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ONNX dynamic sized model export with torch.onnx.dynamo_export fails when torch.nn.functional.interpolate is used #124884
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module: onnx
Related to torch.onnx
triaged
This issue has been looked at a team member, and triaged and prioritized into an appropriate module
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malfet
added
module: onnx
Related to torch.onnx
triaged
This issue has been looked at a team member, and triaged and prioritized into an appropriate module
labels
Apr 24, 2024
Has anyone from the Onnx team been able to take a look at this? |
Facing same issue here. I have to switch to Pytorch 2.0.1 to make the code work. |
I have a similar issue. torch.onnx.dynamo_export() succeeded. However, onnxrumtime inference failed.
The error:
|
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Labels
module: onnx
Related to torch.onnx
triaged
This issue has been looked at a team member, and triaged and prioritized into an appropriate module
馃悰 Describe the bug
I'm trying to export a model from pytorch to onnx that needs to support dynamic input/output sizing at runtime. The model uses an interpolate step to resize features at a few points in the model. However, when
dynamic_shapes
option is set toTrue
, this results in a very long error that seems to indicate the Onnx export fails at the interpolate step. Here's a short example that declares an extremely simple model, verifies it will run a forward pass, but then fails on export.The error printout is quite long, but the most informative part is the following (Full error printout at end):
I've tried various
scale_factor
sizes, as well as different interpolation modes. However, they all seem to cause a similar export error. However, when I disabledynamic_shapes
in the export options, they work.Is there hope to get the interpolate operation supported for dynamic export?
Full error printout:
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