【Fix PIR Unittest No.77,467】Fix test cast in PIR mode

paddle/fluid/pir/dialect/op_generator/ops_api_gen.py

@@ -188,7 +188,6 @@
     'sparse_momentum',
     'tdm_sampler',
     'soft_relu',
-    'uniform_random_batch_size_like',
     'match_matrix_tensor',
     'c_reduce_max',
     'c_reduce_max_',

python/paddle/tensor/random.py

@@ -463,6 +463,22 @@ def uniform_random_batch_size_like(
             >>> print(out_2.shape)
             [2, 3]
     """
+    if in_dynamic_or_pir_mode():
+        dtype = convert_np_dtype_to_dtype_(dtype)
+        return _C_ops.uniform_random_batch_size_like(
+            input,
+            shape,
+            input_dim_idx,
+            output_dim_idx,
+            min,
+            max,
+            seed,
+            0,
+            0,
+            1.0,
+            dtype,
+        )
+
     check_variable_and_dtype(
         input,
         'Input',

test/deprecated/legacy_test/CMakeLists.txt

@@ -735,6 +735,7 @@ set_tests_properties(test_cumprod_op PROPERTIES TIMEOUT 300)
 set_tests_properties(test_split_program PROPERTIES TIMEOUT 120)
 set_tests_properties(test_graph_send_ue_recv_op PROPERTIES TIMEOUT 60)
 set_tests_properties(test_graph_send_uv_op PROPERTIES TIMEOUT 60)
+set_tests_properties(test_uniform_random_op_deprecated PROPERTIES TIMEOUT 60)
 
 set_tests_properties(test_pretrained_model PROPERTIES TIMEOUT 120)
 set_tests_properties(test_model PROPERTIES TIMEOUT 300)

test/deprecated/legacy_test/test_uniform_random_op_deprecated.py

@@ -0,0 +1,67 @@
+#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import unittest
+
+import numpy as np
+from test_attribute_var import UnittestBase
+
+import paddle
+from paddle.base import Program, program_guard
+
+
+class TestUniformMinMaxTensor(UnittestBase):
+    def init_info(self):
+        self.shapes = [[2, 3, 4]]
+        self.save_path = os.path.join(self.temp_dir.name, self.path_prefix())
+
+    def test_static(self):
+        main_prog = Program()
+        startup_prog = Program()
+        with program_guard(main_prog, startup_prog):
+            fc = paddle.nn.Linear(4, 10)
+            x = paddle.randn([2, 3, 4])
+            x.stop_gradient = False
+            feat = fc(x)  # [2,3,10]
+            min_v = paddle.to_tensor([0.1])
+            max_v = paddle.to_tensor([0.9])
+            y = paddle.uniform([2, 3, 10], min=min_v, max=max_v)
+            z = paddle.uniform([2, 3, 10], min=min_v, max=max_v)
+
+            out = feat + y + z
+
+            sgd = paddle.optimizer.SGD()
+            sgd.minimize(paddle.mean(out))
+            self.assertTrue(self.var_prefix() in str(main_prog))
+
+            exe = paddle.static.Executor()
+            exe.run(startup_prog)
+            res = exe.run(fetch_list=[out])
+            np.testing.assert_array_equal(res[0].shape, [2, 3, 10])
+
+            paddle.static.save_inference_model(self.save_path, [x], [out], exe)
+            # Test for Inference Predictor
+            infer_out = self.infer_prog()
+            np.testing.assert_array_equal(res[0].shape, [2, 3, 10])
+
+    def path_prefix(self):
+        return 'uniform_random'
+
+    def var_prefix(self):
+        return "Var["
+
+
+if __name__ == "__main__":
+    unittest.main()

test/deprecated/legacy_test/test_uniform_random_op.py → test/legacy_test/test_uniform_random_op.py

@@ -12,13 +12,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import os
 import unittest
 
 import numpy as np
 from op import Operator
 from op_test import OpTest, convert_uint16_to_float
-from test_attribute_var import UnittestBase
 
 import paddle
 from paddle import base
@@ -733,46 +731,5 @@ def test_fixed_random_number(self):
         paddle.enable_static()
 
 
-class TestUniformMinMaxTensor(UnittestBase):
-    def init_info(self):
-        self.shapes = [[2, 3, 4]]
-        self.save_path = os.path.join(self.temp_dir.name, self.path_prefix())
-
-    def test_static(self):
-        main_prog = Program()
-        startup_prog = Program()
-        with program_guard(main_prog, startup_prog):
-            fc = paddle.nn.Linear(4, 10)
-            x = paddle.randn([2, 3, 4])
-            x.stop_gradient = False
-            feat = fc(x)  # [2,3,10]
-            min_v = paddle.to_tensor([0.1])
-            max_v = paddle.to_tensor([0.9])
-            y = paddle.uniform([2, 3, 10], min=min_v, max=max_v)
-            z = paddle.uniform([2, 3, 10], min=min_v, max=max_v)
-
-            out = feat + y + z
-
-            sgd = paddle.optimizer.SGD()
-            sgd.minimize(paddle.mean(out))
-            self.assertTrue(self.var_prefix() in str(main_prog))
-
-            exe = paddle.static.Executor()
-            exe.run(startup_prog)
-            res = exe.run(fetch_list=[out])
-            np.testing.assert_array_equal(res[0].shape, [2, 3, 10])
-
-            paddle.static.save_inference_model(self.save_path, [x], [out], exe)
-            # Test for Inference Predictor
-            infer_out = self.infer_prog()
-            np.testing.assert_array_equal(res[0].shape, [2, 3, 10])
-
-    def path_prefix(self):
-        return 'uniform_random'
-
-    def var_prefix(self):
-        return "Var["
-
-
 if __name__ == "__main__":
     unittest.main()