Pass backend-related ctx to TorchDynamo Optimize Context #201
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jansel
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May 4, 2022
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Fixes a part of pytorch/pytorch#93751 |
davidberard98
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Summary: Previously not added to TARGETS build file, so trying to run internally would fail when `--dynamo` is added to torchbench command Also removed aot_autograd_speedup_strategy to reflect changes in pytorch/torchdynamo#201 (i.e. use `--torchdynamo aot_nvfuser` instead) Differential Revision: D38445665 fbshipit-source-id: 4385902594ff79a5fe2cf2f3366961fcd552befc
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Summary: Pull Request resolved: #1091 Previously not added to TARGETS build file, so trying to run internally would fail when `--dynamo` is added to torchbench command Also removed aot_autograd_speedup_strategy to reflect changes in pytorch/torchdynamo#201 (i.e. use `--torchdynamo aot_nvfuser` instead) Reviewed By: xuzhao9 Differential Revision: D38445665 fbshipit-source-id: 013bdf5603da6e211936f354a1fccc5dccea1103
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Background - For
aot_autograd_speedup_strategy, the user can assume thatnvfuseris turned on by default. But, for now, we have to wrap the model call inwith torch.jit.fuser("fuser2")separately.This PR extends Dynamo OptimizationCtx to accept extra ctx from the backend, and directly call
__enter__and__exit__.@Chillee @jansel