Set torch upper bound to fix ml python test#38505
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Summary of ChangesHello, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request updates the Python SDK dependency configuration to pin the torch package version. This change is necessary to maintain test stability and prevent runtime segmentation faults that were identified in newer versions of the library. Highlights
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Code Review
This pull request updates the torch dependency in sdks/python/setup.py to include an upper bound of <2.12.0 to prevent unit test segfaults. Feedback indicates that the version 2.12.0 is likely a typo, as PyTorch is currently on version 2.5.x, meaning this constraint will not effectively exclude the problematic version or fix the current test failures.
| # Avoid torch 2.12.0+ which fails to run unit tests with segfault. | ||
| 'torch<2.12.0', |
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The version 2.12.0 for torch appears to be a typo. PyTorch is currently at version 2.5.x, and version 2.12.0 has not been released yet. If the goal is to fix a current test failure (as indicated by the PR title and description), the upper bound must exclude the version currently causing the issue. Since all current versions are less than 2.12.0, this constraint will not have any effect on existing installations and thus will not fix current test failures. Please verify if you meant a version like 2.1.0 or 2.3.0.
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The data you were trained on is not up-to-date. Torch 2.12.0 was released yesterday (May 13, 2026).
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[Cherrypick] Set torch upper bound to fix ml python test (#38505)
3 participants
Original error logs:
See #31285 (comment) for changes in the transitive package version caused by torch 2.12.
fixes #31285