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Avoid circular imports in tracing_state_functions#150325

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@justinchubyjustinchuby commentedMar 31, 2025•
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tracing_state_functions references some torch functions from submodules liketorch.onnx.is_in_onnx_export that could trigger module initialization & circular imports. I turned the mapping into a function so that the dictionary is not initialized at torch import.

(discovered in#149646)

cc@voznesenskym@penguinwu@EikanWang@jgong5@Guobing-Chen@XiaobingSuper@zhuhaozhe@blzheng@wenzhe-nrv@jiayisunx@chenyang78@kadeng@chauhang@amjames

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pytorch-botbot commentedMar 31, 2025•
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🔗 Helpful Links

🧪 See artifacts and rendered test results athud.pytorch.org/pr/150325

Note: Links to docs will display an error until the docs builds have been completed.

❌ 8 New Failures, 2 Pending, 1 Unrelated Failure

As of commitecd03fd with merge base4447352 (image):

NEW FAILURES - The following jobs have failed:

FLAKY - The following job failed but was likely due to flakiness present on trunk:

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Pull Request Overview

This pull request aims to avoid circular imports in tracing_state_functions by converting a statically defined mapping into a function.

  • The mapping for tracing state functions is now returned through a function.
  • The decorator now calls the function to unpack the mapping keys dynamically.
Comments suppressed due to low confidence (1)

torch/_dynamo/variables/torch.py:171

  • [nitpick] Consider renaming 'tracing_state_functions' to 'get_tracing_state_functions' to more clearly indicate that it returns a mapping. Optionally, if the mapping is static, memoizing the result could avoid repeated instantiation.
def tracing_state_functions():

@justinchubyjustinchuby changed the titleAvoid circular imports in tracing_state_functionsRemove torch.onnx.is_in_onnx_export from tracing_state_functionsMar 31, 2025
@justinchubyjustinchuby changed the titleRemove torch.onnx.is_in_onnx_export from tracing_state_functionsRemovetorch.onnx.is_in_onnx_export fromtracing_state_functionsMar 31, 2025
@justinchubyjustinchuby changed the titleRemovetorch.onnx.is_in_onnx_export fromtracing_state_functionsAvoid circular imports in tracing_state_functionsMar 31, 2025
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@pytorchbot rebase

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@pytorchbot started a rebase job ontorefs/remotes/origin/viable/strict. Check the current statushere

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Successfully rebasedjustinchu/tracing-funcs ontorefs/remotes/origin/viable/strict, please pull locally before adding more changes (for example, viagit checkout justinchu/tracing-funcs && git pull --rebase)

@zou3519zou3519 added the triagedThis issue has been looked at a team member, and triaged and prioritized into an appropriate module labelApr 2, 2025
torch.compiler.is_exporting:True,
torch.nn.modules.activation._is_make_fx_tracing:False,
}
deftracing_state_functions():
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Can you toss an lru_cache(None) on this?

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Done, please take a look

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Copilot reviewed 1 out of 1 changed files in this pull request and generated 1 comment.

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@pytorchbot rebase

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@pytorchbot started a rebase job ontorefs/remotes/origin/viable/strict. Check the current statushere

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Successfully rebasedjustinchu/tracing-funcs ontorefs/remotes/origin/viable/strict, please pull locally before adding more changes (for example, viagit checkout justinchu/tracing-funcs && git pull --rebase)

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@pytorchbot merge -i

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@pytorch-botpytorch-botbot added the ciflow/trunkTrigger trunk jobs on your pull request labelApr 9, 2025
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Merge started

Your change will be merged while ignoring the following 7 checks:inductor / linux-jammy-cpu-py3.9-gcc11-inductor / test (cpu_inductor_torchbench, 1, 2, linux.8xlarge.amx),inductor / linux-jammy-cpu-py3.9-gcc11-inductor / test (cpu_inductor_torchbench, 2, 2, linux.8xlarge.amx),inductor / linux-jammy-cpu-py3.9-gcc11-inductor / test (dynamic_cpu_inductor_torchbench, 1, 2, linux.8xlarge.amx),inductor / linux-jammy-cpu-py3.9-gcc11-inductor / test (dynamic_cpu_inductor_torchbench, 2, 2, linux.8xlarge.amx),inductor / linux-jammy-cpu-py3.9-gcc11-inductor / test (inductor_torchbench_cpu_smoketest_perf, 1, 1, linux.24xl.spr-metal),inductor / cuda12.6-py3.10-gcc9-sm86 / test (inductor_torchbench, 1, 2, linux.g5.4xlarge.nvidia.gpu),inductor / cuda12.6-py3.10-gcc9-sm86 / test (inductor_torchbench, 2, 2, linux.g5.4xlarge.nvidia.gpu)

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Merge failed

Reason: 1 jobs have failed, first few of them are:linux-binary-manywheel / manywheel-py3_9-cuda12_6-test / test

Details for Dev Infra teamRaised byworkflow job

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@pytorchbot merge -f "unrelated failures in cuda build"

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Merge started

Your change will be merged immediately since you used the force (-f) flag,bypassing any CI checks (ETA: 1-5 minutes). Please use-f as last resort and instead consider-i/--ignore-current to continue the merge ignoring current failures. This will allow currently pending tests to finish and report signal before the merge.

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timocafe pushed a commit to timocafe/pytorch that referenced this pull requestApr 16, 2025
tracing_state_functions references some torch functions from submodules like `torch.onnx.is_in_onnx_export` that could trigger module initialization & circular imports. I turned the mapping into a function so that the dictionary is not initialized at torch import.(discovered inpytorch#149646)Pull Requestresolved:pytorch#150325Approved by:https://github.com/zou3519
amathewc pushed a commit to amathewc/pytorch that referenced this pull requestApr 17, 2025
tracing_state_functions references some torch functions from submodules like `torch.onnx.is_in_onnx_export` that could trigger module initialization & circular imports. I turned the mapping into a function so that the dictionary is not initialized at torch import.(discovered inpytorch#149646)Pull Requestresolved:pytorch#150325Approved by:https://github.com/zou3519
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