Add batch rule for native_dropout_backward
#140140
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/140140
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 7554e87 with merge base 83e36a6 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
guilhermeleobas
added
module: functorch
guilhermeleobas
requested review from
Chillee,
kshitij12345 and
zou3519
as code owners
guilhermeleobas
commented
Nov 11, 2024
| UNARY_POINTWISE_RANDOM_LEADING_FLOAT(normal, float_Tensor); | ||
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| m.impl("native_dropout", native_dropout_batching_rule); // needs special casing because cuda version doesn't call bernoulli | ||
| m.impl("native_dropout_backward", native_dropout_backward_batch_rule); |
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This should be OP_DECOMPOSE and move this to BatchRulesDecompositions.cpp.
zou3519
approved these changes
Nov 11, 2024
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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 |
pobin6
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Dec 5, 2024
Fixes: pytorch#122432 Pull Request resolved: pytorch#140140 Approved by: https://github.com/zou3519
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Stack from ghstack (oldest at bottom):
native_dropout_backward#140140Fixes: #122432
cc @zou3519 @Chillee @samdow @kshitij12345