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fix default partitioner: save sizes instead of tensor for backward when possible #91012
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…en possible [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/91012
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit dd9173c: This comment was automatically generated by Dr. CI and updates every 15 minutes. |
| for user in backward_usages: | ||
| saved_sym_nodes.append(user) | ||
| else: | ||
| saved_values.append(node) |
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ezyang
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Yeah OK, seems fine lol
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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 |
This should fix hf_Longformer, AllenaiLongformerBase, and tacotron2 with dynamic shapes. Example repro:
used to fail with:
The problem is that:
(1) when we have a tensor from the forward, whose sizes are needed the backward, we were saving the actual tensor for backward, and directly grabbing the sizes off of it inside of the backward graph (bad for perf)
(2) If that tensor happens to be a graph input that gets mutated, we end up with the above error. Autograd yells at you if you try to save a tensor for backward, and later mutate it.
I confirmed that this problem doesn't happen for the min cut partitioner.
Stack from ghstack (oldest at bottom):