Comments (2)
justinchuby
commented on May 24, 2024
Is 1.13.1 the pytorch version being used? If so please test with torch>2.0. It would also be helpful to upload the resulting onnx model.
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gramalingam
commented on May 24, 2024
It would also help to create the issue in pytorch repo. I guess it could be an issue in pytorch-to-onnx exporter, or in onnxruntime implementation, or a potential mismatch in the ONNX op spec.
But it is a bit weird, in that it uses only a linear layer and Relu ... both of which must be very well tested by now in all 3 components.
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Related Issues (20)
- Using Pytorch Count of input_names provided during export not matching with session.get_inputs() HOT 1
- ONNX is broken when built with ONNX_USE_LITE_PROTO=OFF (using protobuf-24.4): File already exists in database: onnx/onnx-ml.proto HOT 5
- Schema error trying to create new version of training ops
- ERROR: Could not build wheels for onnx which use PEP 517 and cannot be installed directly HOT 2
- output different between onnx and pytorch HOT 7
- Implement DepthToSpace as a function HOT 2
- Reference implementation of ONNX Reduce sum square is mismatch with ONNX Spec when noop_with_empty_axes == 1 HOT 5
- Clarification of Reshape semantics for attribute 'allowzero' NOT set, zero volume HOT 3
- Change dynamic shape in fixed shape using C++ HOT 1
- The weekly model zoo CI has been failing HOT 12
- Incorrect input names for quantize/dequantize ONNX backend node tests HOT 1
- Fix and test numpy_helper to_array
- How to read onnx and obtain names, imgsz HOT 3
- Model zoo test failures HOT 1
- DequantizeLinear spec clarification: What happens if the subtraction overflows/underflows? HOT 1
- the model for UniqueOp in backend test is not always correct for different input
- A conflict doc abount compatibility between Onnx Version & ML Opset Version HOT 2
- [Shape Inference] Robustness of `ConstantOfShape` operator HOT 2
- Numpy 2.0.0rc2 causes `pytest` on ONNX to fail HOT 2
- How to modify Slice attribute HOT 4
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