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Previous to this PR, in torchlib TracedONNXFunction, the inputs could be python constants even if the annotation sets to TensorTypes.

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pytorch-bot bot commented Oct 23, 2024

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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/138770

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@pytorch-bot pytorch-bot bot added the release notes: onnx torch.onnx related changes that should show up in the release notes label Oct 23, 2024
@mikaylagawarecki mikaylagawarecki added the triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module label Oct 30, 2024
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@justinchuby I totally forgot the status of this. Are we still doing this?

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Sure! Please feel free to merge

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One sec

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I am not sure if _process_python_sequences is safe to do in the trace level? I suppose we need to preserve some python lists?

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Maybe just do the constants for now? What do you think?

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I will test more on this.

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Maybe just do the constants for now? What do you think?

Agree. python list related properties are leveraged heavily in trace_only function. Also, _process_python_constant is sufficient to solve the symint (fx.Node) and int issue.

@titaiwangms titaiwangms added module: onnx Related to torch.onnx topic: improvements topic category labels Nov 14, 2024
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@pytorchbot merge

@pytorch-bot pytorch-bot bot added the ciflow/trunk Trigger trunk jobs on your pull request label Nov 14, 2024
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pobin6 pushed a commit to pobin6/pytorch that referenced this pull request Dec 5, 2024
…rs (pytorch#138770)

Previous to this PR, in torchlib TracedONNXFunction, the inputs could be python constants even if the annotation sets to TensorTypes.
Pull Request resolved: pytorch#138770
Approved by: https://github.com/justinchuby
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