],si64>, %arg3: !torch.vtensor<[1],si64>, %arg4: !torch.vtensor<[1],si64>) -> !torch.vtensor<[20,9,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Slice"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[20,10,5],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[20,9,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Slice"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[20,10,5],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[20,9,5],f32> return %0 : !torch.vtensor<[20,9,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_slice_neg/model.mlir b/iree_tests/onnx/node/generated/test_slice_neg/model.mlir index 7845c918d..7b43d4e3e 100644 --- a/iree_tests/onnx/node/generated/test_slice_neg/model.mlir +++ b/iree_tests/onnx/node/generated/test_slice_neg/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_slice_neg(%arg0: !torch.vtensor<[20,10,5],f32>, %arg1: !torch.vtensor<[1],si64>, %arg2: !torch.vtensor<[1],si64>, %arg3: !torch.vtensor<[1],si64>, %arg4: !torch.vtensor<[1],si64>) -> !torch.vtensor<[20,9,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Slice"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[20,10,5],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[20,9,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Slice"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[20,10,5],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[20,9,5],f32> return %0 : !torch.vtensor<[20,9,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_slice_neg_steps/model.mlir b/iree_tests/onnx/node/generated/test_slice_neg_steps/model.mlir index 382320fd2..0c2bd6629 100644 --- a/iree_tests/onnx/node/generated/test_slice_neg_steps/model.mlir +++ b/iree_tests/onnx/node/generated/test_slice_neg_steps/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_slice_neg_steps(%arg0: !torch.vtensor<[20,10,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[3],si64>, %arg3: !torch.vtensor<[3],si64>, %arg4: !torch.vtensor<[3],si64>) -> !torch.vtensor<[19,3,2],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Slice"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[20,10,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[19,3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Slice"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[20,10,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[19,3,2],f32> return %0 : !torch.vtensor<[19,3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_slice_negative_axes/model.mlir b/iree_tests/onnx/node/generated/test_slice_negative_axes/model.mlir index e89e2442d..2aa603f55 100644 --- a/iree_tests/onnx/node/generated/test_slice_negative_axes/model.mlir +++ b/iree_tests/onnx/node/generated/test_slice_negative_axes/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_slice_negative_axes(%arg0: !torch.vtensor<[20,10,5],f32>, %arg1: !torch.vtensor<[3],si64>, %arg2: !torch.vtensor<[3],si64>, %arg3: !torch.vtensor<[3],si64>) -> !torch.vtensor<[20,10,1],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Slice"(%arg0, %arg1, %arg2, %arg3) : (!torch.vtensor<[20,10,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[20,10,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Slice"(%arg0, %arg1, %arg2, %arg3) : (!torch.vtensor<[20,10,5],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[20,10,1],f32> return %0 : !torch.vtensor<[20,10,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_slice_start_out_of_bounds/model.mlir b/iree_tests/onnx/node/generated/test_slice_start_out_of_bounds/model.mlir index 0433305ac..a0c1c1c2c 100644 --- a/iree_tests/onnx/node/generated/test_slice_start_out_of_bounds/model.mlir +++ b/iree_tests/onnx/node/generated/test_slice_start_out_of_bounds/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_slice_start_out_of_bounds(%arg0: !torch.vtensor<[20,10,5],f32>, %arg1: !torch.vtensor<[1],si64>, %arg2: !torch.vtensor<[1],si64>, %arg3: !torch.vtensor<[1],si64>, %arg4: !torch.vtensor<[1],si64>) -> !torch.vtensor<[20,0,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Slice"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[20,10,5],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[20,0,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Slice"(%arg0, %arg1, %arg2, %arg3, %arg4) : (!torch.vtensor<[20,10,5],f32>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[20,0,5],f32> return %0 : !torch.vtensor<[20,0,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_axis_0/model.mlir b/iree_tests/onnx/node/generated/test_softmax_axis_0/model.mlir index 2f65c745d..dc7033b93 100644 --- a/iree_tests/onnx/node/generated/test_softmax_axis_0/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_axis_0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_softmax_axis_0(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Softmax"(%arg0) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Softmax"(%arg0) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_axis_0_expanded/model.mlir b/iree_tests/onnx/node/generated/test_softmax_axis_0_expanded/model.mlir index 6f035bd50..c5eff7c3e 100644 --- a/iree_tests/onnx/node/generated/test_softmax_axis_0_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_axis_0_expanded/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_softmax_axis_0_expanded(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [0 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1,4,5],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,4,5],f32> - %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [0 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[1,4,5],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,4,5],f32> + %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %5 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_axis_0_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_softmax_axis_0_expanded_ver18/model.mlir index b56c7a728..f7b3e0b3a 100644 --- a/iree_tests/onnx/node/generated/test_softmax_axis_0_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_axis_0_expanded_ver18/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_softmax_axis_0_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<0> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,4,5],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,4,5],f32> - %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,4,5],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,4,5],f32> + %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %5 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_axis_1/model.mlir b/iree_tests/onnx/node/generated/test_softmax_axis_1/model.mlir index 402e0c854..d0aa78d2b 100644 --- a/iree_tests/onnx/node/generated/test_softmax_axis_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_axis_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_softmax_axis_1(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Softmax"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Softmax"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_axis_1_expanded/model.mlir b/iree_tests/onnx/node/generated/test_softmax_axis_1_expanded/model.mlir index 938ab854b..de1d880c5 100644 --- a/iree_tests/onnx/node/generated/test_softmax_axis_1_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_axis_1_expanded/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_softmax_axis_1_expanded(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,1,5],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,5],f32> - %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,1,5],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,5],f32> + %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %5 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_axis_1_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_softmax_axis_1_expanded_ver18/model.mlir index 8d03e4bec..f196f0757 100644 --- a/iree_tests/onnx/node/generated/test_softmax_axis_1_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_axis_1_expanded_ver18/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_softmax_axis_1_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,5],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,5],f32> - %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,5],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,5],f32> + %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,1,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %5 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_axis_2/model.mlir b/iree_tests/onnx/node/generated/test_softmax_axis_2/model.mlir index 96586d119..37eff0de6 100644 --- a/iree_tests/onnx/node/generated/test_softmax_axis_2/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_axis_2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_softmax_axis_2(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Softmax"(%arg0) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Softmax"(%arg0) {torch.onnx.axis = 2 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_axis_2_expanded/model.mlir b/iree_tests/onnx/node/generated/test_softmax_axis_2_expanded/model.mlir index bc3cf6886..5c1fdfadb 100644 --- a/iree_tests/onnx/node/generated/test_softmax_axis_2_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_axis_2_expanded/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_softmax_axis_2_expanded(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<2> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [2 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [2 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> return %5 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_axis_2_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_softmax_axis_2_expanded_ver18/model.mlir index bf6164519..193048307 100644 --- a/iree_tests/onnx/node/generated/test_softmax_axis_2_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_axis_2_expanded_ver18/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_softmax_axis_2_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<2> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<2> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> return %5 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_default_axis/model.mlir b/iree_tests/onnx/node/generated/test_softmax_default_axis/model.mlir index fa76580d3..8496502b8 100644 --- a/iree_tests/onnx/node/generated/test_softmax_default_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_default_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_softmax_default_axis(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Softmax"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Softmax"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_default_axis_expanded/model.mlir b/iree_tests/onnx/node/generated/test_softmax_default_axis_expanded/model.mlir index 21f72caf4..449666128 100644 --- a/iree_tests/onnx/node/generated/test_softmax_default_axis_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_default_axis_expanded/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_softmax_default_axis_expanded(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [-1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [-1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> return %5 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_default_axis_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_softmax_default_axis_expanded_ver18/model.mlir index 0a601c955..a2fe22820 100644 --- a/iree_tests/onnx/node/generated/test_softmax_default_axis_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_default_axis_expanded_ver18/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_softmax_default_axis_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> return %5 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_example/model.mlir b/iree_tests/onnx/node/generated/test_softmax_example/model.mlir index 1438dfbd4..60454fe51 100644 --- a/iree_tests/onnx/node/generated/test_softmax_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_softmax_example(%arg0: !torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Softmax"(%arg0) : (!torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Softmax"(%arg0) : (!torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> return %0 : !torch.vtensor<[1,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_example_expanded/model.mlir b/iree_tests/onnx/node/generated/test_softmax_example_expanded/model.mlir index a887b0ef1..7a2a6ac9e 100644 --- a/iree_tests/onnx/node/generated/test_softmax_example_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_example_expanded/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_softmax_example_expanded(%arg0: !torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [-1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,3],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> - %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [-1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,3],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,3],f32> return %5 : !torch.vtensor<[1,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_example_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_softmax_example_expanded_ver18/model.mlir index ffb23958c..5f294653e 100644 --- a/iree_tests/onnx/node/generated/test_softmax_example_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_example_expanded_ver18/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_softmax_example_expanded_ver18(%arg0: !torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,3],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> - %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,3],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[1,3],f32>) -> !torch.vtensor<[1,3],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,1],f32> + %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[1,3],f32>, !torch.vtensor<[1,1],f32>) -> !torch.vtensor<[1,3],f32> return %5 : !torch.vtensor<[1,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_large_number/model.mlir b/iree_tests/onnx/node/generated/test_softmax_large_number/model.mlir index 2b16450f8..8fa6d49ef 100644 --- a/iree_tests/onnx/node/generated/test_softmax_large_number/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_large_number/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_softmax_large_number(%arg0: !torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Softmax"(%arg0) : (!torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Softmax"(%arg0) : (!torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> return %0 : !torch.vtensor<[2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_large_number_expanded/model.mlir b/iree_tests/onnx/node/generated/test_softmax_large_number_expanded/model.mlir index 21b67393a..470203703 100644 --- a/iree_tests/onnx/node/generated/test_softmax_large_number_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_large_number_expanded/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_softmax_large_number_expanded(%arg0: !torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [-1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,4],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> - %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [-1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,4],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> + %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,4],f32> return %5 : !torch.vtensor<[2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_large_number_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_softmax_large_number_expanded_ver18/model.mlir index 524dfaab2..aa805c074 100644 --- a/iree_tests/onnx/node/generated/test_softmax_large_number_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_large_number_expanded_ver18/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_softmax_large_number_expanded_ver18(%arg0: !torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,4],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> - %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,4],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[2,4],f32>) -> !torch.vtensor<[2,4],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[2,1],f32> + %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[2,4],f32>, !torch.vtensor<[2,1],f32>) -> !torch.vtensor<[2,4],f32> return %5 : !torch.vtensor<[2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_negative_axis/model.mlir b/iree_tests/onnx/node/generated/test_softmax_negative_axis/model.mlir index 8cf749dbe..9e2143b65 100644 --- a/iree_tests/onnx/node/generated/test_softmax_negative_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_negative_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_softmax_negative_axis(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Softmax"(%arg0) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Softmax"(%arg0) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_negative_axis_expanded/model.mlir b/iree_tests/onnx/node/generated/test_softmax_negative_axis_expanded/model.mlir index 4f1172bbf..611c827b4 100644 --- a/iree_tests/onnx/node/generated/test_softmax_negative_axis_expanded/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_negative_axis_expanded/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_softmax_negative_axis_expanded(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [-1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0) {torch.onnx.axes = [-1 : si64], torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> return %5 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softmax_negative_axis_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_softmax_negative_axis_expanded_ver18/model.mlir index ad48e50b6..74385c10f 100644 --- a/iree_tests/onnx/node/generated/test_softmax_negative_axis_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_softmax_negative_axis_expanded_ver18/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_softmax_negative_axis_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<-1> : tensor<1xsi64>) : !torch.vtensor<[1],si64> - %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> - %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<-1> : tensor<1xsi64>} : () -> !torch.vtensor<[1],si64> + %1 = torch.operator "onnx.ReduceMax"(%arg0, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %2 = torch.operator "onnx.Sub"(%arg0, %1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Exp"(%2) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.ReduceSum"(%3, %0) {torch.onnx.keepdims = 1 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1],f32> + %5 = torch.operator "onnx.Div"(%3, %4) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,1],f32>) -> !torch.vtensor<[3,4,5],f32> return %5 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softplus/model.mlir b/iree_tests/onnx/node/generated/test_softplus/model.mlir index 6acc43cea..7d4963ffc 100644 --- a/iree_tests/onnx/node/generated/test_softplus/model.mlir +++ b/iree_tests/onnx/node/generated/test_softplus/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_softplus(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 1 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Softplus"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Softplus"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softplus_example/model.mlir b/iree_tests/onnx/node/generated/test_softplus_example/model.mlir index c0bd4f817..7883bbfe5 100644 --- a/iree_tests/onnx/node/generated/test_softplus_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_softplus_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_softplus_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 1 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Softplus"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Softplus"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softplus_example_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_softplus_example_expanded_ver18/model.mlir index e9051fdd1..47e17e9d7 100644 --- a/iree_tests/onnx/node/generated/test_softplus_example_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_softplus_example_expanded_ver18/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_softplus_example_expanded_ver18(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %1 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %2 = torch.operator "onnx.CastLike"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.Add"(%0, %2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> - %4 = torch.operator "onnx.Log"(%3) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.CastLike"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Add"(%0, %2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3],f32> + %4 = torch.operator "onnx.Log"(%3) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %4 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softplus_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_softplus_expanded_ver18/model.mlir index a0fe615e6..72f389bea 100644 --- a/iree_tests/onnx/node/generated/test_softplus_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_softplus_expanded_ver18/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_softplus_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %1 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %2 = torch.operator "onnx.CastLike"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %3 = torch.operator "onnx.Add"(%0, %2) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.Log"(%3) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Exp"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %1 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.CastLike"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.Add"(%0, %2) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.Log"(%3) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %4 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softsign/model.mlir b/iree_tests/onnx/node/generated/test_softsign/model.mlir index 81c4169c6..efbf80ae7 100644 --- a/iree_tests/onnx/node/generated/test_softsign/model.mlir +++ b/iree_tests/onnx/node/generated/test_softsign/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_softsign(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 1 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Softsign"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Softsign"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softsign_example/model.mlir b/iree_tests/onnx/node/generated/test_softsign_example/model.mlir index 031364528..289f9ef99 100644 --- a/iree_tests/onnx/node/generated/test_softsign_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_softsign_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_softsign_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 1 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Softsign"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Softsign"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softsign_example_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_softsign_example_expanded_ver18/model.mlir index 6167d644d..ec1d46d58 100644 --- a/iree_tests/onnx/node/generated/test_softsign_example_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_softsign_example_expanded_ver18/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_softsign_example_expanded_ver18(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %3 = torch.operator "onnx.Add"(%1, %2) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> - %4 = torch.operator "onnx.Div"(%arg0, %3) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %3 = torch.operator "onnx.Add"(%1, %2) : (!torch.vtensor<[],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %4 = torch.operator "onnx.Div"(%arg0, %3) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %4 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_softsign_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_softsign_expanded_ver18/model.mlir index da686461d..2af54f812 100644 --- a/iree_tests/onnx/node/generated/test_softsign_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_softsign_expanded_ver18/model.mlir @@ -1,10 +1,11 @@ module { func.func @test_softsign_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.vtensor.literal(dense<1.000000e+00> : tensor) : !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %3 = torch.operator "onnx.Add"(%1, %2) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> - %4 = torch.operator "onnx.Div"(%arg0, %3) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<1.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Abs"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %3 = torch.operator "onnx.Add"(%1, %2) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %4 = torch.operator "onnx.Div"(%arg0, %3) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %4 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_spacetodepth/model.mlir b/iree_tests/onnx/node/generated/test_spacetodepth/model.mlir index dff124a90..a6390e33a 100644 --- a/iree_tests/onnx/node/generated/test_spacetodepth/model.mlir +++ b/iree_tests/onnx/node/generated/test_spacetodepth/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_spacetodepth(%arg0: !torch.vtensor<[2,2,6,6],f32>) -> !torch.vtensor<[2,8,3,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SpaceToDepth"(%arg0) {torch.onnx.blocksize = 2 : si64} : (!torch.vtensor<[2,2,6,6],f32>) -> !torch.vtensor<[2,8,3,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SpaceToDepth"(%arg0) {torch.onnx.blocksize = 2 : si64} : (!torch.vtensor<[2,2,6,6],f32>) -> !torch.vtensor<[2,8,3,3],f32> return %0 : !torch.vtensor<[2,8,3,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_spacetodepth_example/model.mlir b/iree_tests/onnx/node/generated/test_spacetodepth_example/model.mlir index f1a4a6fb5..de79681e0 100644 --- a/iree_tests/onnx/node/generated/test_spacetodepth_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_spacetodepth_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_spacetodepth_example(%arg0: !torch.vtensor<[1,1,4,6],f32>) -> !torch.vtensor<[1,4,2,3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.SpaceToDepth"(%arg0) {torch.onnx.blocksize = 2 : si64} : (!torch.vtensor<[1,1,4,6],f32>) -> !torch.vtensor<[1,4,2,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.SpaceToDepth"(%arg0) {torch.onnx.blocksize = 2 : si64} : (!torch.vtensor<[1,1,4,6],f32>) -> !torch.vtensor<[1,4,2,3],f32> return %0 : !torch.vtensor<[1,4,2,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_split_1d_uneven_split_opset18/model.mlir b/iree_tests/onnx/node/generated/test_split_1d_uneven_split_opset18/model.mlir index fadb089fd..1cf1455d6 100644 --- a/iree_tests/onnx/node/generated/test_split_1d_uneven_split_opset18/model.mlir +++ b/iree_tests/onnx/node/generated/test_split_1d_uneven_split_opset18/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_split_1d_uneven_split_opset18(%arg0: !torch.vtensor<[7],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:4 = torch.operator "onnx.Split"(%arg0) {torch.onnx.num_outputs = 4 : si64} : (!torch.vtensor<[7],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>) + %none = torch.constant.none + %0:4 = torch.operator "onnx.Split"(%arg0) {torch.onnx.num_outputs = 4 : si64} : (!torch.vtensor<[7],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32>) return %0#0, %0#1, %0#2, %0#3 : !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_split_2d_uneven_split_opset18/model.mlir b/iree_tests/onnx/node/generated/test_split_2d_uneven_split_opset18/model.mlir index bc67ca5d4..04faa6596 100644 --- a/iree_tests/onnx/node/generated/test_split_2d_uneven_split_opset18/model.mlir +++ b/iree_tests/onnx/node/generated/test_split_2d_uneven_split_opset18/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_split_2d_uneven_split_opset18(%arg0: !torch.vtensor<[2,8],f32>) -> (!torch.vtensor<[2,3],f32>, !torch.vtensor<[2,3],f32>, !torch.vtensor<[2,2],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.Split"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.num_outputs = 3 : si64} : (!torch.vtensor<[2,8],f32>) -> (!torch.vtensor<[2,3],f32>, !torch.vtensor<[2,3],f32>, !torch.vtensor<[2,2],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.Split"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.num_outputs = 3 : si64} : (!torch.vtensor<[2,8],f32>) -> (!torch.vtensor<[2,3],f32>, !torch.vtensor<[2,3],f32>, !torch.vtensor<[2,2],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2,3],f32>, !torch.vtensor<[2,3],f32>, !torch.vtensor<[2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_split_equal_parts_1d_opset13/model.mlir b/iree_tests/onnx/node/generated/test_split_equal_parts_1d_opset13/model.mlir index 4ae0ca754..d00231a15 100644 --- a/iree_tests/onnx/node/generated/test_split_equal_parts_1d_opset13/model.mlir +++ b/iree_tests/onnx/node/generated/test_split_equal_parts_1d_opset13/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_split_equal_parts_1d_opset13(%arg0: !torch.vtensor<[6],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.Split"(%arg0) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[6],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.Split"(%arg0) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[6],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_split_equal_parts_1d_opset18/model.mlir b/iree_tests/onnx/node/generated/test_split_equal_parts_1d_opset18/model.mlir index 24fbfeda2..ee08f3dc4 100644 --- a/iree_tests/onnx/node/generated/test_split_equal_parts_1d_opset18/model.mlir +++ b/iree_tests/onnx/node/generated/test_split_equal_parts_1d_opset18/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_split_equal_parts_1d_opset18(%arg0: !torch.vtensor<[6],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.Split"(%arg0) {torch.onnx.axis = 0 : si64, torch.onnx.num_outputs = 3 : si64} : (!torch.vtensor<[6],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.Split"(%arg0) {torch.onnx.axis = 0 : si64, torch.onnx.num_outputs = 3 : si64} : (!torch.vtensor<[6],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_split_equal_parts_2d/model.mlir b/iree_tests/onnx/node/generated/test_split_equal_parts_2d/model.mlir index 55fb9a795..bc2c3cf48 100644 --- a/iree_tests/onnx/node/generated/test_split_equal_parts_2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_split_equal_parts_2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_split_equal_parts_2d(%arg0: !torch.vtensor<[2,6],f32>) -> (!torch.vtensor<[2,3],f32>, !torch.vtensor<[2,3],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.Split"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.num_outputs = 2 : si64} : (!torch.vtensor<[2,6],f32>) -> (!torch.vtensor<[2,3],f32>, !torch.vtensor<[2,3],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.Split"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.num_outputs = 2 : si64} : (!torch.vtensor<[2,6],f32>) -> (!torch.vtensor<[2,3],f32>, !torch.vtensor<[2,3],f32>) return %0#0, %0#1 : !torch.vtensor<[2,3],f32>, !torch.vtensor<[2,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_split_equal_parts_2d_opset13/model.mlir b/iree_tests/onnx/node/generated/test_split_equal_parts_2d_opset13/model.mlir index fa93e6746..c35d9a568 100644 --- a/iree_tests/onnx/node/generated/test_split_equal_parts_2d_opset13/model.mlir +++ b/iree_tests/onnx/node/generated/test_split_equal_parts_2d_opset13/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_split_equal_parts_2d_opset13(%arg0: !torch.vtensor<[2,6],f32>) -> (!torch.vtensor<[2,3],f32>, !torch.vtensor<[2,3],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.Split"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,6],f32>) -> (!torch.vtensor<[2,3],f32>, !torch.vtensor<[2,3],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.Split"(%arg0) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,6],f32>) -> (!torch.vtensor<[2,3],f32>, !torch.vtensor<[2,3],f32>) return %0#0, %0#1 : !torch.vtensor<[2,3],f32>, !torch.vtensor<[2,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_split_equal_parts_default_axis_opset13/model.mlir b/iree_tests/onnx/node/generated/test_split_equal_parts_default_axis_opset13/model.mlir index cdc903dc1..320bcea4e 100644 --- a/iree_tests/onnx/node/generated/test_split_equal_parts_default_axis_opset13/model.mlir +++ b/iree_tests/onnx/node/generated/test_split_equal_parts_default_axis_opset13/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_split_equal_parts_default_axis_opset13(%arg0: !torch.vtensor<[6],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.Split"(%arg0) : (!torch.vtensor<[6],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.Split"(%arg0) : (!torch.vtensor<[6],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_split_equal_parts_default_axis_opset18/model.mlir b/iree_tests/onnx/node/generated/test_split_equal_parts_default_axis_opset18/model.mlir index 83d1ec258..c70591541 100644 --- a/iree_tests/onnx/node/generated/test_split_equal_parts_default_axis_opset18/model.mlir +++ b/iree_tests/onnx/node/generated/test_split_equal_parts_default_axis_opset18/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_split_equal_parts_default_axis_opset18(%arg0: !torch.vtensor<[6],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.Split"(%arg0) {torch.onnx.num_outputs = 3 : si64} : (!torch.vtensor<[6],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.Split"(%arg0) {torch.onnx.num_outputs = 3 : si64} : (!torch.vtensor<[6],f32>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32>, !torch.vtensor<[2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_split_variable_parts_1d_opset13/model.mlir b/iree_tests/onnx/node/generated/test_split_variable_parts_1d_opset13/model.mlir index a1b59bb68..f12efa2e4 100644 --- a/iree_tests/onnx/node/generated/test_split_variable_parts_1d_opset13/model.mlir +++ b/iree_tests/onnx/node/generated/test_split_variable_parts_1d_opset13/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_split_variable_parts_1d_opset13(%arg0: !torch.vtensor<[6],f32>, %arg1: !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[4],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.Split"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[6],f32>, !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[4],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.Split"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[6],f32>, !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[4],f32>) return %0#0, %0#1 : !torch.vtensor<[2],f32>, !torch.vtensor<[4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_split_variable_parts_1d_opset18/model.mlir b/iree_tests/onnx/node/generated/test_split_variable_parts_1d_opset18/model.mlir index 93ee4c440..c48c34e4c 100644 --- a/iree_tests/onnx/node/generated/test_split_variable_parts_1d_opset18/model.mlir +++ b/iree_tests/onnx/node/generated/test_split_variable_parts_1d_opset18/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_split_variable_parts_1d_opset18(%arg0: !torch.vtensor<[6],f32>, %arg1: !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[4],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.Split"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[6],f32>, !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[4],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.Split"(%arg0, %arg1) {torch.onnx.axis = 0 : si64} : (!torch.vtensor<[6],f32>, !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[4],f32>) return %0#0, %0#1 : !torch.vtensor<[2],f32>, !torch.vtensor<[4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_split_variable_parts_2d_opset13/model.mlir b/iree_tests/onnx/node/generated/test_split_variable_parts_2d_opset13/model.mlir index 2a6ccb499..42bf63a64 100644 --- a/iree_tests/onnx/node/generated/test_split_variable_parts_2d_opset13/model.mlir +++ b/iree_tests/onnx/node/generated/test_split_variable_parts_2d_opset13/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_split_variable_parts_2d_opset13(%arg0: !torch.vtensor<[2,6],f32>, %arg1: !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2,4],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.Split"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,6],f32>, !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2,4],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.Split"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,6],f32>, !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2,4],f32>) return %0#0, %0#1 : !torch.vtensor<[2,2],f32>, !torch.vtensor<[2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_split_variable_parts_2d_opset18/model.mlir b/iree_tests/onnx/node/generated/test_split_variable_parts_2d_opset18/model.mlir index 99647d1f2..143d9665b 100644 --- a/iree_tests/onnx/node/generated/test_split_variable_parts_2d_opset18/model.mlir +++ b/iree_tests/onnx/node/generated/test_split_variable_parts_2d_opset18/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_split_variable_parts_2d_opset18(%arg0: !torch.vtensor<[2,6],f32>, %arg1: !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2,4],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.Split"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,6],f32>, !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2,4],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.Split"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[2,6],f32>, !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2,4],f32>) return %0#0, %0#1 : !torch.vtensor<[2,2],f32>, !torch.vtensor<[2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_split_variable_parts_default_axis_opset13/model.mlir b/iree_tests/onnx/node/generated/test_split_variable_parts_default_axis_opset13/model.mlir index cede9b170..21625b643 100644 --- a/iree_tests/onnx/node/generated/test_split_variable_parts_default_axis_opset13/model.mlir +++ b/iree_tests/onnx/node/generated/test_split_variable_parts_default_axis_opset13/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_split_variable_parts_default_axis_opset13(%arg0: !torch.vtensor<[6],f32>, %arg1: !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[4],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.Split"(%arg0, %arg1) : (!torch.vtensor<[6],f32>, !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[4],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.Split"(%arg0, %arg1) : (!torch.vtensor<[6],f32>, !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[4],f32>) return %0#0, %0#1 : !torch.vtensor<[2],f32>, !torch.vtensor<[4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_split_variable_parts_default_axis_opset18/model.mlir b/iree_tests/onnx/node/generated/test_split_variable_parts_default_axis_opset18/model.mlir index 56d017bbb..8d7487c4d 100644 --- a/iree_tests/onnx/node/generated/test_split_variable_parts_default_axis_opset18/model.mlir +++ b/iree_tests/onnx/node/generated/test_split_variable_parts_default_axis_opset18/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_split_variable_parts_default_axis_opset18(%arg0: !torch.vtensor<[6],f32>, %arg1: !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[4],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.Split"(%arg0, %arg1) : (!torch.vtensor<[6],f32>, !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[4],f32>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.Split"(%arg0, %arg1) : (!torch.vtensor<[6],f32>, !torch.vtensor<[2],si64>) -> (!torch.vtensor<[2],f32>, !torch.vtensor<[4],f32>) return %0#0, %0#1 : !torch.vtensor<[2],f32>, !torch.vtensor<[4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_split_zero_size_splits_opset13/model.mlir b/iree_tests/onnx/node/generated/test_split_zero_size_splits_opset13/model.mlir index 26a002024..fe4774abd 100644 --- a/iree_tests/onnx/node/generated/test_split_zero_size_splits_opset13/model.mlir +++ b/iree_tests/onnx/node/generated/test_split_zero_size_splits_opset13/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_split_zero_size_splits_opset13(%arg0: !torch.vtensor<[0],f32>, %arg1: !torch.vtensor<[3],si64>) -> (!torch.vtensor<[0],f32>, !torch.vtensor<[0],f32>, !torch.vtensor<[0],f32>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.Split"(%arg0, %arg1) : (!torch.vtensor<[0],f32>, !torch.vtensor<[3],si64>) -> (!torch.vtensor<[0],f32>, !torch.vtensor<[0],f32>, !torch.vtensor<[0],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.Split"(%arg0, %arg1) : (!torch.vtensor<[0],f32>, !torch.vtensor<[3],si64>) -> (!torch.vtensor<[0],f32>, !torch.vtensor<[0],f32>, !torch.vtensor<[0],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[0],f32>, !torch.vtensor<[0],f32>, !torch.vtensor<[0],f32> } } diff --git a/iree_tests/onnx/node/generated/test_split_zero_size_splits_opset18/model.mlir b/iree_tests/onnx/node/generated/test_split_zero_size_splits_opset18/model.mlir index b1f5f479d..8c1fd45cc 100644 --- a/iree_tests/onnx/node/generated/test_split_zero_size_splits_opset18/model.mlir +++ b/iree_tests/onnx/node/generated/test_split_zero_size_splits_opset18/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_split_zero_size_splits_opset18(%arg0: !torch.vtensor<[0],f32>, %arg1: !torch.vtensor<[3],si64>) -> (!torch.vtensor<[0],f32>, !torch.vtensor<[0],f32>, !torch.vtensor<[0],f32>) attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:3 = torch.operator "onnx.Split"(%arg0, %arg1) : (!torch.vtensor<[0],f32>, !torch.vtensor<[3],si64>) -> (!torch.vtensor<[0],f32>, !torch.vtensor<[0],f32>, !torch.vtensor<[0],f32>) + %none = torch.constant.none + %0:3 = torch.operator "onnx.Split"(%arg0, %arg1) : (!torch.vtensor<[0],f32>, !torch.vtensor<[3],si64>) -> (!torch.vtensor<[0],f32>, !torch.vtensor<[0],f32>, !torch.vtensor<[0],f32>) return %0#0, %0#1, %0#2 : !torch.vtensor<[0],f32>, !torch.vtensor<[0],f32>, !torch.vtensor<[0],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sqrt/model.mlir b/iree_tests/onnx/node/generated/test_sqrt/model.mlir index 4fdf81cba..99b5f1a37 100644 --- a/iree_tests/onnx/node/generated/test_sqrt/model.mlir +++ b/iree_tests/onnx/node/generated/test_sqrt/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sqrt(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Sqrt"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Sqrt"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sqrt_example/model.mlir b/iree_tests/onnx/node/generated/test_sqrt_example/model.mlir index 20ac55037..0ae2b8b40 100644 --- a/iree_tests/onnx/node/generated/test_sqrt_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_sqrt_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sqrt_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Sqrt"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Sqrt"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_squeeze/model.mlir b/iree_tests/onnx/node/generated/test_squeeze/model.mlir index 7d37ec603..2d3efe11f 100644 --- a/iree_tests/onnx/node/generated/test_squeeze/model.mlir +++ b/iree_tests/onnx/node/generated/test_squeeze/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_squeeze(%arg0: !torch.vtensor<[1,3,4,5],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Squeeze"(%arg0, %arg1) : (!torch.vtensor<[1,3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Squeeze"(%arg0, %arg1) : (!torch.vtensor<[1,3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_squeeze_negative_axes/model.mlir b/iree_tests/onnx/node/generated/test_squeeze_negative_axes/model.mlir index b1646ea9a..859a504e5 100644 --- a/iree_tests/onnx/node/generated/test_squeeze_negative_axes/model.mlir +++ b/iree_tests/onnx/node/generated/test_squeeze_negative_axes/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_squeeze_negative_axes(%arg0: !torch.vtensor<[1,3,1,5],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,3,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Squeeze"(%arg0, %arg1) : (!torch.vtensor<[1,3,1,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,3,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Squeeze"(%arg0, %arg1) : (!torch.vtensor<[1,3,1,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,3,5],f32> return %0 : !torch.vtensor<[1,3,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_stft/input_0.npy b/iree_tests/onnx/node/generated/test_stft/input_0.npy new file mode 100644 index 000000000..baf0e5167 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_stft/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_stft/input_1.npy b/iree_tests/onnx/node/generated/test_stft/input_1.npy new file mode 100644 index 000000000..0c3f64398 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_stft/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_stft/input_2.npy b/iree_tests/onnx/node/generated/test_stft/input_2.npy new file mode 100644 index 000000000..98bc3a302 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_stft/input_2.npy differ diff --git a/iree_tests/onnx/node/generated/test_stft/model.mlir b/iree_tests/onnx/node/generated/test_stft/model.mlir new file mode 100644 index 000000000..e66ed3934 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_stft/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_stft(%arg0: !torch.vtensor<[1,128,1],f32>, %arg1: !torch.vtensor<[],si64>, %arg2: !torch.vtensor<[],si64>) -> !torch.vtensor<[1,15,9,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.STFT"(%arg0, %arg1, %none, %arg2) : (!torch.vtensor<[1,128,1],f32>, !torch.vtensor<[],si64>, !torch.none, !torch.vtensor<[],si64>) -> !torch.vtensor<[1,15,9,2],f32> + return %0 : !torch.vtensor<[1,15,9,2],f32> + } +} + diff --git a/iree_tests/onnx/node/generated/test_stft/output_0.npy b/iree_tests/onnx/node/generated/test_stft/output_0.npy new file mode 100644 index 000000000..b23a05ba4 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_stft/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_stft/test_data_flags.txt b/iree_tests/onnx/node/generated/test_stft/test_data_flags.txt new file mode 100644 index 000000000..cb3b7ab77 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_stft/test_data_flags.txt @@ -0,0 +1,4 @@ +--input=@input_0.npy +--input=@input_1.npy +--input=@input_2.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_stft_with_window/model.mlir b/iree_tests/onnx/node/generated/test_stft_with_window/model.mlir index 57e703061..a4cc3cd39 100644 --- a/iree_tests/onnx/node/generated/test_stft_with_window/model.mlir +++ b/iree_tests/onnx/node/generated/test_stft_with_window/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_stft_with_window(%arg0: !torch.vtensor<[1,128,1],f32>, %arg1: !torch.vtensor<[],si64>, %arg2: !torch.vtensor<[16],f32>) -> !torch.vtensor<[1,15,9,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 17 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.STFT"(%arg0, %arg1, %arg2) : (!torch.vtensor<[1,128,1],f32>, !torch.vtensor<[],si64>, !torch.vtensor<[16],f32>) -> !torch.vtensor<[1,15,9,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.STFT"(%arg0, %arg1, %arg2) : (!torch.vtensor<[1,128,1],f32>, !torch.vtensor<[],si64>, !torch.vtensor<[16],f32>) -> !torch.vtensor<[1,15,9,2],f32> return %0 : !torch.vtensor<[1,15,9,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_string_concat/input_0.npy b/iree_tests/onnx/node/generated/test_string_concat/input_0.npy new file mode 100644 index 000000000..b94026fca Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_concat/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_concat/input_1.npy b/iree_tests/onnx/node/generated/test_string_concat/input_1.npy new file mode 100644 index 000000000..88ed854f5 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_concat/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_concat/model.mlir b/iree_tests/onnx/node/generated/test_string_concat/model.mlir new file mode 100644 index 000000000..0ba6e8f70 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_concat/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_string_concat(%arg0: !torch.vtensor<[2],!torch.str>, %arg1: !torch.vtensor<[2],!torch.str>) -> !torch.vtensor<[2],!torch.str> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.StringConcat"(%arg0, %arg1) : (!torch.vtensor<[2],!torch.str>, !torch.vtensor<[2],!torch.str>) -> !torch.vtensor<[2],!torch.str> + return %0 : !torch.vtensor<[2],!torch.str> + } +} + diff --git a/iree_tests/onnx/node/generated/test_string_concat/output_0.npy b/iree_tests/onnx/node/generated/test_string_concat/output_0.npy new file mode 100644 index 000000000..d2fc0ad24 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_concat/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_concat/test_data_flags.txt b/iree_tests/onnx/node/generated/test_string_concat/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_concat/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_string_concat_broadcasting/input_0.npy b/iree_tests/onnx/node/generated/test_string_concat_broadcasting/input_0.npy new file mode 100644 index 000000000..169525ac1 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_concat_broadcasting/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_concat_broadcasting/input_1.npy b/iree_tests/onnx/node/generated/test_string_concat_broadcasting/input_1.npy new file mode 100644 index 000000000..8c92eb76e Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_concat_broadcasting/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_concat_broadcasting/model.mlir b/iree_tests/onnx/node/generated/test_string_concat_broadcasting/model.mlir new file mode 100644 index 000000000..4981de179 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_concat_broadcasting/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_string_concat_broadcasting(%arg0: !torch.vtensor<[3],!torch.str>, %arg1: !torch.vtensor<[1],!torch.str>) -> !torch.vtensor<[3],!torch.str> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.StringConcat"(%arg0, %arg1) : (!torch.vtensor<[3],!torch.str>, !torch.vtensor<[1],!torch.str>) -> !torch.vtensor<[3],!torch.str> + return %0 : !torch.vtensor<[3],!torch.str> + } +} + diff --git a/iree_tests/onnx/node/generated/test_string_concat_broadcasting/output_0.npy b/iree_tests/onnx/node/generated/test_string_concat_broadcasting/output_0.npy new file mode 100644 index 000000000..64aa6bc37 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_concat_broadcasting/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_concat_broadcasting/test_data_flags.txt b/iree_tests/onnx/node/generated/test_string_concat_broadcasting/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_concat_broadcasting/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_string_concat_empty_string/input_0.npy b/iree_tests/onnx/node/generated/test_string_concat_empty_string/input_0.npy new file mode 100644 index 000000000..9318dd377 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_concat_empty_string/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_concat_empty_string/input_1.npy b/iree_tests/onnx/node/generated/test_string_concat_empty_string/input_1.npy new file mode 100644 index 000000000..495f2837d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_concat_empty_string/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_concat_empty_string/model.mlir b/iree_tests/onnx/node/generated/test_string_concat_empty_string/model.mlir new file mode 100644 index 000000000..d4b97fa85 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_concat_empty_string/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_string_concat_empty_string(%arg0: !torch.vtensor<[2],!torch.str>, %arg1: !torch.vtensor<[2],!torch.str>) -> !torch.vtensor<[2],!torch.str> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.StringConcat"(%arg0, %arg1) : (!torch.vtensor<[2],!torch.str>, !torch.vtensor<[2],!torch.str>) -> !torch.vtensor<[2],!torch.str> + return %0 : !torch.vtensor<[2],!torch.str> + } +} + diff --git a/iree_tests/onnx/node/generated/test_string_concat_empty_string/output_0.npy b/iree_tests/onnx/node/generated/test_string_concat_empty_string/output_0.npy new file mode 100644 index 000000000..27d328311 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_concat_empty_string/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_concat_empty_string/test_data_flags.txt b/iree_tests/onnx/node/generated/test_string_concat_empty_string/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_concat_empty_string/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_string_concat_utf8/input_0.npy b/iree_tests/onnx/node/generated/test_string_concat_utf8/input_0.npy new file mode 100644 index 000000000..36fa976cb Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_concat_utf8/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_concat_utf8/input_1.npy b/iree_tests/onnx/node/generated/test_string_concat_utf8/input_1.npy new file mode 100644 index 000000000..36fa976cb Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_concat_utf8/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_concat_utf8/model.mlir b/iree_tests/onnx/node/generated/test_string_concat_utf8/model.mlir new file mode 100644 index 000000000..616cca15a --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_concat_utf8/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_string_concat_utf8(%arg0: !torch.vtensor<[2],!torch.str>, %arg1: !torch.vtensor<[2],!torch.str>) -> !torch.vtensor<[2],!torch.str> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.StringConcat"(%arg0, %arg1) : (!torch.vtensor<[2],!torch.str>, !torch.vtensor<[2],!torch.str>) -> !torch.vtensor<[2],!torch.str> + return %0 : !torch.vtensor<[2],!torch.str> + } +} + diff --git a/iree_tests/onnx/node/generated/test_string_concat_utf8/output_0.npy b/iree_tests/onnx/node/generated/test_string_concat_utf8/output_0.npy new file mode 100644 index 000000000..702a5c344 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_concat_utf8/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_concat_utf8/test_data_flags.txt b/iree_tests/onnx/node/generated/test_string_concat_utf8/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_concat_utf8/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_string_concat_zero_dimensional/input_0.npy b/iree_tests/onnx/node/generated/test_string_concat_zero_dimensional/input_0.npy new file mode 100644 index 000000000..640ab9f20 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_concat_zero_dimensional/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_concat_zero_dimensional/input_1.npy b/iree_tests/onnx/node/generated/test_string_concat_zero_dimensional/input_1.npy new file mode 100644 index 000000000..a9fac3f17 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_concat_zero_dimensional/input_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_concat_zero_dimensional/model.mlir b/iree_tests/onnx/node/generated/test_string_concat_zero_dimensional/model.mlir new file mode 100644 index 000000000..db9e1f82d --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_concat_zero_dimensional/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_string_concat_zero_dimensional(%arg0: !torch.vtensor<[],!torch.str>, %arg1: !torch.vtensor<[],!torch.str>) -> !torch.vtensor<[],!torch.str> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.StringConcat"(%arg0, %arg1) : (!torch.vtensor<[],!torch.str>, !torch.vtensor<[],!torch.str>) -> !torch.vtensor<[],!torch.str> + return %0 : !torch.vtensor<[],!torch.str> + } +} + diff --git a/iree_tests/onnx/node/generated/test_string_concat_zero_dimensional/output_0.npy b/iree_tests/onnx/node/generated/test_string_concat_zero_dimensional/output_0.npy new file mode 100644 index 000000000..a967e7171 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_concat_zero_dimensional/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_concat_zero_dimensional/test_data_flags.txt b/iree_tests/onnx/node/generated/test_string_concat_zero_dimensional/test_data_flags.txt new file mode 100644 index 000000000..e952cbe31 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_concat_zero_dimensional/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--input=@input_1.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_string_split_basic/input_0.npy b/iree_tests/onnx/node/generated/test_string_split_basic/input_0.npy new file mode 100644 index 000000000..d2fc0ad24 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_basic/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_basic/model.mlir b/iree_tests/onnx/node/generated/test_string_split_basic/model.mlir new file mode 100644 index 000000000..c3f245701 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_split_basic/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_string_split_basic(%arg0: !torch.vtensor<[2],!torch.str>) -> (!torch.vtensor<[2,2],!torch.str>, !torch.vtensor<[2],si64>) attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.StringSplit"(%arg0) {torch.onnx.delimiter = "."} : (!torch.vtensor<[2],!torch.str>) -> (!torch.vtensor<[2,2],!torch.str>, !torch.vtensor<[2],si64>) + return %0#0, %0#1 : !torch.vtensor<[2,2],!torch.str>, !torch.vtensor<[2],si64> + } +} + diff --git a/iree_tests/onnx/node/generated/test_string_split_basic/output_0.npy b/iree_tests/onnx/node/generated/test_string_split_basic/output_0.npy new file mode 100644 index 000000000..eb451986d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_basic/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_basic/output_1.npy b/iree_tests/onnx/node/generated/test_string_split_basic/output_1.npy new file mode 100644 index 000000000..57819e1dd Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_basic/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_basic/test_data_flags.txt b/iree_tests/onnx/node/generated/test_string_split_basic/test_data_flags.txt new file mode 100644 index 000000000..2e7ed88d7 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_split_basic/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy diff --git a/iree_tests/onnx/node/generated/test_string_split_consecutive_delimiters/input_0.npy b/iree_tests/onnx/node/generated/test_string_split_consecutive_delimiters/input_0.npy new file mode 100644 index 000000000..2eba29c57 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_consecutive_delimiters/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_consecutive_delimiters/model.mlir b/iree_tests/onnx/node/generated/test_string_split_consecutive_delimiters/model.mlir new file mode 100644 index 000000000..d0ce9d883 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_split_consecutive_delimiters/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_string_split_consecutive_delimiters(%arg0: !torch.vtensor<[2],!torch.str>) -> (!torch.vtensor<[2,6],!torch.str>, !torch.vtensor<[2],si64>) attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.StringSplit"(%arg0) {torch.onnx.delimiter = "-"} : (!torch.vtensor<[2],!torch.str>) -> (!torch.vtensor<[2,6],!torch.str>, !torch.vtensor<[2],si64>) + return %0#0, %0#1 : !torch.vtensor<[2,6],!torch.str>, !torch.vtensor<[2],si64> + } +} + diff --git a/iree_tests/onnx/node/generated/test_string_split_consecutive_delimiters/output_0.npy b/iree_tests/onnx/node/generated/test_string_split_consecutive_delimiters/output_0.npy new file mode 100644 index 000000000..fc1f26552 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_consecutive_delimiters/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_consecutive_delimiters/output_1.npy b/iree_tests/onnx/node/generated/test_string_split_consecutive_delimiters/output_1.npy new file mode 100644 index 000000000..b9328b469 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_consecutive_delimiters/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_consecutive_delimiters/test_data_flags.txt b/iree_tests/onnx/node/generated/test_string_split_consecutive_delimiters/test_data_flags.txt new file mode 100644 index 000000000..2e7ed88d7 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_split_consecutive_delimiters/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy diff --git a/iree_tests/onnx/node/generated/test_string_split_empty_string_delimiter/input_0.npy b/iree_tests/onnx/node/generated/test_string_split_empty_string_delimiter/input_0.npy new file mode 100644 index 000000000..040c00595 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_empty_string_delimiter/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_empty_string_delimiter/model.mlir b/iree_tests/onnx/node/generated/test_string_split_empty_string_delimiter/model.mlir new file mode 100644 index 000000000..afa9022c8 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_split_empty_string_delimiter/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_string_split_empty_string_delimiter(%arg0: !torch.vtensor<[3],!torch.str>) -> (!torch.vtensor<[3,3],!torch.str>, !torch.vtensor<[3],si64>) attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.StringSplit"(%arg0) {torch.onnx.delimiter = ""} : (!torch.vtensor<[3],!torch.str>) -> (!torch.vtensor<[3,3],!torch.str>, !torch.vtensor<[3],si64>) + return %0#0, %0#1 : !torch.vtensor<[3,3],!torch.str>, !torch.vtensor<[3],si64> + } +} + diff --git a/iree_tests/onnx/node/generated/test_string_split_empty_string_delimiter/output_0.npy b/iree_tests/onnx/node/generated/test_string_split_empty_string_delimiter/output_0.npy new file mode 100644 index 000000000..db3829f84 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_empty_string_delimiter/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_empty_string_delimiter/output_1.npy b/iree_tests/onnx/node/generated/test_string_split_empty_string_delimiter/output_1.npy new file mode 100644 index 000000000..4da733dc5 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_empty_string_delimiter/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_empty_string_delimiter/test_data_flags.txt b/iree_tests/onnx/node/generated/test_string_split_empty_string_delimiter/test_data_flags.txt new file mode 100644 index 000000000..2e7ed88d7 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_split_empty_string_delimiter/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy diff --git a/iree_tests/onnx/node/generated/test_string_split_empty_tensor/input_0.npy b/iree_tests/onnx/node/generated/test_string_split_empty_tensor/input_0.npy new file mode 100644 index 000000000..df6c4ca05 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_empty_tensor/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_empty_tensor/model.mlir b/iree_tests/onnx/node/generated/test_string_split_empty_tensor/model.mlir new file mode 100644 index 000000000..fcebbebac --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_split_empty_tensor/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_string_split_empty_tensor(%arg0: !torch.vtensor<[0],!torch.str>) -> (!torch.vtensor<[0,?],!torch.str>, !torch.vtensor<[0],si64>) attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.StringSplit"(%arg0) : (!torch.vtensor<[0],!torch.str>) -> (!torch.vtensor<[0,?],!torch.str>, !torch.vtensor<[0],si64>) + return %0#0, %0#1 : !torch.vtensor<[0,?],!torch.str>, !torch.vtensor<[0],si64> + } +} + diff --git a/iree_tests/onnx/node/generated/test_string_split_empty_tensor/output_0.npy b/iree_tests/onnx/node/generated/test_string_split_empty_tensor/output_0.npy new file mode 100644 index 000000000..90f4176ec Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_empty_tensor/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_empty_tensor/output_1.npy b/iree_tests/onnx/node/generated/test_string_split_empty_tensor/output_1.npy new file mode 100644 index 000000000..d62c53132 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_empty_tensor/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_empty_tensor/test_data_flags.txt b/iree_tests/onnx/node/generated/test_string_split_empty_tensor/test_data_flags.txt new file mode 100644 index 000000000..2e7ed88d7 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_split_empty_tensor/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy diff --git a/iree_tests/onnx/node/generated/test_string_split_maxsplit/input_0.npy b/iree_tests/onnx/node/generated/test_string_split_maxsplit/input_0.npy new file mode 100644 index 000000000..9ab35fb5c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_maxsplit/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_maxsplit/model.mlir b/iree_tests/onnx/node/generated/test_string_split_maxsplit/model.mlir new file mode 100644 index 000000000..d0c4af699 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_split_maxsplit/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_string_split_maxsplit(%arg0: !torch.vtensor<[2,2],!torch.str>) -> (!torch.vtensor<[2,2,3],!torch.str>, !torch.vtensor<[2,2],si64>) attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.StringSplit"(%arg0) {torch.onnx.maxsplit = 2 : si64} : (!torch.vtensor<[2,2],!torch.str>) -> (!torch.vtensor<[2,2,3],!torch.str>, !torch.vtensor<[2,2],si64>) + return %0#0, %0#1 : !torch.vtensor<[2,2,3],!torch.str>, !torch.vtensor<[2,2],si64> + } +} + diff --git a/iree_tests/onnx/node/generated/test_string_split_maxsplit/output_0.npy b/iree_tests/onnx/node/generated/test_string_split_maxsplit/output_0.npy new file mode 100644 index 000000000..6395b8d77 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_maxsplit/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_maxsplit/output_1.npy b/iree_tests/onnx/node/generated/test_string_split_maxsplit/output_1.npy new file mode 100644 index 000000000..982120267 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_maxsplit/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_maxsplit/test_data_flags.txt b/iree_tests/onnx/node/generated/test_string_split_maxsplit/test_data_flags.txt new file mode 100644 index 000000000..2e7ed88d7 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_split_maxsplit/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy diff --git a/iree_tests/onnx/node/generated/test_string_split_no_delimiter/input_0.npy b/iree_tests/onnx/node/generated/test_string_split_no_delimiter/input_0.npy new file mode 100644 index 000000000..040c00595 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_no_delimiter/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_no_delimiter/model.mlir b/iree_tests/onnx/node/generated/test_string_split_no_delimiter/model.mlir new file mode 100644 index 000000000..ab37e7213 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_split_no_delimiter/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_string_split_no_delimiter(%arg0: !torch.vtensor<[3],!torch.str>) -> (!torch.vtensor<[3,3],!torch.str>, !torch.vtensor<[3],si64>) attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 20 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0:2 = torch.operator "onnx.StringSplit"(%arg0) : (!torch.vtensor<[3],!torch.str>) -> (!torch.vtensor<[3,3],!torch.str>, !torch.vtensor<[3],si64>) + return %0#0, %0#1 : !torch.vtensor<[3,3],!torch.str>, !torch.vtensor<[3],si64> + } +} + diff --git a/iree_tests/onnx/node/generated/test_string_split_no_delimiter/output_0.npy b/iree_tests/onnx/node/generated/test_string_split_no_delimiter/output_0.npy new file mode 100644 index 000000000..db3829f84 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_no_delimiter/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_no_delimiter/output_1.npy b/iree_tests/onnx/node/generated/test_string_split_no_delimiter/output_1.npy new file mode 100644 index 000000000..4da733dc5 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_string_split_no_delimiter/output_1.npy differ diff --git a/iree_tests/onnx/node/generated/test_string_split_no_delimiter/test_data_flags.txt b/iree_tests/onnx/node/generated/test_string_split_no_delimiter/test_data_flags.txt new file mode 100644 index 000000000..2e7ed88d7 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_string_split_no_delimiter/test_data_flags.txt @@ -0,0 +1,3 @@ +--input=@input_0.npy +--expected_output=@output_0.npy +--expected_output=@output_1.npy diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_lower/input_0.npy b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_lower/input_0.npy new file mode 100644 index 000000000..7397b8dd2 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_lower/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_lower/model.mlir b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_lower/model.mlir new file mode 100644 index 000000000..08e7811f6 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_lower/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_strnormalizer_export_monday_casesensintive_lower(%arg0: !torch.vtensor<[4],!torch.str>) -> !torch.vtensor<[3],!torch.str> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.StringNormalizer"(%arg0) {torch.onnx.case_change_action = "LOWER", torch.onnx.is_case_sensitive = 1 : si64, torch.onnx.stopwords = ["monday"]} : (!torch.vtensor<[4],!torch.str>) -> !torch.vtensor<[3],!torch.str> + return %0 : !torch.vtensor<[3],!torch.str> + } +} + diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_lower/output_0.npy b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_lower/output_0.npy new file mode 100644 index 000000000..2565f070c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_lower/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_lower/test_data_flags.txt b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_lower/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_lower/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_nochangecase/input_0.npy b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_nochangecase/input_0.npy new file mode 100644 index 000000000..7397b8dd2 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_nochangecase/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_nochangecase/model.mlir b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_nochangecase/model.mlir new file mode 100644 index 000000000..0e1054d7b --- /dev/null +++ b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_nochangecase/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_strnormalizer_export_monday_casesensintive_nochangecase(%arg0: !torch.vtensor<[4],!torch.str>) -> !torch.vtensor<[3],!torch.str> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.StringNormalizer"(%arg0) {torch.onnx.is_case_sensitive = 1 : si64, torch.onnx.stopwords = ["monday"]} : (!torch.vtensor<[4],!torch.str>) -> !torch.vtensor<[3],!torch.str> + return %0 : !torch.vtensor<[3],!torch.str> + } +} + diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_nochangecase/output_0.npy b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_nochangecase/output_0.npy new file mode 100644 index 000000000..2565f070c Binary files /dev/null and b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_nochangecase/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_nochangecase/test_data_flags.txt b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_nochangecase/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_nochangecase/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_upper/input_0.npy b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_upper/input_0.npy new file mode 100644 index 000000000..7397b8dd2 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_upper/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_upper/model.mlir b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_upper/model.mlir new file mode 100644 index 000000000..6b64fbe84 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_upper/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_strnormalizer_export_monday_casesensintive_upper(%arg0: !torch.vtensor<[4],!torch.str>) -> !torch.vtensor<[3],!torch.str> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.StringNormalizer"(%arg0) {torch.onnx.case_change_action = "UPPER", torch.onnx.is_case_sensitive = 1 : si64, torch.onnx.stopwords = ["monday"]} : (!torch.vtensor<[4],!torch.str>) -> !torch.vtensor<[3],!torch.str> + return %0 : !torch.vtensor<[3],!torch.str> + } +} + diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_upper/output_0.npy b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_upper/output_0.npy new file mode 100644 index 000000000..637622dce Binary files /dev/null and b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_upper/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_upper/test_data_flags.txt b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_upper/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_casesensintive_upper/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_empty_output/input_0.npy b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_empty_output/input_0.npy new file mode 100644 index 000000000..e39b3c33a Binary files /dev/null and b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_empty_output/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_empty_output/model.mlir b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_empty_output/model.mlir new file mode 100644 index 000000000..58537d583 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_empty_output/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_strnormalizer_export_monday_empty_output(%arg0: !torch.vtensor<[2],!torch.str>) -> !torch.vtensor<[1],!torch.str> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.StringNormalizer"(%arg0) {torch.onnx.case_change_action = "UPPER", torch.onnx.is_case_sensitive = 1 : si64, torch.onnx.stopwords = ["monday"]} : (!torch.vtensor<[2],!torch.str>) -> !torch.vtensor<[1],!torch.str> + return %0 : !torch.vtensor<[1],!torch.str> + } +} + diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_empty_output/output_0.npy b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_empty_output/output_0.npy new file mode 100644 index 000000000..0e50a9725 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_empty_output/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_empty_output/test_data_flags.txt b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_empty_output/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_empty_output/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_insensintive_upper_twodim/input_0.npy b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_insensintive_upper_twodim/input_0.npy new file mode 100644 index 000000000..e75cd3afe Binary files /dev/null and b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_insensintive_upper_twodim/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_insensintive_upper_twodim/model.mlir b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_insensintive_upper_twodim/model.mlir new file mode 100644 index 000000000..4bb09e3bf --- /dev/null +++ b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_insensintive_upper_twodim/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_strnormalizer_export_monday_insensintive_upper_twodim(%arg0: !torch.vtensor<[1,6],!torch.str>) -> !torch.vtensor<[1,4],!torch.str> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.StringNormalizer"(%arg0) {torch.onnx.case_change_action = "UPPER", torch.onnx.stopwords = ["monday"]} : (!torch.vtensor<[1,6],!torch.str>) -> !torch.vtensor<[1,4],!torch.str> + return %0 : !torch.vtensor<[1,4],!torch.str> + } +} + diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_insensintive_upper_twodim/output_0.npy b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_insensintive_upper_twodim/output_0.npy new file mode 100644 index 000000000..afbda5cf4 Binary files /dev/null and b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_insensintive_upper_twodim/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_insensintive_upper_twodim/test_data_flags.txt b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_insensintive_upper_twodim/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_strnormalizer_export_monday_insensintive_upper_twodim/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_nostopwords_nochangecase/input_0.npy b/iree_tests/onnx/node/generated/test_strnormalizer_nostopwords_nochangecase/input_0.npy new file mode 100644 index 000000000..33631b58d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_strnormalizer_nostopwords_nochangecase/input_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_nostopwords_nochangecase/model.mlir b/iree_tests/onnx/node/generated/test_strnormalizer_nostopwords_nochangecase/model.mlir new file mode 100644 index 000000000..f1cf9b262 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_strnormalizer_nostopwords_nochangecase/model.mlir @@ -0,0 +1,8 @@ +module { + func.func @test_strnormalizer_nostopwords_nochangecase(%arg0: !torch.vtensor<[2],!torch.str>) -> !torch.vtensor<[2],!torch.str> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { + %none = torch.constant.none + %0 = torch.operator "onnx.StringNormalizer"(%arg0) {torch.onnx.is_case_sensitive = 1 : si64} : (!torch.vtensor<[2],!torch.str>) -> !torch.vtensor<[2],!torch.str> + return %0 : !torch.vtensor<[2],!torch.str> + } +} + diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_nostopwords_nochangecase/output_0.npy b/iree_tests/onnx/node/generated/test_strnormalizer_nostopwords_nochangecase/output_0.npy new file mode 100644 index 000000000..33631b58d Binary files /dev/null and b/iree_tests/onnx/node/generated/test_strnormalizer_nostopwords_nochangecase/output_0.npy differ diff --git a/iree_tests/onnx/node/generated/test_strnormalizer_nostopwords_nochangecase/test_data_flags.txt b/iree_tests/onnx/node/generated/test_strnormalizer_nostopwords_nochangecase/test_data_flags.txt new file mode 100644 index 000000000..35f000405 --- /dev/null +++ b/iree_tests/onnx/node/generated/test_strnormalizer_nostopwords_nochangecase/test_data_flags.txt @@ -0,0 +1,2 @@ +--input=@input_0.npy +--expected_output=@output_0.npy diff --git a/iree_tests/onnx/node/generated/test_sub/model.mlir b/iree_tests/onnx/node/generated/test_sub/model.mlir index 4a3791c00..ca70e9d76 100644 --- a/iree_tests/onnx/node/generated/test_sub/model.mlir +++ b/iree_tests/onnx/node/generated/test_sub/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sub(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Sub"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Sub"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sub_bcast/model.mlir b/iree_tests/onnx/node/generated/test_sub_bcast/model.mlir index b142e13f7..716c7de9b 100644 --- a/iree_tests/onnx/node/generated/test_sub_bcast/model.mlir +++ b/iree_tests/onnx/node/generated/test_sub_bcast/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sub_bcast(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Sub"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Sub"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sub_example/model.mlir b/iree_tests/onnx/node/generated/test_sub_example/model.mlir index 4e4b8a559..5cee5de62 100644 --- a/iree_tests/onnx/node/generated/test_sub_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_sub_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sub_example(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Sub"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Sub"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sub_uint8/model.mlir b/iree_tests/onnx/node/generated/test_sub_uint8/model.mlir index 18fc8e7f4..91fe48e0a 100644 --- a/iree_tests/onnx/node/generated/test_sub_uint8/model.mlir +++ b/iree_tests/onnx/node/generated/test_sub_uint8/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sub_uint8(%arg0: !torch.vtensor<[3,4,5],ui8>, %arg1: !torch.vtensor<[3,4,5],ui8>) -> !torch.vtensor<[3,4,5],ui8> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Sub"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],ui8>, !torch.vtensor<[3,4,5],ui8>) -> !torch.vtensor<[3,4,5],ui8> + %none = torch.constant.none + %0 = torch.operator "onnx.Sub"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],ui8>, !torch.vtensor<[3,4,5],ui8>) -> !torch.vtensor<[3,4,5],ui8> return %0 : !torch.vtensor<[3,4,5],ui8> } } diff --git a/iree_tests/onnx/node/generated/test_sum_example/model.mlir b/iree_tests/onnx/node/generated/test_sum_example/model.mlir index e5fec21d8..372696160 100644 --- a/iree_tests/onnx/node/generated/test_sum_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_sum_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sum_example(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],f32>, %arg2: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Sum"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Sum"(%arg0, %arg1, %arg2) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sum_one_input/model.mlir b/iree_tests/onnx/node/generated/test_sum_one_input/model.mlir index 7bef4ee0d..59ba0e315 100644 --- a/iree_tests/onnx/node/generated/test_sum_one_input/model.mlir +++ b/iree_tests/onnx/node/generated/test_sum_one_input/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sum_one_input(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Sum"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Sum"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_sum_two_inputs/model.mlir b/iree_tests/onnx/node/generated/test_sum_two_inputs/model.mlir index 518ab69cc..c2d2c1335 100644 --- a/iree_tests/onnx/node/generated/test_sum_two_inputs/model.mlir +++ b/iree_tests/onnx/node/generated/test_sum_two_inputs/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_sum_two_inputs(%arg0: !torch.vtensor<[3],f32>, %arg1: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Sum"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Sum"(%arg0, %arg1) : (!torch.vtensor<[3],f32>, !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_tan/model.mlir b/iree_tests/onnx/node/generated/test_tan/model.mlir index ff28846ce..253e50ba3 100644 --- a/iree_tests/onnx/node/generated/test_tan/model.mlir +++ b/iree_tests/onnx/node/generated/test_tan/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tan(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Tan"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Tan"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_tan_example/model.mlir b/iree_tests/onnx/node/generated/test_tan_example/model.mlir index ec68ec2fa..330f19886 100644 --- a/iree_tests/onnx/node/generated/test_tan_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_tan_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tan_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Tan"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Tan"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_tanh/model.mlir b/iree_tests/onnx/node/generated/test_tanh/model.mlir index cfe9e9534..2bd6b1309 100644 --- a/iree_tests/onnx/node/generated/test_tanh/model.mlir +++ b/iree_tests/onnx/node/generated/test_tanh/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tanh(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Tanh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Tanh"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_tanh_example/model.mlir b/iree_tests/onnx/node/generated/test_tanh_example/model.mlir index 30d800a09..8e61d5e2b 100644 --- a/iree_tests/onnx/node/generated/test_tanh_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_tanh_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tanh_example(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Tanh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Tanh"(%arg0) : (!torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_batch_onlybigrams_skip0/model.mlir b/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_batch_onlybigrams_skip0/model.mlir index 180c678a8..09c7f2560 100644 --- a/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_batch_onlybigrams_skip0/model.mlir +++ b/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_batch_onlybigrams_skip0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tfidfvectorizer_tf_batch_onlybigrams_skip0(%arg0: !torch.vtensor<[2,6],si32>) -> !torch.vtensor<[2,7],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.TfIdfVectorizer"(%arg0) {torch.onnx.max_gram_length = 2 : si64, torch.onnx.max_skip_count = 0 : si64, torch.onnx.min_gram_length = 2 : si64, torch.onnx.mode = "TF", torch.onnx.ngram_counts = [0 : si64, 4 : si64], torch.onnx.ngram_indexes = [0 : si64, 1 : si64, 2 : si64, 3 : si64, 4 : si64, 5 : si64, 6 : si64], torch.onnx.pool_int64s = [2 : si64, 3 : si64, 5 : si64, 4 : si64, 5 : si64, 6 : si64, 7 : si64, 8 : si64, 6 : si64, 7 : si64]} : (!torch.vtensor<[2,6],si32>) -> !torch.vtensor<[2,7],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.TfIdfVectorizer"(%arg0) {torch.onnx.max_gram_length = 2 : si64, torch.onnx.max_skip_count = 0 : si64, torch.onnx.min_gram_length = 2 : si64, torch.onnx.mode = "TF", torch.onnx.ngram_counts = [0 : si64, 4 : si64], torch.onnx.ngram_indexes = [0 : si64, 1 : si64, 2 : si64, 3 : si64, 4 : si64, 5 : si64, 6 : si64], torch.onnx.pool_int64s = [2 : si64, 3 : si64, 5 : si64, 4 : si64, 5 : si64, 6 : si64, 7 : si64, 8 : si64, 6 : si64, 7 : si64]} : (!torch.vtensor<[2,6],si32>) -> !torch.vtensor<[2,7],f32> return %0 : !torch.vtensor<[2,7],f32> } } diff --git a/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_batch_onlybigrams_skip5/model.mlir b/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_batch_onlybigrams_skip5/model.mlir index b29f1e3d1..1c003c77b 100644 --- a/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_batch_onlybigrams_skip5/model.mlir +++ b/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_batch_onlybigrams_skip5/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tfidfvectorizer_tf_batch_onlybigrams_skip5(%arg0: !torch.vtensor<[2,6],si32>) -> !torch.vtensor<[2,7],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.TfIdfVectorizer"(%arg0) {torch.onnx.max_gram_length = 2 : si64, torch.onnx.max_skip_count = 5 : si64, torch.onnx.min_gram_length = 2 : si64, torch.onnx.mode = "TF", torch.onnx.ngram_counts = [0 : si64, 4 : si64], torch.onnx.ngram_indexes = [0 : si64, 1 : si64, 2 : si64, 3 : si64, 4 : si64, 5 : si64, 6 : si64], torch.onnx.pool_int64s = [2 : si64, 3 : si64, 5 : si64, 4 : si64, 5 : si64, 6 : si64, 7 : si64, 8 : si64, 6 : si64, 7 : si64]} : (!torch.vtensor<[2,6],si32>) -> !torch.vtensor<[2,7],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.TfIdfVectorizer"(%arg0) {torch.onnx.max_gram_length = 2 : si64, torch.onnx.max_skip_count = 5 : si64, torch.onnx.min_gram_length = 2 : si64, torch.onnx.mode = "TF", torch.onnx.ngram_counts = [0 : si64, 4 : si64], torch.onnx.ngram_indexes = [0 : si64, 1 : si64, 2 : si64, 3 : si64, 4 : si64, 5 : si64, 6 : si64], torch.onnx.pool_int64s = [2 : si64, 3 : si64, 5 : si64, 4 : si64, 5 : si64, 6 : si64, 7 : si64, 8 : si64, 6 : si64, 7 : si64]} : (!torch.vtensor<[2,6],si32>) -> !torch.vtensor<[2,7],f32> return %0 : !torch.vtensor<[2,7],f32> } } diff --git a/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_batch_uniandbigrams_skip5/model.mlir b/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_batch_uniandbigrams_skip5/model.mlir index a2f028f84..60044e8d7 100644 --- a/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_batch_uniandbigrams_skip5/model.mlir +++ b/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_batch_uniandbigrams_skip5/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tfidfvectorizer_tf_batch_uniandbigrams_skip5(%arg0: !torch.vtensor<[2,6],si32>) -> !torch.vtensor<[2,7],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.TfIdfVectorizer"(%arg0) {torch.onnx.max_gram_length = 2 : si64, torch.onnx.max_skip_count = 5 : si64, torch.onnx.min_gram_length = 1 : si64, torch.onnx.mode = "TF", torch.onnx.ngram_counts = [0 : si64, 4 : si64], torch.onnx.ngram_indexes = [0 : si64, 1 : si64, 2 : si64, 3 : si64, 4 : si64, 5 : si64, 6 : si64], torch.onnx.pool_int64s = [2 : si64, 3 : si64, 5 : si64, 4 : si64, 5 : si64, 6 : si64, 7 : si64, 8 : si64, 6 : si64, 7 : si64]} : (!torch.vtensor<[2,6],si32>) -> !torch.vtensor<[2,7],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.TfIdfVectorizer"(%arg0) {torch.onnx.max_gram_length = 2 : si64, torch.onnx.max_skip_count = 5 : si64, torch.onnx.min_gram_length = 1 : si64, torch.onnx.mode = "TF", torch.onnx.ngram_counts = [0 : si64, 4 : si64], torch.onnx.ngram_indexes = [0 : si64, 1 : si64, 2 : si64, 3 : si64, 4 : si64, 5 : si64, 6 : si64], torch.onnx.pool_int64s = [2 : si64, 3 : si64, 5 : si64, 4 : si64, 5 : si64, 6 : si64, 7 : si64, 8 : si64, 6 : si64, 7 : si64]} : (!torch.vtensor<[2,6],si32>) -> !torch.vtensor<[2,7],f32> return %0 : !torch.vtensor<[2,7],f32> } } diff --git a/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_only_bigrams_skip0/model.mlir b/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_only_bigrams_skip0/model.mlir index 5e0cbcaa2..1a1a08510 100644 --- a/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_only_bigrams_skip0/model.mlir +++ b/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_only_bigrams_skip0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tfidfvectorizer_tf_only_bigrams_skip0(%arg0: !torch.vtensor<[12],si32>) -> !torch.vtensor<[7],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.TfIdfVectorizer"(%arg0) {torch.onnx.max_gram_length = 2 : si64, torch.onnx.max_skip_count = 0 : si64, torch.onnx.min_gram_length = 2 : si64, torch.onnx.mode = "TF", torch.onnx.ngram_counts = [0 : si64, 4 : si64], torch.onnx.ngram_indexes = [0 : si64, 1 : si64, 2 : si64, 3 : si64, 4 : si64, 5 : si64, 6 : si64], torch.onnx.pool_int64s = [2 : si64, 3 : si64, 5 : si64, 4 : si64, 5 : si64, 6 : si64, 7 : si64, 8 : si64, 6 : si64, 7 : si64]} : (!torch.vtensor<[12],si32>) -> !torch.vtensor<[7],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.TfIdfVectorizer"(%arg0) {torch.onnx.max_gram_length = 2 : si64, torch.onnx.max_skip_count = 0 : si64, torch.onnx.min_gram_length = 2 : si64, torch.onnx.mode = "TF", torch.onnx.ngram_counts = [0 : si64, 4 : si64], torch.onnx.ngram_indexes = [0 : si64, 1 : si64, 2 : si64, 3 : si64, 4 : si64, 5 : si64, 6 : si64], torch.onnx.pool_int64s = [2 : si64, 3 : si64, 5 : si64, 4 : si64, 5 : si64, 6 : si64, 7 : si64, 8 : si64, 6 : si64, 7 : si64]} : (!torch.vtensor<[12],si32>) -> !torch.vtensor<[7],f32> return %0 : !torch.vtensor<[7],f32> } } diff --git a/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_onlybigrams_levelempty/model.mlir b/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_onlybigrams_levelempty/model.mlir index 64d4ead03..a10c57c32 100644 --- a/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_onlybigrams_levelempty/model.mlir +++ b/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_onlybigrams_levelempty/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tfidfvectorizer_tf_onlybigrams_levelempty(%arg0: !torch.vtensor<[12],si32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.TfIdfVectorizer"(%arg0) {torch.onnx.max_gram_length = 2 : si64, torch.onnx.max_skip_count = 0 : si64, torch.onnx.min_gram_length = 2 : si64, torch.onnx.mode = "TF", torch.onnx.ngram_counts = [0 : si64, 0 : si64], torch.onnx.ngram_indexes = [0 : si64, 1 : si64, 2 : si64], torch.onnx.pool_int64s = [5 : si64, 6 : si64, 7 : si64, 8 : si64, 6 : si64, 7 : si64]} : (!torch.vtensor<[12],si32>) -> !torch.vtensor<[3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.TfIdfVectorizer"(%arg0) {torch.onnx.max_gram_length = 2 : si64, torch.onnx.max_skip_count = 0 : si64, torch.onnx.min_gram_length = 2 : si64, torch.onnx.mode = "TF", torch.onnx.ngram_counts = [0 : si64, 0 : si64], torch.onnx.ngram_indexes = [0 : si64, 1 : si64, 2 : si64], torch.onnx.pool_int64s = [5 : si64, 6 : si64, 7 : si64, 8 : si64, 6 : si64, 7 : si64]} : (!torch.vtensor<[12],si32>) -> !torch.vtensor<[3],f32> return %0 : !torch.vtensor<[3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_onlybigrams_skip5/model.mlir b/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_onlybigrams_skip5/model.mlir index 60c0bff04..1b2ccc760 100644 --- a/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_onlybigrams_skip5/model.mlir +++ b/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_onlybigrams_skip5/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tfidfvectorizer_tf_onlybigrams_skip5(%arg0: !torch.vtensor<[12],si32>) -> !torch.vtensor<[7],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.TfIdfVectorizer"(%arg0) {torch.onnx.max_gram_length = 2 : si64, torch.onnx.max_skip_count = 5 : si64, torch.onnx.min_gram_length = 2 : si64, torch.onnx.mode = "TF", torch.onnx.ngram_counts = [0 : si64, 4 : si64], torch.onnx.ngram_indexes = [0 : si64, 1 : si64, 2 : si64, 3 : si64, 4 : si64, 5 : si64, 6 : si64], torch.onnx.pool_int64s = [2 : si64, 3 : si64, 5 : si64, 4 : si64, 5 : si64, 6 : si64, 7 : si64, 8 : si64, 6 : si64, 7 : si64]} : (!torch.vtensor<[12],si32>) -> !torch.vtensor<[7],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.TfIdfVectorizer"(%arg0) {torch.onnx.max_gram_length = 2 : si64, torch.onnx.max_skip_count = 5 : si64, torch.onnx.min_gram_length = 2 : si64, torch.onnx.mode = "TF", torch.onnx.ngram_counts = [0 : si64, 4 : si64], torch.onnx.ngram_indexes = [0 : si64, 1 : si64, 2 : si64, 3 : si64, 4 : si64, 5 : si64, 6 : si64], torch.onnx.pool_int64s = [2 : si64, 3 : si64, 5 : si64, 4 : si64, 5 : si64, 6 : si64, 7 : si64, 8 : si64, 6 : si64, 7 : si64]} : (!torch.vtensor<[12],si32>) -> !torch.vtensor<[7],f32> return %0 : !torch.vtensor<[7],f32> } } diff --git a/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_uniandbigrams_skip5/model.mlir b/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_uniandbigrams_skip5/model.mlir index 8f075f81e..ec1b4aa7f 100644 --- a/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_uniandbigrams_skip5/model.mlir +++ b/iree_tests/onnx/node/generated/test_tfidfvectorizer_tf_uniandbigrams_skip5/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tfidfvectorizer_tf_uniandbigrams_skip5(%arg0: !torch.vtensor<[12],si32>) -> !torch.vtensor<[7],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.TfIdfVectorizer"(%arg0) {torch.onnx.max_gram_length = 2 : si64, torch.onnx.max_skip_count = 5 : si64, torch.onnx.min_gram_length = 1 : si64, torch.onnx.mode = "TF", torch.onnx.ngram_counts = [0 : si64, 4 : si64], torch.onnx.ngram_indexes = [0 : si64, 1 : si64, 2 : si64, 3 : si64, 4 : si64, 5 : si64, 6 : si64], torch.onnx.pool_int64s = [2 : si64, 3 : si64, 5 : si64, 4 : si64, 5 : si64, 6 : si64, 7 : si64, 8 : si64, 6 : si64, 7 : si64]} : (!torch.vtensor<[12],si32>) -> !torch.vtensor<[7],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.TfIdfVectorizer"(%arg0) {torch.onnx.max_gram_length = 2 : si64, torch.onnx.max_skip_count = 5 : si64, torch.onnx.min_gram_length = 1 : si64, torch.onnx.mode = "TF", torch.onnx.ngram_counts = [0 : si64, 4 : si64], torch.onnx.ngram_indexes = [0 : si64, 1 : si64, 2 : si64, 3 : si64, 4 : si64, 5 : si64, 6 : si64], torch.onnx.pool_int64s = [2 : si64, 3 : si64, 5 : si64, 4 : si64, 5 : si64, 6 : si64, 7 : si64, 8 : si64, 6 : si64, 7 : si64]} : (!torch.vtensor<[12],si32>) -> !torch.vtensor<[7],f32> return %0 : !torch.vtensor<[7],f32> } } diff --git a/iree_tests/onnx/node/generated/test_thresholdedrelu/model.mlir b/iree_tests/onnx/node/generated/test_thresholdedrelu/model.mlir index 3a90f8a10..5dcd96c9b 100644 --- a/iree_tests/onnx/node/generated/test_thresholdedrelu/model.mlir +++ b/iree_tests/onnx/node/generated/test_thresholdedrelu/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_thresholdedrelu(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ThresholdedRelu"(%arg0) {torch.onnx.alpha = 2.000000e+00 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ThresholdedRelu"(%arg0) {torch.onnx.alpha = 2.000000e+00 : f32} : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_thresholdedrelu_default/model.mlir b/iree_tests/onnx/node/generated/test_thresholdedrelu_default/model.mlir index 9082fa833..ded47ca9a 100644 --- a/iree_tests/onnx/node/generated/test_thresholdedrelu_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_thresholdedrelu_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_thresholdedrelu_default(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ThresholdedRelu"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ThresholdedRelu"(%arg0) : (!torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_thresholdedrelu_default_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_thresholdedrelu_default_expanded_ver18/model.mlir index 6f3e3081c..2bfcb3567 100644 --- a/iree_tests/onnx/node/generated/test_thresholdedrelu_default_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_thresholdedrelu_default_expanded_ver18/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_thresholdedrelu_default_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.000000e+00 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.Less"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> - %5 = torch.operator "onnx.Where"(%4, %arg0, %3) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 1.000000e+00 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Less"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> + %5 = torch.operator "onnx.Where"(%4, %arg0, %3) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> return %5 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_thresholdedrelu_example/model.mlir b/iree_tests/onnx/node/generated/test_thresholdedrelu_example/model.mlir index 495bdbbaf..64feea28f 100644 --- a/iree_tests/onnx/node/generated/test_thresholdedrelu_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_thresholdedrelu_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_thresholdedrelu_example(%arg0: !torch.vtensor<[5],f32>) -> !torch.vtensor<[5],f32> attributes {torch.onnx_meta.ir_version = 5 : si64, torch.onnx_meta.opset_version = 10 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.ThresholdedRelu"(%arg0) {torch.onnx.alpha = 2.000000e+00 : f32} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.ThresholdedRelu"(%arg0) {torch.onnx.alpha = 2.000000e+00 : f32} : (!torch.vtensor<[5],f32>) -> !torch.vtensor<[5],f32> return %0 : !torch.vtensor<[5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_thresholdedrelu_example_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_thresholdedrelu_example_expanded_ver18/model.mlir index 2a08d4093..e50d19758 100644 --- a/iree_tests/onnx/node/generated/test_thresholdedrelu_example_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_thresholdedrelu_example_expanded_ver18/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_thresholdedrelu_example_expanded_ver18(%arg0: !torch.vtensor<[5],f32>) -> !torch.vtensor<[5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 2.000000e+00 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.Less"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[5],i1> - %5 = torch.operator "onnx.Where"(%4, %arg0, %3) : (!torch.vtensor<[5],i1>, !torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 2.000000e+00 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Less"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[5],f32>) -> !torch.vtensor<[5],i1> + %5 = torch.operator "onnx.Where"(%4, %arg0, %3) : (!torch.vtensor<[5],i1>, !torch.vtensor<[5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[5],f32> return %5 : !torch.vtensor<[5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_thresholdedrelu_expanded_ver18/model.mlir b/iree_tests/onnx/node/generated/test_thresholdedrelu_expanded_ver18/model.mlir index bd76b3dd1..57f681304 100644 --- a/iree_tests/onnx/node/generated/test_thresholdedrelu_expanded_ver18/model.mlir +++ b/iree_tests/onnx/node/generated/test_thresholdedrelu_expanded_ver18/model.mlir @@ -1,11 +1,12 @@ module { func.func @test_thresholdedrelu_expanded_ver18(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 2.000000e+00 : f32} : () -> !torch.vtensor<[],f32> - %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %2 = torch.vtensor.literal(dense<0.000000e+00> : tensor) : !torch.vtensor<[],f32> - %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> - %4 = torch.operator "onnx.Less"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> - %5 = torch.operator "onnx.Where"(%4, %arg0, %3) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Constant"() {torch.onnx.value_float = 2.000000e+00 : f32} : () -> !torch.vtensor<[],f32> + %1 = torch.operator "onnx.CastLike"(%0, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %2 = torch.operator "onnx.Constant"() {torch.onnx.value = dense<0.000000e+00> : tensor} : () -> !torch.vtensor<[],f32> + %3 = torch.operator "onnx.CastLike"(%2, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[],f32> + %4 = torch.operator "onnx.Less"(%1, %arg0) : (!torch.vtensor<[],f32>, !torch.vtensor<[3,4,5],f32>) -> !torch.vtensor<[3,4,5],i1> + %5 = torch.operator "onnx.Where"(%4, %arg0, %3) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>) -> !torch.vtensor<[3,4,5],f32> return %5 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_tile/model.mlir b/iree_tests/onnx/node/generated/test_tile/model.mlir index 87a019d7c..9c12a322c 100644 --- a/iree_tests/onnx/node/generated/test_tile/model.mlir +++ b/iree_tests/onnx/node/generated/test_tile/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tile(%arg0: !torch.vtensor<[2,3,4,5],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[14,18,16,10],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Tile"(%arg0, %arg1) : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[14,18,16,10],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Tile"(%arg0, %arg1) : (!torch.vtensor<[2,3,4,5],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[14,18,16,10],f32> return %0 : !torch.vtensor<[14,18,16,10],f32> } } diff --git a/iree_tests/onnx/node/generated/test_tile_precomputed/model.mlir b/iree_tests/onnx/node/generated/test_tile_precomputed/model.mlir index 73ede10c7..b3914cf54 100644 --- a/iree_tests/onnx/node/generated/test_tile_precomputed/model.mlir +++ b/iree_tests/onnx/node/generated/test_tile_precomputed/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tile_precomputed(%arg0: !torch.vtensor<[2,2],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[4,4],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Tile"(%arg0, %arg1) : (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[4,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Tile"(%arg0, %arg1) : (!torch.vtensor<[2,2],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[4,4],f32> return %0 : !torch.vtensor<[4,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_top_k/model.mlir b/iree_tests/onnx/node/generated/test_top_k/model.mlir index c0b011d1a..fe7cbb3b7 100644 --- a/iree_tests/onnx/node/generated/test_top_k/model.mlir +++ b/iree_tests/onnx/node/generated/test_top_k/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_top_k(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> (!torch.vtensor<[3,3],f32>, !torch.vtensor<[3,3],si64>) attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.TopK"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],si64>) -> (!torch.vtensor<[3,3],f32>, !torch.vtensor<[3,3],si64>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.TopK"(%arg0, %arg1) {torch.onnx.axis = 1 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],si64>) -> (!torch.vtensor<[3,3],f32>, !torch.vtensor<[3,3],si64>) return %0#0, %0#1 : !torch.vtensor<[3,3],f32>, !torch.vtensor<[3,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_top_k_negative_axis/model.mlir b/iree_tests/onnx/node/generated/test_top_k_negative_axis/model.mlir index d5371f11d..1da4255e5 100644 --- a/iree_tests/onnx/node/generated/test_top_k_negative_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_top_k_negative_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_top_k_negative_axis(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> (!torch.vtensor<[3,3],f32>, !torch.vtensor<[3,3],si64>) attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.TopK"(%arg0, %arg1) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],si64>) -> (!torch.vtensor<[3,3],f32>, !torch.vtensor<[3,3],si64>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.TopK"(%arg0, %arg1) {torch.onnx.axis = -1 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],si64>) -> (!torch.vtensor<[3,3],f32>, !torch.vtensor<[3,3],si64>) return %0#0, %0#1 : !torch.vtensor<[3,3],f32>, !torch.vtensor<[3,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_top_k_smallest/model.mlir b/iree_tests/onnx/node/generated/test_top_k_smallest/model.mlir index 3c8718232..76dba87f8 100644 --- a/iree_tests/onnx/node/generated/test_top_k_smallest/model.mlir +++ b/iree_tests/onnx/node/generated/test_top_k_smallest/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_top_k_smallest(%arg0: !torch.vtensor<[3,4],f32>, %arg1: !torch.vtensor<[1],si64>) -> (!torch.vtensor<[3,3],f32>, !torch.vtensor<[3,3],si64>) attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.TopK"(%arg0, %arg1) {torch.onnx.axis = 1 : si64, torch.onnx.largest = 0 : si64, torch.onnx.sorted = 1 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],si64>) -> (!torch.vtensor<[3,3],f32>, !torch.vtensor<[3,3],si64>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.TopK"(%arg0, %arg1) {torch.onnx.axis = 1 : si64, torch.onnx.largest = 0 : si64, torch.onnx.sorted = 1 : si64} : (!torch.vtensor<[3,4],f32>, !torch.vtensor<[1],si64>) -> (!torch.vtensor<[3,3],f32>, !torch.vtensor<[3,3],si64>) return %0#0, %0#1 : !torch.vtensor<[3,3],f32>, !torch.vtensor<[3,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_training_dropout/model.mlir b/iree_tests/onnx/node/generated/test_training_dropout/model.mlir index 5f1c994c5..3527c89a2 100644 --- a/iree_tests/onnx/node/generated/test_training_dropout/model.mlir +++ b/iree_tests/onnx/node/generated/test_training_dropout/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_training_dropout(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],i1>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Dropout"(%arg0, %arg1, %arg2) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],i1>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Dropout"(%arg0, %arg1, %arg2) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],i1>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_training_dropout_default/model.mlir b/iree_tests/onnx/node/generated/test_training_dropout_default/model.mlir index 766808309..e7db221a1 100644 --- a/iree_tests/onnx/node/generated/test_training_dropout_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_training_dropout_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_training_dropout_default(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],i1>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Dropout"(%arg0, %arg1, %arg2) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],i1>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Dropout"(%arg0, %arg1, %arg2) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],i1>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_training_dropout_default_mask/model.mlir b/iree_tests/onnx/node/generated/test_training_dropout_default_mask/model.mlir index edebb6f51..322117700 100644 --- a/iree_tests/onnx/node/generated/test_training_dropout_default_mask/model.mlir +++ b/iree_tests/onnx/node/generated/test_training_dropout_default_mask/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_training_dropout_default_mask(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],i1>) -> (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.Dropout"(%arg0, %arg1, %arg2) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],i1>) -> (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.Dropout"(%arg0, %arg1, %arg2) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],i1>) -> (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1>) return %0#0, %0#1 : !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_training_dropout_mask/model.mlir b/iree_tests/onnx/node/generated/test_training_dropout_mask/model.mlir index c5a1e668e..54c27ad9c 100644 --- a/iree_tests/onnx/node/generated/test_training_dropout_mask/model.mlir +++ b/iree_tests/onnx/node/generated/test_training_dropout_mask/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_training_dropout_mask(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],i1>) -> (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.Dropout"(%arg0, %arg1, %arg2) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],i1>) -> (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.Dropout"(%arg0, %arg1, %arg2) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],i1>) -> (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1>) return %0#0, %0#1 : !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_training_dropout_zero_ratio/model.mlir b/iree_tests/onnx/node/generated/test_training_dropout_zero_ratio/model.mlir index dce0cac57..c70b5461f 100644 --- a/iree_tests/onnx/node/generated/test_training_dropout_zero_ratio/model.mlir +++ b/iree_tests/onnx/node/generated/test_training_dropout_zero_ratio/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_training_dropout_zero_ratio(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],i1>) -> !torch.vtensor<[3,4,5],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Dropout"(%arg0, %arg1, %arg2) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],i1>) -> !torch.vtensor<[3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Dropout"(%arg0, %arg1, %arg2) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],i1>) -> !torch.vtensor<[3,4,5],f32> return %0 : !torch.vtensor<[3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_training_dropout_zero_ratio_mask/model.mlir b/iree_tests/onnx/node/generated/test_training_dropout_zero_ratio_mask/model.mlir index ed50043dc..0d2cbe0bf 100644 --- a/iree_tests/onnx/node/generated/test_training_dropout_zero_ratio_mask/model.mlir +++ b/iree_tests/onnx/node/generated/test_training_dropout_zero_ratio_mask/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_training_dropout_zero_ratio_mask(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[],f32>, %arg2: !torch.vtensor<[],i1>) -> (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1>) attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:2 = torch.operator "onnx.Dropout"(%arg0, %arg1, %arg2) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],i1>) -> (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1>) + %none = torch.constant.none + %0:2 = torch.operator "onnx.Dropout"(%arg0, %arg1, %arg2) {torch.onnx.seed = 0 : si64} : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[],f32>, !torch.vtensor<[],i1>) -> (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1>) return %0#0, %0#1 : !torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_transpose_all_permutations_0/model.mlir b/iree_tests/onnx/node/generated/test_transpose_all_permutations_0/model.mlir index 8db29f863..3c40036bb 100644 --- a/iree_tests/onnx/node/generated/test_transpose_all_permutations_0/model.mlir +++ b/iree_tests/onnx/node/generated/test_transpose_all_permutations_0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_transpose_all_permutations_0(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Transpose"(%arg0) {torch.onnx.perm = [0 : si64, 1 : si64, 2 : si64]} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Transpose"(%arg0) {torch.onnx.perm = [0 : si64, 1 : si64, 2 : si64]} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,3,4],f32> return %0 : !torch.vtensor<[2,3,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_transpose_all_permutations_1/model.mlir b/iree_tests/onnx/node/generated/test_transpose_all_permutations_1/model.mlir index 467c5d7f6..f80baf9e3 100644 --- a/iree_tests/onnx/node/generated/test_transpose_all_permutations_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_transpose_all_permutations_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_transpose_all_permutations_1(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,4,3],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Transpose"(%arg0) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,4,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Transpose"(%arg0) {torch.onnx.perm = [0 : si64, 2 : si64, 1 : si64]} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[2,4,3],f32> return %0 : !torch.vtensor<[2,4,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_transpose_all_permutations_2/model.mlir b/iree_tests/onnx/node/generated/test_transpose_all_permutations_2/model.mlir index 1614386ba..c7d899dc5 100644 --- a/iree_tests/onnx/node/generated/test_transpose_all_permutations_2/model.mlir +++ b/iree_tests/onnx/node/generated/test_transpose_all_permutations_2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_transpose_all_permutations_2(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[3,2,4],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Transpose"(%arg0) {torch.onnx.perm = [1 : si64, 0 : si64, 2 : si64]} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[3,2,4],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Transpose"(%arg0) {torch.onnx.perm = [1 : si64, 0 : si64, 2 : si64]} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[3,2,4],f32> return %0 : !torch.vtensor<[3,2,4],f32> } } diff --git a/iree_tests/onnx/node/generated/test_transpose_all_permutations_3/model.mlir b/iree_tests/onnx/node/generated/test_transpose_all_permutations_3/model.mlir index 212b54a52..aaa9a54ba 100644 --- a/iree_tests/onnx/node/generated/test_transpose_all_permutations_3/model.mlir +++ b/iree_tests/onnx/node/generated/test_transpose_all_permutations_3/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_transpose_all_permutations_3(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[3,4,2],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Transpose"(%arg0) {torch.onnx.perm = [1 : si64, 2 : si64, 0 : si64]} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[3,4,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Transpose"(%arg0) {torch.onnx.perm = [1 : si64, 2 : si64, 0 : si64]} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[3,4,2],f32> return %0 : !torch.vtensor<[3,4,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_transpose_all_permutations_4/model.mlir b/iree_tests/onnx/node/generated/test_transpose_all_permutations_4/model.mlir index 7183592ce..24c0300fd 100644 --- a/iree_tests/onnx/node/generated/test_transpose_all_permutations_4/model.mlir +++ b/iree_tests/onnx/node/generated/test_transpose_all_permutations_4/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_transpose_all_permutations_4(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[4,2,3],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Transpose"(%arg0) {torch.onnx.perm = [2 : si64, 0 : si64, 1 : si64]} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[4,2,3],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Transpose"(%arg0) {torch.onnx.perm = [2 : si64, 0 : si64, 1 : si64]} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[4,2,3],f32> return %0 : !torch.vtensor<[4,2,3],f32> } } diff --git a/iree_tests/onnx/node/generated/test_transpose_all_permutations_5/model.mlir b/iree_tests/onnx/node/generated/test_transpose_all_permutations_5/model.mlir index 2d1a22512..b498bc845 100644 --- a/iree_tests/onnx/node/generated/test_transpose_all_permutations_5/model.mlir +++ b/iree_tests/onnx/node/generated/test_transpose_all_permutations_5/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_transpose_all_permutations_5(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[4,3,2],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Transpose"(%arg0) {torch.onnx.perm = [2 : si64, 1 : si64, 0 : si64]} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[4,3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Transpose"(%arg0) {torch.onnx.perm = [2 : si64, 1 : si64, 0 : si64]} : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[4,3,2],f32> return %0 : !torch.vtensor<[4,3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_transpose_default/model.mlir b/iree_tests/onnx/node/generated/test_transpose_default/model.mlir index 0e26417f7..ab19626ca 100644 --- a/iree_tests/onnx/node/generated/test_transpose_default/model.mlir +++ b/iree_tests/onnx/node/generated/test_transpose_default/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_transpose_default(%arg0: !torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[4,3,2],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Transpose"(%arg0) : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[4,3,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Transpose"(%arg0) : (!torch.vtensor<[2,3,4],f32>) -> !torch.vtensor<[4,3,2],f32> return %0 : !torch.vtensor<[4,3,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_tril/model.mlir b/iree_tests/onnx/node/generated/test_tril/model.mlir index 67a209bdc..7f0066622 100644 --- a/iree_tests/onnx/node/generated/test_tril/model.mlir +++ b/iree_tests/onnx/node/generated/test_tril/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tril(%arg0: !torch.vtensor<[4,5],si64>) -> !torch.vtensor<[4,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[4,5],si64>) -> !torch.vtensor<[4,5],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[4,5],si64>) -> !torch.vtensor<[4,5],si64> return %0 : !torch.vtensor<[4,5],si64> } } diff --git a/iree_tests/onnx/node/generated/test_tril_neg/model.mlir b/iree_tests/onnx/node/generated/test_tril_neg/model.mlir index dccda9f2a..8e2f5de5a 100644 --- a/iree_tests/onnx/node/generated/test_tril_neg/model.mlir +++ b/iree_tests/onnx/node/generated/test_tril_neg/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tril_neg(%arg0: !torch.vtensor<[4,5],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> return %0 : !torch.vtensor<[4,5],si64> } } diff --git a/iree_tests/onnx/node/generated/test_tril_one_row_neg/model.mlir b/iree_tests/onnx/node/generated/test_tril_one_row_neg/model.mlir index 2db752c52..647ee3981 100644 --- a/iree_tests/onnx/node/generated/test_tril_one_row_neg/model.mlir +++ b/iree_tests/onnx/node/generated/test_tril_one_row_neg/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tril_one_row_neg(%arg0: !torch.vtensor<[3,1,5],si64>) -> !torch.vtensor<[3,1,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[3,1,5],si64>) -> !torch.vtensor<[3,1,5],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[3,1,5],si64>) -> !torch.vtensor<[3,1,5],si64> return %0 : !torch.vtensor<[3,1,5],si64> } } diff --git a/iree_tests/onnx/node/generated/test_tril_out_neg/model.mlir b/iree_tests/onnx/node/generated/test_tril_out_neg/model.mlir index 5209c5d03..a646d9d03 100644 --- a/iree_tests/onnx/node/generated/test_tril_out_neg/model.mlir +++ b/iree_tests/onnx/node/generated/test_tril_out_neg/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tril_out_neg(%arg0: !torch.vtensor<[4,5],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> return %0 : !torch.vtensor<[4,5],si64> } } diff --git a/iree_tests/onnx/node/generated/test_tril_out_pos/model.mlir b/iree_tests/onnx/node/generated/test_tril_out_pos/model.mlir index 0268e93b9..0cf8d68f6 100644 --- a/iree_tests/onnx/node/generated/test_tril_out_pos/model.mlir +++ b/iree_tests/onnx/node/generated/test_tril_out_pos/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tril_out_pos(%arg0: !torch.vtensor<[4,5],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> return %0 : !torch.vtensor<[4,5],si64> } } diff --git a/iree_tests/onnx/node/generated/test_tril_pos/model.mlir b/iree_tests/onnx/node/generated/test_tril_pos/model.mlir index bb83ed14a..4ccbe1c8d 100644 --- a/iree_tests/onnx/node/generated/test_tril_pos/model.mlir +++ b/iree_tests/onnx/node/generated/test_tril_pos/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tril_pos(%arg0: !torch.vtensor<[4,5],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> return %0 : !torch.vtensor<[4,5],si64> } } diff --git a/iree_tests/onnx/node/generated/test_tril_square/model.mlir b/iree_tests/onnx/node/generated/test_tril_square/model.mlir index 13f23dfa0..73b014fa3 100644 --- a/iree_tests/onnx/node/generated/test_tril_square/model.mlir +++ b/iree_tests/onnx/node/generated/test_tril_square/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tril_square(%arg0: !torch.vtensor<[2,3,3],si64>) -> !torch.vtensor<[2,3,3],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[2,3,3],si64>) -> !torch.vtensor<[2,3,3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[2,3,3],si64>) -> !torch.vtensor<[2,3,3],si64> return %0 : !torch.vtensor<[2,3,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_tril_square_neg/model.mlir b/iree_tests/onnx/node/generated/test_tril_square_neg/model.mlir index db820ea82..6588aedec 100644 --- a/iree_tests/onnx/node/generated/test_tril_square_neg/model.mlir +++ b/iree_tests/onnx/node/generated/test_tril_square_neg/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tril_square_neg(%arg0: !torch.vtensor<[2,3,3],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[2,3,3],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[2,3,3],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[2,3,3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[2,3,3],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[2,3,3],si64> return %0 : !torch.vtensor<[2,3,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_tril_zero/model.mlir b/iree_tests/onnx/node/generated/test_tril_zero/model.mlir index 3f87e48e2..11d576d6c 100644 --- a/iree_tests/onnx/node/generated/test_tril_zero/model.mlir +++ b/iree_tests/onnx/node/generated/test_tril_zero/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_tril_zero(%arg0: !torch.vtensor<[3,0,5],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[3,0,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[3,0,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[3,0,5],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) {torch.onnx.upper = 0 : si64} : (!torch.vtensor<[3,0,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[3,0,5],si64> return %0 : !torch.vtensor<[3,0,5],si64> } } diff --git a/iree_tests/onnx/node/generated/test_triu/model.mlir b/iree_tests/onnx/node/generated/test_triu/model.mlir index 4a1be4e4c..423626a65 100644 --- a/iree_tests/onnx/node/generated/test_triu/model.mlir +++ b/iree_tests/onnx/node/generated/test_triu/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_triu(%arg0: !torch.vtensor<[4,5],si64>) -> !torch.vtensor<[4,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0) : (!torch.vtensor<[4,5],si64>) -> !torch.vtensor<[4,5],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0) : (!torch.vtensor<[4,5],si64>) -> !torch.vtensor<[4,5],si64> return %0 : !torch.vtensor<[4,5],si64> } } diff --git a/iree_tests/onnx/node/generated/test_triu_neg/model.mlir b/iree_tests/onnx/node/generated/test_triu_neg/model.mlir index 43651481d..e46c0728b 100644 --- a/iree_tests/onnx/node/generated/test_triu_neg/model.mlir +++ b/iree_tests/onnx/node/generated/test_triu_neg/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_triu_neg(%arg0: !torch.vtensor<[4,5],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> return %0 : !torch.vtensor<[4,5],si64> } } diff --git a/iree_tests/onnx/node/generated/test_triu_one_row/model.mlir b/iree_tests/onnx/node/generated/test_triu_one_row/model.mlir index b9e2f81c6..0c8153526 100644 --- a/iree_tests/onnx/node/generated/test_triu_one_row/model.mlir +++ b/iree_tests/onnx/node/generated/test_triu_one_row/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_triu_one_row(%arg0: !torch.vtensor<[3,1,5],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[3,1,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) : (!torch.vtensor<[3,1,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[3,1,5],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) : (!torch.vtensor<[3,1,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[3,1,5],si64> return %0 : !torch.vtensor<[3,1,5],si64> } } diff --git a/iree_tests/onnx/node/generated/test_triu_out_neg_out/model.mlir b/iree_tests/onnx/node/generated/test_triu_out_neg_out/model.mlir index 8370606ad..887258d72 100644 --- a/iree_tests/onnx/node/generated/test_triu_out_neg_out/model.mlir +++ b/iree_tests/onnx/node/generated/test_triu_out_neg_out/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_triu_out_neg_out(%arg0: !torch.vtensor<[4,5],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> return %0 : !torch.vtensor<[4,5],si64> } } diff --git a/iree_tests/onnx/node/generated/test_triu_out_pos/model.mlir b/iree_tests/onnx/node/generated/test_triu_out_pos/model.mlir index 698cb3bda..0972be62c 100644 --- a/iree_tests/onnx/node/generated/test_triu_out_pos/model.mlir +++ b/iree_tests/onnx/node/generated/test_triu_out_pos/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_triu_out_pos(%arg0: !torch.vtensor<[4,5],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> return %0 : !torch.vtensor<[4,5],si64> } } diff --git a/iree_tests/onnx/node/generated/test_triu_pos/model.mlir b/iree_tests/onnx/node/generated/test_triu_pos/model.mlir index 8aad36c27..d208eb4aa 100644 --- a/iree_tests/onnx/node/generated/test_triu_pos/model.mlir +++ b/iree_tests/onnx/node/generated/test_triu_pos/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_triu_pos(%arg0: !torch.vtensor<[4,5],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) : (!torch.vtensor<[4,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[4,5],si64> return %0 : !torch.vtensor<[4,5],si64> } } diff --git a/iree_tests/onnx/node/generated/test_triu_square/model.mlir b/iree_tests/onnx/node/generated/test_triu_square/model.mlir index b2e75e74c..f17b75094 100644 --- a/iree_tests/onnx/node/generated/test_triu_square/model.mlir +++ b/iree_tests/onnx/node/generated/test_triu_square/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_triu_square(%arg0: !torch.vtensor<[2,3,3],si64>) -> !torch.vtensor<[2,3,3],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0) : (!torch.vtensor<[2,3,3],si64>) -> !torch.vtensor<[2,3,3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0) : (!torch.vtensor<[2,3,3],si64>) -> !torch.vtensor<[2,3,3],si64> return %0 : !torch.vtensor<[2,3,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_triu_square_neg/model.mlir b/iree_tests/onnx/node/generated/test_triu_square_neg/model.mlir index ca8fabe8c..955a70393 100644 --- a/iree_tests/onnx/node/generated/test_triu_square_neg/model.mlir +++ b/iree_tests/onnx/node/generated/test_triu_square_neg/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_triu_square_neg(%arg0: !torch.vtensor<[2,3,3],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[2,3,3],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) : (!torch.vtensor<[2,3,3],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[2,3,3],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) : (!torch.vtensor<[2,3,3],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[2,3,3],si64> return %0 : !torch.vtensor<[2,3,3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_triu_zero/model.mlir b/iree_tests/onnx/node/generated/test_triu_zero/model.mlir index 313494c28..839ef5c1f 100644 --- a/iree_tests/onnx/node/generated/test_triu_zero/model.mlir +++ b/iree_tests/onnx/node/generated/test_triu_zero/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_triu_zero(%arg0: !torch.vtensor<[0,5],si64>, %arg1: !torch.vtensor<[],si64>) -> !torch.vtensor<[0,5],si64> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 14 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) : (!torch.vtensor<[0,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[0,5],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Trilu"(%arg0, %arg1) : (!torch.vtensor<[0,5],si64>, !torch.vtensor<[],si64>) -> !torch.vtensor<[0,5],si64> return %0 : !torch.vtensor<[0,5],si64> } } diff --git a/iree_tests/onnx/node/generated/test_unique_not_sorted_without_axis/model.mlir b/iree_tests/onnx/node/generated/test_unique_not_sorted_without_axis/model.mlir index 61faefd31..74fa0b759 100644 --- a/iree_tests/onnx/node/generated/test_unique_not_sorted_without_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_unique_not_sorted_without_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_unique_not_sorted_without_axis(%arg0: !torch.vtensor<[6],f32>) -> (!torch.vtensor<[4],f32>, !torch.vtensor<[4],si64>, !torch.vtensor<[6],si64>, !torch.vtensor<[4],si64>) attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:4 = torch.operator "onnx.Unique"(%arg0) {torch.onnx.sorted = 0 : si64} : (!torch.vtensor<[6],f32>) -> (!torch.vtensor<[4],f32>, !torch.vtensor<[4],si64>, !torch.vtensor<[6],si64>, !torch.vtensor<[4],si64>) + %none = torch.constant.none + %0:4 = torch.operator "onnx.Unique"(%arg0) {torch.onnx.sorted = 0 : si64} : (!torch.vtensor<[6],f32>) -> (!torch.vtensor<[4],f32>, !torch.vtensor<[4],si64>, !torch.vtensor<[6],si64>, !torch.vtensor<[4],si64>) return %0#0, %0#1, %0#2, %0#3 : !torch.vtensor<[4],f32>, !torch.vtensor<[4],si64>, !torch.vtensor<[6],si64>, !torch.vtensor<[4],si64> } } diff --git a/iree_tests/onnx/node/generated/test_unique_sorted_with_axis/model.mlir b/iree_tests/onnx/node/generated/test_unique_sorted_with_axis/model.mlir index 93478c21b..5cf2d0620 100644 --- a/iree_tests/onnx/node/generated/test_unique_sorted_with_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_unique_sorted_with_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_unique_sorted_with_axis(%arg0: !torch.vtensor<[3,3],f32>) -> (!torch.vtensor<[2,3],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[3],si64>, !torch.vtensor<[2],si64>) attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:4 = torch.operator "onnx.Unique"(%arg0) {torch.onnx.axis = 0 : si64, torch.onnx.sorted = 1 : si64} : (!torch.vtensor<[3,3],f32>) -> (!torch.vtensor<[2,3],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[3],si64>, !torch.vtensor<[2],si64>) + %none = torch.constant.none + %0:4 = torch.operator "onnx.Unique"(%arg0) {torch.onnx.axis = 0 : si64, torch.onnx.sorted = 1 : si64} : (!torch.vtensor<[3,3],f32>) -> (!torch.vtensor<[2,3],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[3],si64>, !torch.vtensor<[2],si64>) return %0#0, %0#1, %0#2, %0#3 : !torch.vtensor<[2,3],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[3],si64>, !torch.vtensor<[2],si64> } } diff --git a/iree_tests/onnx/node/generated/test_unique_sorted_with_axis_3d/model.mlir b/iree_tests/onnx/node/generated/test_unique_sorted_with_axis_3d/model.mlir index 138a6d74c..b6c38456a 100644 --- a/iree_tests/onnx/node/generated/test_unique_sorted_with_axis_3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_unique_sorted_with_axis_3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_unique_sorted_with_axis_3d(%arg0: !torch.vtensor<[2,4,2],f32>) -> (!torch.vtensor<[2,3,2],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[4],si64>, !torch.vtensor<[3],si64>) attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:4 = torch.operator "onnx.Unique"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.sorted = 1 : si64} : (!torch.vtensor<[2,4,2],f32>) -> (!torch.vtensor<[2,3,2],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[4],si64>, !torch.vtensor<[3],si64>) + %none = torch.constant.none + %0:4 = torch.operator "onnx.Unique"(%arg0) {torch.onnx.axis = 1 : si64, torch.onnx.sorted = 1 : si64} : (!torch.vtensor<[2,4,2],f32>) -> (!torch.vtensor<[2,3,2],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[4],si64>, !torch.vtensor<[3],si64>) return %0#0, %0#1, %0#2, %0#3 : !torch.vtensor<[2,3,2],f32>, !torch.vtensor<[3],si64>, !torch.vtensor<[4],si64>, !torch.vtensor<[3],si64> } } diff --git a/iree_tests/onnx/node/generated/test_unique_sorted_with_negative_axis/model.mlir b/iree_tests/onnx/node/generated/test_unique_sorted_with_negative_axis/model.mlir index 02eeed637..1537829a5 100644 --- a/iree_tests/onnx/node/generated/test_unique_sorted_with_negative_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_unique_sorted_with_negative_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_unique_sorted_with_negative_axis(%arg0: !torch.vtensor<[3,3],f32>) -> (!torch.vtensor<[3,2],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[3],si64>, !torch.vtensor<[2],si64>) attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:4 = torch.operator "onnx.Unique"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.sorted = 1 : si64} : (!torch.vtensor<[3,3],f32>) -> (!torch.vtensor<[3,2],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[3],si64>, !torch.vtensor<[2],si64>) + %none = torch.constant.none + %0:4 = torch.operator "onnx.Unique"(%arg0) {torch.onnx.axis = -1 : si64, torch.onnx.sorted = 1 : si64} : (!torch.vtensor<[3,3],f32>) -> (!torch.vtensor<[3,2],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[3],si64>, !torch.vtensor<[2],si64>) return %0#0, %0#1, %0#2, %0#3 : !torch.vtensor<[3,2],f32>, !torch.vtensor<[2],si64>, !torch.vtensor<[3],si64>, !torch.vtensor<[2],si64> } } diff --git a/iree_tests/onnx/node/generated/test_unique_sorted_without_axis/model.mlir b/iree_tests/onnx/node/generated/test_unique_sorted_without_axis/model.mlir index 627cac851..eb23257eb 100644 --- a/iree_tests/onnx/node/generated/test_unique_sorted_without_axis/model.mlir +++ b/iree_tests/onnx/node/generated/test_unique_sorted_without_axis/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_unique_sorted_without_axis(%arg0: !torch.vtensor<[6],f32>) -> (!torch.vtensor<[4],f32>, !torch.vtensor<[4],si64>, !torch.vtensor<[6],si64>, !torch.vtensor<[4],si64>) attributes {torch.onnx_meta.ir_version = 6 : si64, torch.onnx_meta.opset_version = 11 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0:4 = torch.operator "onnx.Unique"(%arg0) : (!torch.vtensor<[6],f32>) -> (!torch.vtensor<[4],f32>, !torch.vtensor<[4],si64>, !torch.vtensor<[6],si64>, !torch.vtensor<[4],si64>) + %none = torch.constant.none + %0:4 = torch.operator "onnx.Unique"(%arg0) : (!torch.vtensor<[6],f32>) -> (!torch.vtensor<[4],f32>, !torch.vtensor<[4],si64>, !torch.vtensor<[6],si64>, !torch.vtensor<[4],si64>) return %0#0, %0#1, %0#2, %0#3 : !torch.vtensor<[4],f32>, !torch.vtensor<[4],si64>, !torch.vtensor<[6],si64>, !torch.vtensor<[4],si64> } } diff --git a/iree_tests/onnx/node/generated/test_unsqueeze_axis_0/model.mlir b/iree_tests/onnx/node/generated/test_unsqueeze_axis_0/model.mlir index ac70ab5e2..c1551388b 100644 --- a/iree_tests/onnx/node/generated/test_unsqueeze_axis_0/model.mlir +++ b/iree_tests/onnx/node/generated/test_unsqueeze_axis_0/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_unsqueeze_axis_0(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,3,4,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Unsqueeze"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,3,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Unsqueeze"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,3,4,5],f32> return %0 : !torch.vtensor<[1,3,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_unsqueeze_axis_1/model.mlir b/iree_tests/onnx/node/generated/test_unsqueeze_axis_1/model.mlir index c6f94f585..63f4189b9 100644 --- a/iree_tests/onnx/node/generated/test_unsqueeze_axis_1/model.mlir +++ b/iree_tests/onnx/node/generated/test_unsqueeze_axis_1/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_unsqueeze_axis_1(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,4,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Unsqueeze"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,4,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Unsqueeze"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,1,4,5],f32> return %0 : !torch.vtensor<[3,1,4,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_unsqueeze_axis_2/model.mlir b/iree_tests/onnx/node/generated/test_unsqueeze_axis_2/model.mlir index ff451d864..28b3739ad 100644 --- a/iree_tests/onnx/node/generated/test_unsqueeze_axis_2/model.mlir +++ b/iree_tests/onnx/node/generated/test_unsqueeze_axis_2/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_unsqueeze_axis_2(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Unsqueeze"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Unsqueeze"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[3,4,1,5],f32> return %0 : !torch.vtensor<[3,4,1,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_unsqueeze_negative_axes/model.mlir b/iree_tests/onnx/node/generated/test_unsqueeze_negative_axes/model.mlir index 6bb82c42f..8f24deddf 100644 --- a/iree_tests/onnx/node/generated/test_unsqueeze_negative_axes/model.mlir +++ b/iree_tests/onnx/node/generated/test_unsqueeze_negative_axes/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_unsqueeze_negative_axes(%arg0: !torch.vtensor<[1,3,1,5],f32>, %arg1: !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,3,1,1,5],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Unsqueeze"(%arg0, %arg1) : (!torch.vtensor<[1,3,1,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,3,1,1,5],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Unsqueeze"(%arg0, %arg1) : (!torch.vtensor<[1,3,1,5],f32>, !torch.vtensor<[1],si64>) -> !torch.vtensor<[1,3,1,1,5],f32> return %0 : !torch.vtensor<[1,3,1,1,5],f32> } } diff --git a/iree_tests/onnx/node/generated/test_unsqueeze_three_axes/model.mlir b/iree_tests/onnx/node/generated/test_unsqueeze_three_axes/model.mlir index fd21067fc..8b3a72e10 100644 --- a/iree_tests/onnx/node/generated/test_unsqueeze_three_axes/model.mlir +++ b/iree_tests/onnx/node/generated/test_unsqueeze_three_axes/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_unsqueeze_three_axes(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,4,1,5,1,1],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Unsqueeze"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,4,1,5,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Unsqueeze"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,4,1,5,1,1],f32> return %0 : !torch.vtensor<[3,4,1,5,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_unsqueeze_two_axes/model.mlir b/iree_tests/onnx/node/generated/test_unsqueeze_two_axes/model.mlir index 718be4e43..187d2ef77 100644 --- a/iree_tests/onnx/node/generated/test_unsqueeze_two_axes/model.mlir +++ b/iree_tests/onnx/node/generated/test_unsqueeze_two_axes/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_unsqueeze_two_axes(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,1,4,5,1],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Unsqueeze"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,1,4,5,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Unsqueeze"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[2],si64>) -> !torch.vtensor<[3,1,4,5,1],f32> return %0 : !torch.vtensor<[3,1,4,5,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_unsqueeze_unsorted_axes/model.mlir b/iree_tests/onnx/node/generated/test_unsqueeze_unsorted_axes/model.mlir index 82fd88707..b91743b05 100644 --- a/iree_tests/onnx/node/generated/test_unsqueeze_unsorted_axes/model.mlir +++ b/iree_tests/onnx/node/generated/test_unsqueeze_unsorted_axes/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_unsqueeze_unsorted_axes(%arg0: !torch.vtensor<[3,4,5],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,4,1,5,1,1],f32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Unsqueeze"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,4,1,5,1,1],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Unsqueeze"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[3,4,1,5,1,1],f32> return %0 : !torch.vtensor<[3,4,1,5,1,1],f32> } } diff --git a/iree_tests/onnx/node/generated/test_upsample_nearest/model.mlir b/iree_tests/onnx/node/generated/test_upsample_nearest/model.mlir index 2ba6e6e04..28d40dff1 100644 --- a/iree_tests/onnx/node/generated/test_upsample_nearest/model.mlir +++ b/iree_tests/onnx/node/generated/test_upsample_nearest/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_upsample_nearest(%arg0: !torch.vtensor<[1,1,2,2],f32>, %arg1: !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,4,6],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Upsample"(%arg0, %arg1) {torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,2,2],f32>, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,4,6],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Upsample"(%arg0, %arg1) {torch.onnx.mode = "nearest"} : (!torch.vtensor<[1,1,2,2],f32>, !torch.vtensor<[4],f32>) -> !torch.vtensor<[1,1,4,6],f32> return %0 : !torch.vtensor<[1,1,4,6],f32> } } diff --git a/iree_tests/onnx/node/generated/test_where_example/model.mlir b/iree_tests/onnx/node/generated/test_where_example/model.mlir index 498e80e30..3f792dea0 100644 --- a/iree_tests/onnx/node/generated/test_where_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_where_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_where_example(%arg0: !torch.vtensor<[2,2],i1>, %arg1: !torch.vtensor<[2,2],f32>, %arg2: !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,2],f32> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Where"(%arg0, %arg1, %arg2) : (!torch.vtensor<[2,2],i1>, !torch.vtensor<[2,2],f32>, !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,2],f32> + %none = torch.constant.none + %0 = torch.operator "onnx.Where"(%arg0, %arg1, %arg2) : (!torch.vtensor<[2,2],i1>, !torch.vtensor<[2,2],f32>, !torch.vtensor<[2,2],f32>) -> !torch.vtensor<[2,2],f32> return %0 : !torch.vtensor<[2,2],f32> } } diff --git a/iree_tests/onnx/node/generated/test_where_long_example/model.mlir b/iree_tests/onnx/node/generated/test_where_long_example/model.mlir index a316a62cf..7f34c464c 100644 --- a/iree_tests/onnx/node/generated/test_where_long_example/model.mlir +++ b/iree_tests/onnx/node/generated/test_where_long_example/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_where_long_example(%arg0: !torch.vtensor<[2,2],i1>, %arg1: !torch.vtensor<[2,2],si64>, %arg2: !torch.vtensor<[2,2],si64>) -> !torch.vtensor<[2,2],si64> attributes {torch.onnx_meta.ir_version = 8 : si64, torch.onnx_meta.opset_version = 16 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Where"(%arg0, %arg1, %arg2) : (!torch.vtensor<[2,2],i1>, !torch.vtensor<[2,2],si64>, !torch.vtensor<[2,2],si64>) -> !torch.vtensor<[2,2],si64> + %none = torch.constant.none + %0 = torch.operator "onnx.Where"(%arg0, %arg1, %arg2) : (!torch.vtensor<[2,2],i1>, !torch.vtensor<[2,2],si64>, !torch.vtensor<[2,2],si64>) -> !torch.vtensor<[2,2],si64> return %0 : !torch.vtensor<[2,2],si64> } } diff --git a/iree_tests/onnx/node/generated/test_wrap_pad/model.mlir b/iree_tests/onnx/node/generated/test_wrap_pad/model.mlir index de615b676..1947ebc8d 100644 --- a/iree_tests/onnx/node/generated/test_wrap_pad/model.mlir +++ b/iree_tests/onnx/node/generated/test_wrap_pad/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_wrap_pad(%arg0: !torch.vtensor<[1,3,4,5],si32>, %arg1: !torch.vtensor<[8],si64>) -> !torch.vtensor<[1,3,6,7],si32> attributes {torch.onnx_meta.ir_version = 10 : si64, torch.onnx_meta.opset_version = 21 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Pad"(%arg0, %arg1) {torch.onnx.mode = "wrap"} : (!torch.vtensor<[1,3,4,5],si32>, !torch.vtensor<[8],si64>) -> !torch.vtensor<[1,3,6,7],si32> + %none = torch.constant.none + %0 = torch.operator "onnx.Pad"(%arg0, %arg1) {torch.onnx.mode = "wrap"} : (!torch.vtensor<[1,3,4,5],si32>, !torch.vtensor<[8],si64>) -> !torch.vtensor<[1,3,6,7],si32> return %0 : !torch.vtensor<[1,3,6,7],si32> } } diff --git a/iree_tests/onnx/node/generated/test_xor2d/model.mlir b/iree_tests/onnx/node/generated/test_xor2d/model.mlir index 66fc2e115..5740a1b0e 100644 --- a/iree_tests/onnx/node/generated/test_xor2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_xor2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_xor2d(%arg0: !torch.vtensor<[3,4],i1>, %arg1: !torch.vtensor<[3,4],i1>) -> !torch.vtensor<[3,4],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Xor"(%arg0, %arg1) : (!torch.vtensor<[3,4],i1>, !torch.vtensor<[3,4],i1>) -> !torch.vtensor<[3,4],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Xor"(%arg0, %arg1) : (!torch.vtensor<[3,4],i1>, !torch.vtensor<[3,4],i1>) -> !torch.vtensor<[3,4],i1> return %0 : !torch.vtensor<[3,4],i1> } } diff --git a/iree_tests/onnx/node/generated/test_xor3d/model.mlir b/iree_tests/onnx/node/generated/test_xor3d/model.mlir index 3579d31c4..676fc0ce7 100644 --- a/iree_tests/onnx/node/generated/test_xor3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_xor3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_xor3d(%arg0: !torch.vtensor<[3,4,5],i1>, %arg1: !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Xor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Xor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[3,4,5],i1>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_xor4d/model.mlir b/iree_tests/onnx/node/generated/test_xor4d/model.mlir index bfcf433da..a7cd50431 100644 --- a/iree_tests/onnx/node/generated/test_xor4d/model.mlir +++ b/iree_tests/onnx/node/generated/test_xor4d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_xor4d(%arg0: !torch.vtensor<[3,4,5,6],i1>, %arg1: !torch.vtensor<[3,4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Xor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[3,4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Xor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[3,4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> return %0 : !torch.vtensor<[3,4,5,6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_xor_bcast3v1d/model.mlir b/iree_tests/onnx/node/generated/test_xor_bcast3v1d/model.mlir index e50536d49..0d094053f 100644 --- a/iree_tests/onnx/node/generated/test_xor_bcast3v1d/model.mlir +++ b/iree_tests/onnx/node/generated/test_xor_bcast3v1d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_xor_bcast3v1d(%arg0: !torch.vtensor<[3,4,5],i1>, %arg1: !torch.vtensor<[5],i1>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Xor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[5],i1>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Xor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[5],i1>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_xor_bcast3v2d/model.mlir b/iree_tests/onnx/node/generated/test_xor_bcast3v2d/model.mlir index 8c89a5a0b..f13b1a89e 100644 --- a/iree_tests/onnx/node/generated/test_xor_bcast3v2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_xor_bcast3v2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_xor_bcast3v2d(%arg0: !torch.vtensor<[3,4,5],i1>, %arg1: !torch.vtensor<[4,5],i1>) -> !torch.vtensor<[3,4,5],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Xor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[4,5],i1>) -> !torch.vtensor<[3,4,5],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Xor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5],i1>, !torch.vtensor<[4,5],i1>) -> !torch.vtensor<[3,4,5],i1> return %0 : !torch.vtensor<[3,4,5],i1> } } diff --git a/iree_tests/onnx/node/generated/test_xor_bcast4v2d/model.mlir b/iree_tests/onnx/node/generated/test_xor_bcast4v2d/model.mlir index 1df287004..7299ea2c0 100644 --- a/iree_tests/onnx/node/generated/test_xor_bcast4v2d/model.mlir +++ b/iree_tests/onnx/node/generated/test_xor_bcast4v2d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_xor_bcast4v2d(%arg0: !torch.vtensor<[3,4,5,6],i1>, %arg1: !torch.vtensor<[5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Xor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Xor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> return %0 : !torch.vtensor<[3,4,5,6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_xor_bcast4v3d/model.mlir b/iree_tests/onnx/node/generated/test_xor_bcast4v3d/model.mlir index c1777db1b..3f6f48445 100644 --- a/iree_tests/onnx/node/generated/test_xor_bcast4v3d/model.mlir +++ b/iree_tests/onnx/node/generated/test_xor_bcast4v3d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_xor_bcast4v3d(%arg0: !torch.vtensor<[3,4,5,6],i1>, %arg1: !torch.vtensor<[4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Xor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Xor"(%arg0, %arg1) : (!torch.vtensor<[3,4,5,6],i1>, !torch.vtensor<[4,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> return %0 : !torch.vtensor<[3,4,5,6],i1> } } diff --git a/iree_tests/onnx/node/generated/test_xor_bcast4v4d/model.mlir b/iree_tests/onnx/node/generated/test_xor_bcast4v4d/model.mlir index 0cc1ebb60..9383ea2d2 100644 --- a/iree_tests/onnx/node/generated/test_xor_bcast4v4d/model.mlir +++ b/iree_tests/onnx/node/generated/test_xor_bcast4v4d/model.mlir @@ -1,6 +1,7 @@ module { func.func @test_xor_bcast4v4d(%arg0: !torch.vtensor<[1,4,1,6],i1>, %arg1: !torch.vtensor<[3,1,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> attributes {torch.onnx_meta.ir_version = 3 : si64, torch.onnx_meta.opset_version = 7 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} { - %0 = torch.operator "onnx.Xor"(%arg0, %arg1) : (!torch.vtensor<[1,4,1,6],i1>, !torch.vtensor<[3,1,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> + %none = torch.constant.none + %0 = torch.operator "onnx.Xor"(%arg0, %arg1) : (!torch.vtensor<[1,4,1,6],i1>, !torch.vtensor<[3,1,5,6],i1>) -> !torch.vtensor<[3,4,5,6],i1> return %0 : !torch.vtensor<[3,4,5,6],i1> } } diff --git a/iree_tests/onnx/node/import_failures.txt b/iree_tests/onnx/node/import_failures.txt index b27ad2e02..ddd750b5d 100644 --- a/iree_tests/onnx/node/import_failures.txt +++ b/iree_tests/onnx/node/import_failures.txt @@ -1,200 +1,34 @@ -test_affine_grid_2d_align_corners_expanded -test_affine_grid_2d_expanded -test_affine_grid_3d_align_corners_expanded -test_affine_grid_3d_expanded -test_ai_onnx_ml_label_encoder_string_int -test_ai_onnx_ml_label_encoder_string_int_no_default test_ai_onnx_ml_label_encoder_tensor_mapping -test_ai_onnx_ml_label_encoder_tensor_value_only_mapping test_ai_onnx_ml_tree_ensemble_set_membership test_ai_onnx_ml_tree_ensemble_single_tree -test_cast_FLOAT16_to_FLOAT8E4M3FN -test_cast_FLOAT16_to_FLOAT8E4M3FNUZ -test_cast_FLOAT16_to_FLOAT8E5M2 -test_cast_FLOAT16_to_FLOAT8E5M2FNUZ test_cast_FLOAT16_to_INT4 test_cast_FLOAT16_to_UINT4 -test_cast_FLOAT8E4M3FNUZ_to_FLOAT -test_cast_FLOAT8E4M3FNUZ_to_FLOAT16 -test_cast_FLOAT8E4M3FN_to_FLOAT -test_cast_FLOAT8E4M3FN_to_FLOAT16 -test_cast_FLOAT8E5M2FNUZ_to_FLOAT -test_cast_FLOAT8E5M2FNUZ_to_FLOAT16 -test_cast_FLOAT8E5M2_to_FLOAT -test_cast_FLOAT8E5M2_to_FLOAT16 -test_cast_FLOAT_to_FLOAT8E4M3FN -test_cast_FLOAT_to_FLOAT8E4M3FNUZ -test_cast_FLOAT_to_FLOAT8E5M2 -test_cast_FLOAT_to_FLOAT8E5M2FNUZ test_cast_FLOAT_to_INT4 -test_cast_FLOAT_to_STRING test_cast_FLOAT_to_UINT4 test_cast_INT4_to_FLOAT test_cast_INT4_to_FLOAT16 test_cast_INT4_to_INT8 -test_cast_STRING_to_FLOAT test_cast_UINT4_to_FLOAT test_cast_UINT4_to_FLOAT16 test_cast_UINT4_to_UINT8 -test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN -test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ -test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2 -test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ -test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN -test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ -test_cast_no_saturate_FLOAT_to_FLOAT8E5M2 -test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ -test_castlike_FLOAT8E4M3FNUZ_to_FLOAT -test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded -test_castlike_FLOAT8E4M3FN_to_FLOAT -test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded -test_castlike_FLOAT8E5M2FNUZ_to_FLOAT -test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded -test_castlike_FLOAT8E5M2_to_FLOAT -test_castlike_FLOAT8E5M2_to_FLOAT_expanded -test_castlike_FLOAT_to_FLOAT8E4M3FN -test_castlike_FLOAT_to_FLOAT8E4M3FNUZ -test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded -test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded -test_castlike_FLOAT_to_FLOAT8E5M2 -test_castlike_FLOAT_to_FLOAT8E5M2FNUZ -test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded -test_castlike_FLOAT_to_FLOAT8E5M2_expanded -test_castlike_FLOAT_to_STRING -test_castlike_FLOAT_to_STRING_expanded -test_castlike_STRING_to_FLOAT -test_castlike_STRING_to_FLOAT_expanded -test_center_crop_pad_crop_axes_chw_expanded -test_center_crop_pad_crop_axes_hwc_expanded -test_center_crop_pad_crop_negative_axes_hwc_expanded -test_clip_default_inbounds -test_clip_default_int8_inbounds -test_clip_default_int8_max -test_clip_default_max -test_constantofshape_float_ones -test_constantofshape_int_shape_zero -test_constantofshape_int_zeros -test_dequantizelinear_e4m3fn test_dequantizelinear_e4m3fn_float16 -test_dequantizelinear_e4m3fn_zero_point -test_dequantizelinear_e5m2 test_dequantizelinear_int4 test_dequantizelinear_uint4 -test_dft -test_dft_axis -test_dft_inverse -test_equal_string -test_equal_string_broadcast -test_gru_defaults -test_gru_seq_length -test_gru_with_initial_bias test_identity_opt test_identity_sequence -test_if test_if_opt test_if_seq -test_layer_normalization_2d_axis0_expanded -test_layer_normalization_2d_axis0_expanded_ver18 -test_layer_normalization_2d_axis1_expanded -test_layer_normalization_2d_axis1_expanded_ver18 -test_layer_normalization_2d_axis_negative_1_expanded -test_layer_normalization_2d_axis_negative_1_expanded_ver18 -test_layer_normalization_2d_axis_negative_2_expanded -test_layer_normalization_2d_axis_negative_2_expanded_ver18 -test_layer_normalization_3d_axis0_epsilon_expanded -test_layer_normalization_3d_axis0_epsilon_expanded_ver18 -test_layer_normalization_3d_axis1_epsilon_expanded -test_layer_normalization_3d_axis1_epsilon_expanded_ver18 -test_layer_normalization_3d_axis2_epsilon_expanded -test_layer_normalization_3d_axis2_epsilon_expanded_ver18 -test_layer_normalization_3d_axis_negative_1_epsilon_expanded -test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18 -test_layer_normalization_3d_axis_negative_2_epsilon_expanded -test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18 -test_layer_normalization_3d_axis_negative_3_epsilon_expanded -test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18 -test_layer_normalization_4d_axis0_expanded -test_layer_normalization_4d_axis0_expanded_ver18 -test_layer_normalization_4d_axis1_expanded -test_layer_normalization_4d_axis1_expanded_ver18 -test_layer_normalization_4d_axis2_expanded -test_layer_normalization_4d_axis2_expanded_ver18 -test_layer_normalization_4d_axis3_expanded -test_layer_normalization_4d_axis3_expanded_ver18 -test_layer_normalization_4d_axis_negative_1_expanded -test_layer_normalization_4d_axis_negative_1_expanded_ver18 -test_layer_normalization_4d_axis_negative_2_expanded -test_layer_normalization_4d_axis_negative_2_expanded_ver18 -test_layer_normalization_4d_axis_negative_3_expanded -test_layer_normalization_4d_axis_negative_3_expanded_ver18 -test_layer_normalization_4d_axis_negative_4_expanded -test_layer_normalization_4d_axis_negative_4_expanded_ver18 -test_layer_normalization_default_axis_expanded -test_layer_normalization_default_axis_expanded_ver18 -test_loop11 test_loop13_seq test_loop16_seq_none -test_lstm_defaults -test_lstm_with_initial_bias -test_lstm_with_peepholes test_maxpool_2d_ceil_output_size_reduce_by_one test_optional_get_element_optional_sequence test_optional_get_element_optional_tensor test_optional_get_element_sequence -test_optional_has_element_empty_no_input_name_optional_input -test_optional_has_element_empty_no_input_name_tensor_input test_optional_has_element_empty_optional_input test_optional_has_element_optional_input test_optional_has_element_tensor_input -test_quantizelinear_e4m3fn -test_quantizelinear_e5m2 test_quantizelinear_int4 test_quantizelinear_uint4 -test_range_float_type_positive_delta_expanded -test_range_int32_type_negative_delta_expanded -test_regex_full_match_basic -test_regex_full_match_email_domain -test_regex_full_match_empty -test_resize_downsample_scales_cubic -test_resize_downsample_scales_cubic_A_n0p5_exclude_outside -test_resize_downsample_scales_cubic_align_corners -test_resize_downsample_scales_cubic_antialias -test_resize_downsample_scales_linear -test_resize_downsample_scales_linear_align_corners -test_resize_downsample_scales_linear_antialias -test_resize_downsample_scales_linear_half_pixel_symmetric -test_resize_downsample_scales_nearest -test_resize_downsample_sizes_cubic -test_resize_downsample_sizes_cubic_antialias -test_resize_downsample_sizes_linear_antialias -test_resize_downsample_sizes_linear_pytorch_half_pixel -test_resize_downsample_sizes_nearest -test_resize_downsample_sizes_nearest_not_larger -test_resize_downsample_sizes_nearest_not_smaller -test_resize_tf_crop_and_resize -test_resize_tf_crop_and_resize_axes_2_3 -test_resize_tf_crop_and_resize_axes_3_2 -test_resize_upsample_scales_cubic -test_resize_upsample_scales_cubic_A_n0p5_exclude_outside -test_resize_upsample_scales_cubic_align_corners -test_resize_upsample_scales_cubic_asymmetric -test_resize_upsample_scales_linear -test_resize_upsample_scales_linear_align_corners -test_resize_upsample_scales_linear_half_pixel_symmetric -test_resize_upsample_scales_nearest -test_resize_upsample_scales_nearest_axes_2_3 -test_resize_upsample_scales_nearest_axes_3_2 -test_resize_upsample_sizes_cubic -test_resize_upsample_sizes_nearest -test_resize_upsample_sizes_nearest_axes_2_3 -test_resize_upsample_sizes_nearest_axes_3_2 -test_resize_upsample_sizes_nearest_ceil_half_pixel -test_resize_upsample_sizes_nearest_floor_align_corners -test_resize_upsample_sizes_nearest_not_larger -test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric -test_rnn_seq_length -test_scan9_sum -test_scan_sum test_sequence_insert_at_back test_sequence_insert_at_front test_sequence_map_add_1_sequence_1_tensor @@ -209,26 +43,6 @@ test_sequence_map_identity_1_sequence_1_tensor_expanded test_sequence_map_identity_1_sequence_expanded test_sequence_map_identity_2_sequences test_sequence_map_identity_2_sequences_expanded -test_simple_rnn_defaults -test_simple_rnn_with_initial_bias test_split_to_sequence_1 test_split_to_sequence_2 -test_split_to_sequence_nokeepdims -test_stft -test_string_concat -test_string_concat_broadcasting -test_string_concat_empty_string -test_string_concat_utf8 -test_string_concat_zero_dimensional -test_string_split_basic -test_string_split_consecutive_delimiters -test_string_split_empty_string_delimiter -test_string_split_empty_tensor -test_string_split_maxsplit -test_string_split_no_delimiter -test_strnormalizer_export_monday_casesensintive_lower -test_strnormalizer_export_monday_casesensintive_nochangecase -test_strnormalizer_export_monday_casesensintive_upper -test_strnormalizer_export_monday_empty_output -test_strnormalizer_export_monday_insensintive_upper_twodim -test_strnormalizer_nostopwords_nochangecase \ No newline at end of file +test_split_to_sequence_nokeepdims \ No newline at end of file diff --git a/iree_tests/onnx/node/import_successes.txt b/iree_tests/onnx/node/import_successes.txt index 2f36a640a..4b6a8ab5f 100644 --- a/iree_tests/onnx/node/import_successes.txt +++ b/iree_tests/onnx/node/import_successes.txt @@ -12,10 +12,17 @@ test_add_bcast test_add_uint8 test_affine_grid_2d test_affine_grid_2d_align_corners +test_affine_grid_2d_align_corners_expanded +test_affine_grid_2d_expanded test_affine_grid_3d test_affine_grid_3d_align_corners +test_affine_grid_3d_align_corners_expanded +test_affine_grid_3d_expanded test_ai_onnx_ml_array_feature_extractor test_ai_onnx_ml_binarizer +test_ai_onnx_ml_label_encoder_string_int +test_ai_onnx_ml_label_encoder_string_int_no_default +test_ai_onnx_ml_label_encoder_tensor_value_only_mapping test_and2d test_and3d test_and4d @@ -129,9 +136,35 @@ test_cast_DOUBLE_to_FLOAT test_cast_DOUBLE_to_FLOAT16 test_cast_FLOAT16_to_DOUBLE test_cast_FLOAT16_to_FLOAT +test_cast_FLOAT16_to_FLOAT8E4M3FN +test_cast_FLOAT16_to_FLOAT8E4M3FNUZ +test_cast_FLOAT16_to_FLOAT8E5M2 +test_cast_FLOAT16_to_FLOAT8E5M2FNUZ +test_cast_FLOAT8E4M3FNUZ_to_FLOAT +test_cast_FLOAT8E4M3FNUZ_to_FLOAT16 +test_cast_FLOAT8E4M3FN_to_FLOAT +test_cast_FLOAT8E4M3FN_to_FLOAT16 +test_cast_FLOAT8E5M2FNUZ_to_FLOAT +test_cast_FLOAT8E5M2FNUZ_to_FLOAT16 +test_cast_FLOAT8E5M2_to_FLOAT +test_cast_FLOAT8E5M2_to_FLOAT16 test_cast_FLOAT_to_BFLOAT16 test_cast_FLOAT_to_DOUBLE test_cast_FLOAT_to_FLOAT16 +test_cast_FLOAT_to_FLOAT8E4M3FN +test_cast_FLOAT_to_FLOAT8E4M3FNUZ +test_cast_FLOAT_to_FLOAT8E5M2 +test_cast_FLOAT_to_FLOAT8E5M2FNUZ +test_cast_FLOAT_to_STRING +test_cast_STRING_to_FLOAT +test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FN +test_cast_no_saturate_FLOAT16_to_FLOAT8E4M3FNUZ +test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2 +test_cast_no_saturate_FLOAT16_to_FLOAT8E5M2FNUZ +test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FN +test_cast_no_saturate_FLOAT_to_FLOAT8E4M3FNUZ +test_cast_no_saturate_FLOAT_to_FLOAT8E5M2 +test_cast_no_saturate_FLOAT_to_FLOAT8E5M2FNUZ test_castlike_BFLOAT16_to_FLOAT test_castlike_BFLOAT16_to_FLOAT_expanded test_castlike_DOUBLE_to_FLOAT @@ -142,12 +175,32 @@ test_castlike_FLOAT16_to_DOUBLE test_castlike_FLOAT16_to_DOUBLE_expanded test_castlike_FLOAT16_to_FLOAT test_castlike_FLOAT16_to_FLOAT_expanded +test_castlike_FLOAT8E4M3FNUZ_to_FLOAT +test_castlike_FLOAT8E4M3FNUZ_to_FLOAT_expanded +test_castlike_FLOAT8E4M3FN_to_FLOAT +test_castlike_FLOAT8E4M3FN_to_FLOAT_expanded +test_castlike_FLOAT8E5M2FNUZ_to_FLOAT +test_castlike_FLOAT8E5M2FNUZ_to_FLOAT_expanded +test_castlike_FLOAT8E5M2_to_FLOAT +test_castlike_FLOAT8E5M2_to_FLOAT_expanded test_castlike_FLOAT_to_BFLOAT16 test_castlike_FLOAT_to_BFLOAT16_expanded test_castlike_FLOAT_to_DOUBLE test_castlike_FLOAT_to_DOUBLE_expanded test_castlike_FLOAT_to_FLOAT16 test_castlike_FLOAT_to_FLOAT16_expanded +test_castlike_FLOAT_to_FLOAT8E4M3FN +test_castlike_FLOAT_to_FLOAT8E4M3FNUZ +test_castlike_FLOAT_to_FLOAT8E4M3FNUZ_expanded +test_castlike_FLOAT_to_FLOAT8E4M3FN_expanded +test_castlike_FLOAT_to_FLOAT8E5M2 +test_castlike_FLOAT_to_FLOAT8E5M2FNUZ +test_castlike_FLOAT_to_FLOAT8E5M2FNUZ_expanded +test_castlike_FLOAT_to_FLOAT8E5M2_expanded +test_castlike_FLOAT_to_STRING +test_castlike_FLOAT_to_STRING_expanded +test_castlike_STRING_to_FLOAT +test_castlike_STRING_to_FLOAT_expanded test_ceil test_ceil_example test_celu @@ -156,17 +209,24 @@ test_center_crop_pad_crop test_center_crop_pad_crop_and_pad test_center_crop_pad_crop_and_pad_expanded test_center_crop_pad_crop_axes_chw +test_center_crop_pad_crop_axes_chw_expanded test_center_crop_pad_crop_axes_hwc +test_center_crop_pad_crop_axes_hwc_expanded test_center_crop_pad_crop_expanded test_center_crop_pad_crop_negative_axes_hwc +test_center_crop_pad_crop_negative_axes_hwc_expanded test_center_crop_pad_pad test_center_crop_pad_pad_expanded test_clip +test_clip_default_inbounds test_clip_default_inbounds_expanded +test_clip_default_int8_inbounds test_clip_default_int8_inbounds_expanded +test_clip_default_int8_max test_clip_default_int8_max_expanded test_clip_default_int8_min test_clip_default_int8_min_expanded +test_clip_default_max test_clip_default_max_expanded test_clip_default_min test_clip_default_min_expanded @@ -204,6 +264,9 @@ test_constant test_constant_pad test_constant_pad_axes test_constant_pad_negative_axes +test_constantofshape_float_ones +test_constantofshape_int_shape_zero +test_constantofshape_int_zeros test_conv_with_autopad_same test_conv_with_strides_and_asymmetric_padding test_conv_with_strides_no_padding @@ -237,11 +300,17 @@ test_depthtospace_example test_dequantizelinear test_dequantizelinear_axis test_dequantizelinear_blocked +test_dequantizelinear_e4m3fn +test_dequantizelinear_e4m3fn_zero_point +test_dequantizelinear_e5m2 test_dequantizelinear_int16 test_dequantizelinear_uint16 test_det_2d test_det_nd +test_dft +test_dft_axis test_dft_axis_opset19 +test_dft_inverse test_dft_inverse_opset19 test_dft_opset19 test_div @@ -274,6 +343,8 @@ test_elu_example_expanded_ver18 test_elu_expanded_ver18 test_equal test_equal_bcast +test_equal_string +test_equal_string_broadcast test_erf test_exp test_exp_example @@ -355,6 +426,9 @@ test_group_normalization_epsilon_expanded test_group_normalization_example test_group_normalization_example_expanded test_gru_batchwise +test_gru_defaults +test_gru_seq_length +test_gru_with_initial_bias test_hammingwindow test_hammingwindow_expanded test_hammingwindow_symmetric @@ -379,6 +453,7 @@ test_hardsigmoid_expanded_ver18 test_hardswish test_hardswish_expanded test_identity +test_if test_image_decoder_decode_bmp_rgb test_image_decoder_decode_jpeg2k_rgb test_image_decoder_decode_jpeg_bgr @@ -397,24 +472,62 @@ test_isinf_positive test_isnan test_isnan_float16 test_layer_normalization_2d_axis0 +test_layer_normalization_2d_axis0_expanded +test_layer_normalization_2d_axis0_expanded_ver18 test_layer_normalization_2d_axis1 +test_layer_normalization_2d_axis1_expanded +test_layer_normalization_2d_axis1_expanded_ver18 test_layer_normalization_2d_axis_negative_1 +test_layer_normalization_2d_axis_negative_1_expanded +test_layer_normalization_2d_axis_negative_1_expanded_ver18 test_layer_normalization_2d_axis_negative_2 +test_layer_normalization_2d_axis_negative_2_expanded +test_layer_normalization_2d_axis_negative_2_expanded_ver18 test_layer_normalization_3d_axis0_epsilon +test_layer_normalization_3d_axis0_epsilon_expanded +test_layer_normalization_3d_axis0_epsilon_expanded_ver18 test_layer_normalization_3d_axis1_epsilon +test_layer_normalization_3d_axis1_epsilon_expanded +test_layer_normalization_3d_axis1_epsilon_expanded_ver18 test_layer_normalization_3d_axis2_epsilon +test_layer_normalization_3d_axis2_epsilon_expanded +test_layer_normalization_3d_axis2_epsilon_expanded_ver18 test_layer_normalization_3d_axis_negative_1_epsilon +test_layer_normalization_3d_axis_negative_1_epsilon_expanded +test_layer_normalization_3d_axis_negative_1_epsilon_expanded_ver18 test_layer_normalization_3d_axis_negative_2_epsilon +test_layer_normalization_3d_axis_negative_2_epsilon_expanded +test_layer_normalization_3d_axis_negative_2_epsilon_expanded_ver18 test_layer_normalization_3d_axis_negative_3_epsilon +test_layer_normalization_3d_axis_negative_3_epsilon_expanded +test_layer_normalization_3d_axis_negative_3_epsilon_expanded_ver18 test_layer_normalization_4d_axis0 +test_layer_normalization_4d_axis0_expanded +test_layer_normalization_4d_axis0_expanded_ver18 test_layer_normalization_4d_axis1 +test_layer_normalization_4d_axis1_expanded +test_layer_normalization_4d_axis1_expanded_ver18 test_layer_normalization_4d_axis2 +test_layer_normalization_4d_axis2_expanded +test_layer_normalization_4d_axis2_expanded_ver18 test_layer_normalization_4d_axis3 +test_layer_normalization_4d_axis3_expanded +test_layer_normalization_4d_axis3_expanded_ver18 test_layer_normalization_4d_axis_negative_1 +test_layer_normalization_4d_axis_negative_1_expanded +test_layer_normalization_4d_axis_negative_1_expanded_ver18 test_layer_normalization_4d_axis_negative_2 +test_layer_normalization_4d_axis_negative_2_expanded +test_layer_normalization_4d_axis_negative_2_expanded_ver18 test_layer_normalization_4d_axis_negative_3 +test_layer_normalization_4d_axis_negative_3_expanded +test_layer_normalization_4d_axis_negative_3_expanded_ver18 test_layer_normalization_4d_axis_negative_4 +test_layer_normalization_4d_axis_negative_4_expanded +test_layer_normalization_4d_axis_negative_4_expanded_ver18 test_layer_normalization_default_axis +test_layer_normalization_default_axis_expanded +test_layer_normalization_default_axis_expanded_ver18 test_leakyrelu test_leakyrelu_default test_leakyrelu_default_expanded @@ -450,6 +563,7 @@ test_logsoftmax_large_number_expanded_ver18 test_logsoftmax_negative_axis test_logsoftmax_negative_axis_expanded test_logsoftmax_negative_axis_expanded_ver18 +test_loop11 test_lppool_1d_default test_lppool_2d_default test_lppool_2d_dilations @@ -461,6 +575,9 @@ test_lppool_3d_default test_lrn test_lrn_default test_lstm_batchwise +test_lstm_defaults +test_lstm_with_initial_bias +test_lstm_with_peepholes test_matmul_2d test_matmul_3d test_matmul_4d @@ -598,6 +715,8 @@ test_onehot_with_axis test_onehot_with_negative_axis test_onehot_without_axis test_optional_get_element_tensor +test_optional_has_element_empty_no_input_name_optional_input +test_optional_has_element_empty_no_input_name_tensor_input test_optional_has_element_empty_no_input_optional_input test_optional_has_element_empty_no_input_tensor_input test_or2d @@ -636,10 +755,14 @@ test_qlinearmatmul_3D_uint8_float32 test_quantizelinear test_quantizelinear_axis test_quantizelinear_blocked +test_quantizelinear_e4m3fn +test_quantizelinear_e5m2 test_quantizelinear_int16 test_quantizelinear_uint16 test_range_float_type_positive_delta +test_range_float_type_positive_delta_expanded test_range_int32_type_negative_delta +test_range_int32_type_negative_delta_expanded test_reciprocal test_reciprocal_example test_reduce_l1_default_axes_keepdims_example @@ -772,6 +895,9 @@ test_reduce_sum_square_negative_axes_keepdims_example_expanded test_reduce_sum_square_negative_axes_keepdims_random test_reduce_sum_square_negative_axes_keepdims_random_expanded test_reflect_pad +test_regex_full_match_basic +test_regex_full_match_email_domain +test_regex_full_match_empty test_relu test_relu_expanded_ver18 test_reshape_allowzero_reordered @@ -784,12 +910,52 @@ test_reshape_reordered_all_dims test_reshape_reordered_last_dims test_reshape_zero_and_negative_dim test_reshape_zero_dim +test_resize_downsample_scales_cubic +test_resize_downsample_scales_cubic_A_n0p5_exclude_outside +test_resize_downsample_scales_cubic_align_corners +test_resize_downsample_scales_cubic_antialias +test_resize_downsample_scales_linear +test_resize_downsample_scales_linear_align_corners +test_resize_downsample_scales_linear_antialias +test_resize_downsample_scales_linear_half_pixel_symmetric +test_resize_downsample_scales_nearest +test_resize_downsample_sizes_cubic +test_resize_downsample_sizes_cubic_antialias +test_resize_downsample_sizes_linear_antialias +test_resize_downsample_sizes_linear_pytorch_half_pixel +test_resize_downsample_sizes_nearest +test_resize_downsample_sizes_nearest_not_larger +test_resize_downsample_sizes_nearest_not_smaller +test_resize_tf_crop_and_resize +test_resize_tf_crop_and_resize_axes_2_3 +test_resize_tf_crop_and_resize_axes_3_2 +test_resize_upsample_scales_cubic +test_resize_upsample_scales_cubic_A_n0p5_exclude_outside +test_resize_upsample_scales_cubic_align_corners +test_resize_upsample_scales_cubic_asymmetric +test_resize_upsample_scales_linear +test_resize_upsample_scales_linear_align_corners +test_resize_upsample_scales_linear_half_pixel_symmetric +test_resize_upsample_scales_nearest +test_resize_upsample_scales_nearest_axes_2_3 +test_resize_upsample_scales_nearest_axes_3_2 +test_resize_upsample_sizes_cubic +test_resize_upsample_sizes_nearest +test_resize_upsample_sizes_nearest_axes_2_3 +test_resize_upsample_sizes_nearest_axes_3_2 +test_resize_upsample_sizes_nearest_ceil_half_pixel +test_resize_upsample_sizes_nearest_floor_align_corners +test_resize_upsample_sizes_nearest_not_larger +test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric test_reversesequence_batch test_reversesequence_time +test_rnn_seq_length test_roialign_aligned_false test_roialign_aligned_true test_roialign_mode_max test_round +test_scan9_sum +test_scan_sum test_scatter_elements_with_axis test_scatter_elements_with_duplicate_indices test_scatter_elements_with_negative_indices @@ -895,6 +1061,8 @@ test_sigmoid test_sigmoid_example test_sign test_simple_rnn_batchwise +test_simple_rnn_defaults +test_simple_rnn_with_initial_bias test_sin test_sin_example test_sinh @@ -960,7 +1128,25 @@ test_sqrt test_sqrt_example test_squeeze test_squeeze_negative_axes +test_stft test_stft_with_window +test_string_concat +test_string_concat_broadcasting +test_string_concat_empty_string +test_string_concat_utf8 +test_string_concat_zero_dimensional +test_string_split_basic +test_string_split_consecutive_delimiters +test_string_split_empty_string_delimiter +test_string_split_empty_tensor +test_string_split_maxsplit +test_string_split_no_delimiter +test_strnormalizer_export_monday_casesensintive_lower +test_strnormalizer_export_monday_casesensintive_nochangecase +test_strnormalizer_export_monday_casesensintive_upper +test_strnormalizer_export_monday_empty_output +test_strnormalizer_export_monday_insensintive_upper_twodim +test_strnormalizer_nostopwords_nochangecase test_sub test_sub_bcast test_sub_example