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The AMP inserts `_autocast_to_reduced_precision` and `_autocast_to_full_precision` automatically. The aten implementation provides a fast path to bypass the conversion if the tensor data type has been the reduced/full precision. But NNC always does the conversion which could bring >5% E2E performance regression. This PR is to address the performance issue like aten. We will not pull `_autocast_to_reduced_precision` and `_autocast_to_full_precision` into NNC fusion group and fallback to aten to trigger its fast path if the tensor data type has been the reduced/full precision. Pull Request resolved: https://github.com/pytorch/pytorch/pull/85140 Approved by: https://github.com/frank-wei |
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| .. | ||
| api | ||
| c10d | ||
| common | ||
| dist_autograd | ||
| jit | ||
| lazy | ||
| lite_interpreter_runtime | ||
| monitor | ||
| profiler | ||
| rpc | ||
| tensorexpr | ||
| __init__.py | ||