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Fix 0-sized views of tensors in cudagraphs #109055
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/109055
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (1 Unrelated Failure)As of commit fbbe81e with merge base 8ff0036 (): UNSTABLE - The following job failed but was likely due to flakiness present on trunk and has been marked as unstable:
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ghstack-source-id: 1142b1fad12da951b08e32f68f8f1d0a67c457d8 Pull Request resolved: #109055
Fixes internal model. If a tensor with real storage is viewed by a 0-dim tensor it is still kept alive and needs to be kept track of in our storage tracking. [ghstack-poisoned]
ghstack-source-id: a513b472682307211fdee4c20246b0e300308ac1 Pull Request resolved: #109055
@pytorchbot merge |
Merge failedReason: This PR needs a If not, please add the To add a label, you can comment to pytorchbot, for example For more information, see Details for Dev Infra teamRaised by workflow job |
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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 |
Merge failedReason: 11 jobs have failed, first few of them are: pull / linux-focal-py3.8-clang10 / test (dynamo, 1, 2, linux.2xlarge, unstable), pull / linux-focal-py3.8-clang10 / test (dynamo, 2, 2, linux.2xlarge, unstable), pull / linux-focal-py3.11-clang10 / test (dynamo, 1, 2, linux.2xlarge, unstable), pull / linux-focal-py3.11-clang10 / test (dynamo, 2, 2, linux.2xlarge, unstable), pull / linux-focal-cuda12.1-py3.10-gcc9-sm86 / test (default, 1, 5, linux.g5.4xlarge.nvidia.gpu, unstable) Details for Dev Infra teamRaised by workflow job |
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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 |
Stack from ghstack (oldest at bottom):
Fixes internal model. If a tensor with real storage is viewed by a 0-dim tensor it is still kept alive and needs to be kept track of in our storage tracking.
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