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The attached DLRM model uses ONNX loop operators which have only the trip count and condition inputs but no initial values for the loop-carried dependencies. This results in onnx2trt aborting as follows when it hits an empty std::vector:
$ onnx2trt -o dlrm_s_pytorch.trt dlrm_s_pytorch.onnx
----------------------------------------------------------------
Input filename: dlrm_s_pytorch.onnx
ONNX IR version: 0.0.6
Opset version: 11
Producer name: pytorch
Producer version: 1.8
Domain:
Model version: 0
Doc string:
----------------------------------------------------------------
Parsing model
[2020-10-15 05:44:40 WARNING] [TRT]/local/tensorRT/onnx-tensorrt/onnx2trt_utils.cpp:220: Your ONNX model has been generated with INT64 weights, while TensorRT does not natively support INT64. Attempting to cast down to INT32.
[2020-10-15 05:44:40 WARNING] [TRT]/local/tensorRT/onnx-tensorrt/onnx2trt_utils.cpp:246: One or more weights outside the range of INT32 was clamped
terminate called after throwing an instance of 'std::out_of_range'
what(): vector::_M_range_check: __n (which is 0) >= this->size() (which is 0)
Aborted (core dumped)
This occurs when there are no initial values and an empty stateVars vector is accessed at line 1730 below:
I can't upload the version with embedded tensors since it is too large so I'm attaching the version with external tensors. #542 needs to be resolved or worked around to hit this issue when using external tensors.
The attached DLRM model uses ONNX loop operators which have only the trip count and condition inputs but no initial values for the loop-carried dependencies. This results in onnx2trt aborting as follows when it hits an empty std::vector:
This occurs when there are no initial values and an empty stateVars vector is accessed at line 1730 below:
onnx-tensorrt/builtin_op_importers.cpp
Lines 1722 to 1730 in a3a4e38
I can't upload the version with embedded tensors since it is too large so I'm attaching the version with external tensors. #542 needs to be resolved or worked around to hit this issue when using external tensors.
dlrm-external-tensors.zip
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