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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/66554 In native_functions.yaml, the schemas for batch_norm and instance_norm are incorrect: the inputs `running_mean` and `running_var` are mutated, but are not marked as such in the function schema. Since `(a!)?` annotations are currently not working (see #65760), this instead adds a special case to `alias_anaysis.cpp`. If the value of `training` or `use_input_stats` is known to be `false`, then `alias_analysis` will mark the input as _not_ being written to. Test Plan: Removed the `skip` annotation on the following test, and added a special exception in `check_alias_annotations`: ``` python test/test_ops.py -k test_variant_consistency_jit_nn_functional_batch_norm ``` Also: ``` ./build/bin/test_jit --gtest_filter="*BatchAndInstanceNormFixture*" ``` Imported from OSS Reviewed By: eellison Differential Revision: D31612339 fbshipit-source-id: 12ca61b782b9e41e06883ba080a276209dc435bb |
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| .. | ||
| api | ||
| c10d | ||
| common | ||
| dist_autograd | ||
| jit | ||
| lazy | ||
| lite_interpreter_runtime | ||
| rpc | ||
| tensorexpr | ||
| __init__.py | ||