[ONNX] Support symbolic arguments in onnx exporter #157734
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titaiwangms
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/157734
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit ce23365 with merge base 2e14069 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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@pytorchbot rebase |
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@pytorchbot started a rebase job onto refs/remotes/origin/viable/strict. Check the current status here |
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justinchuby
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| if isinstance(spec.arg, graph_signature.ConstantArgument): | ||
| # If dynamic is set to a constant input, it becomes a | ||
| # symbolic argument, which is not a tensor. | ||
| if isinstance( |
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Should we include them?
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They don't have tensor_meta though. Is there other info we might want from them?
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Maybe just say they are symbolic?
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As a string? Currently, io_spec supports onlt tensor_meta.
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I think this is only for printing iirc? If so it's fine as long as we are able to display them in the report.
justinchuby
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titaiwangms
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@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
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Hi @titaiwangms looks like this is broke amazon linux 2023 test: https://github.com/pytorch/test-infra/actions/runs/16525830777/job/46738788918 when numpy not installed: |
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@pytorchmergebot revert -c nosignal -m "Broke test on amazon linux 2023 when numpy not installed" |
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@pytorchbot successfully started a revert job. Check the current status here. |
Reverting PR 157734 failedReason: Command Details for Dev Infra teamRaised by workflow job |
justinchuby
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Jul 25, 2025
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| def _to_ort_value(tensor: torch.Tensor) -> ort.OrtValue: | ||
| def _to_ort_value(input: torch.Tensor | int | float | str | bool) -> ort.OrtValue: |
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@titaiwangms we can hide the numpy import here
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Thanks for the help.
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One should not expect numpy to be there during onnx import Forward fix for : #157734 Added regression test to `test_without_numpy` function Test plan: Run `python -c "import sys;sys.path.insert(0, 'fake_numpy');import torch; import torch.onnx"` with/without this fix Pull Request resolved: #159177 Approved by: https://github.com/atalman, https://github.com/justinchuby, https://github.com/titaiwangms, https://github.com/cyyever, https://github.com/Skylion007, https://github.com/andrewboldi
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One should not expect numpy to be there during onnx import Forward fix for : #157734 Added regression test to `test_without_numpy` function Test plan: Run `python -c "import sys;sys.path.insert(0, 'fake_numpy');import torch; import torch.onnx"` with/without this fix Pull Request resolved: #159177 Approved by: https://github.com/atalman, https://github.com/justinchuby, https://github.com/titaiwangms, https://github.com/cyyever, https://github.com/Skylion007, https://github.com/andrewboldi
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Previous to this PR, torch.onnx.export(..., dynamo=True, veriy=True, report=True) does not support symbolic arguments. Such examples are like follwing:
symbolic arguments are like constant arguments that they don't have tensor_meta wither. Besides, torch.export.export supports model inputs having constants, which is different from the legacy issue: #99534 where we tried to get the FX directly from dynamo export. Thus,
_remove_non_tensoris deleted from args processing.NOTE: If the ConstantArugment shows up in exported_program, it was kept to align the length of inputs to nn.Module, but it's irrelevant to the model graph, hwich is why in ONNX model the input is omitted.
The test
test_constant_argument_user_input_is_omitted_in_onnx_graphneeds #157719