Use TORCH_SYM_CHECK in nll_loss_nd_symint for symbolic size comparison to avoid DDE #175956
Use TORCH_SYM_CHECK in nll_loss_nd_symint for symbolic size comparison to avoid DDE #175956laithsakka wants to merge 11 commits intogh/laithsakka/412/basefrom
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/175956
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (2 Unrelated Failures)As of commit c1ab3be with merge base 07efc60 ( BROKEN TRUNK - The following job failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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This PR needs a
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torch/_decomp/decompositions.py
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| raise AssertionError( | ||
| f"size mismatch (got input: {self.shape}, target: {target.shape})" | ||
| ) | ||
| torch._check( |
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Double check, we might have Python bindings to torch._check_sym or something? Even if it's not documented well? Or at least torch._check_assert
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torch._check shall behave like TORCH_SYM_CHECK
the issue was sym_or does not short circuit addressed, so i get access out of bounds.
addressed
…ze comparison to avoid DDE " encountered while running python benchmarks/dynamo/huggingface.py --only AllenaiLongformerBase --backend inductor --performance --inference --unbacked-batch-only [ghstack-poisoned]
…ze comparison to avoid DDE " encountered while running python benchmarks/dynamo/huggingface.py --only AllenaiLongformerBase --backend inductor --performance --inference --unbacked-batch-only [ghstack-poisoned]
…ze comparison to avoid DDE " encountered while running python benchmarks/dynamo/huggingface.py --only AllenaiLongformerBase --backend inductor --performance --inference --unbacked-batch-only [ghstack-poisoned]
…ze comparison to avoid DDE " encountered while running python benchmarks/dynamo/huggingface.py --only AllenaiLongformerBase --backend inductor --performance --inference --unbacked-batch-only [ghstack-poisoned]
…ze comparison to avoid DDE " encountered while running python benchmarks/dynamo/huggingface.py --only AllenaiLongformerBase --backend inductor --performance --inference --unbacked-batch-only [ghstack-poisoned]
…ze comparison to avoid DDE " encountered while running python benchmarks/dynamo/huggingface.py --only AllenaiLongformerBase --backend inductor --performance --inference --unbacked-batch-only [ghstack-poisoned]
i messed up the rebase it was clean |
…ze comparison to avoid DDE " encountered while running python benchmarks/dynamo/huggingface.py --only AllenaiLongformerBase --backend inductor --performance --inference --unbacked-batch-only [ghstack-poisoned]
…ze comparison to avoid DDE " encountered while running python benchmarks/dynamo/huggingface.py --only AllenaiLongformerBase --backend inductor --performance --inference --unbacked-batch-only [ghstack-poisoned]
…ze comparison to avoid DDE " encountered while running python benchmarks/dynamo/huggingface.py --only AllenaiLongformerBase --backend inductor --performance --inference --unbacked-batch-only [ghstack-poisoned]
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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 |
Adds min and max parameters to mark_unbacked() to allow specifying value range constraints for unbacked dimensions. When an unbacked symbol is created with min/max bounds, torch._check() calls are emitted to establish the constraints (e.g., torch._check(u0 >= 1)). Pull Request resolved: #176313 Approved by: https://github.com/Lucaskabela, https://github.com/mlazos ghstack dependencies: #175946, #175956
ghstack-source-id: d1f66c0 Pull Request resolved: pytorch/pytorch#175956
ghstack-source-id: 5491787 Pull Request resolved: pytorch/pytorch#175956
Stack from ghstack (oldest at bottom):
encountered while running
python benchmarks/dynamo/huggingface.py --only AllenaiLongformerBase --backend inductor --performance --inference --unbacked-batch-only