Summary:
Context: https://github.com/pytorch/pytorch/pull/53299#discussion_r587882857
These are the only hand-written parts of this diff:
- the addition to `.github/workflows/lint.yml`
- the file endings changed in these four files (to appease FB-internal land-blocking lints):
- `GLOSSARY.md`
- `aten/src/ATen/core/op_registration/README.md`
- `scripts/README.md`
- `torch/csrc/jit/codegen/fuser/README.md`
The rest was generated by running this command (on macOS):
```
git grep -I -l ' $' -- . ':(exclude)**/contrib/**' ':(exclude)third_party' | xargs gsed -i 's/ *$//'
```
I looked over the auto-generated changes and didn't see anything that looked problematic.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/53406
Test Plan:
This run (after adding the lint but before removing existing trailing spaces) failed:
- https://github.com/pytorch/pytorch/runs/2043032377
This run (on the tip of this PR) succeeded:
- https://github.com/pytorch/pytorch/runs/2043296348
Reviewed By: walterddr, seemethere
Differential Revision: D26856620
Pulled By: samestep
fbshipit-source-id: 3f0de7f7c2e4b0f1c089eac9b5085a58dd7e0d97
Summary:
There are three guards related to mobile build:
* AutoGradMode
* AutoNonVariableTypeMode
* GraphOptimizerEnabledGuard
Today we need set some of these guards before calling libtorch APIs because we customized mobile build to only support inference (for both OSS and most FB use cases) to optimize binary size.
Several changes were made since 1.3 release so there are already inconsistent uses of these guards in the codebase. I did a sweep of all mobile related model loading & forward() call sites, trying to unify the use of these guards:
Full JIT: still set all three guards. More specifically:
* OSS: Fixed a bug of not setting the guard at model load time correctly in Android JNI.
* FB: Not covered by this diff (as we are using mobile interpreter for most internal builds).
Lite JIT (mobile interpreter): only needs AutoNonVariableTypeMode guard. AutoGradMode doesn't seem to be relevant (so removed from a few places) and GraphOptimizerEnabledGuard definitely not relevant (only full JIT has graph optimizer). More specifically:
* OSS: At this point we are not committed to support Lite-JIT. For Android it shares the same code with FB JNI callsites.
* FB:
** JNI callsites: Use the unified LiteJITCallGuard.
** For iOS/C++: manually set AutoNonVariableTypeMode for _load_for_mobile() & forward() callsites.
Ideally we should avoid having to set AutoNonVariableTypeMode for mobile interpreter. It's currently needed for dynamic dispatch + inference-only mobile build (where variable kernels are not registered) - without the guard it will try to run `variable_fallback_kernel` and crash (PR #34038). The proper fix will take some time so using this workaround to unblock selective BUCK build which depends on dynamic dispatch.
PS. The current status (of having to set AutoNonVariableTypeMode) should not block running FL model + mobile interpreter - if all necessary variable kernels are registered then it can call _load_for_mobile()/forward() against the FL model without setting the AutoNonVariableTypeMode guard. It's still inconvenient for JAVA callsites as it's set unconditionally inside JNI methods.
Test Plan: - CI
Reviewed By: xta0
Differential Revision: D20498017
fbshipit-source-id: ba6740f66839a61790873df46e8e66e4e141c728
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/34278
This diff helps check all the ops not supported by lite_interpreter.
Helpful mainly to find all the ops that need to be added instead of adding them
one by one.
Test Plan:
buck run caffe2/binaries:lite_interpreter_model_load --
--model=<bytecode-model-path>
Reviewed By: iseeyuan
Differential Revision: D20266341
fbshipit-source-id: 5a6c7a5bc52f910cea82a72045870da8105ccb87
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/34072
This diff helps check all the ops not supported by lite_interpreter.
Helpful mainly to find all the ops that need to be added instead of adding them
one by one.
Test Plan:
buck run caffe2/binaries:lite_interpreter_model_load --
--model=<bytecode-model-path>
Reviewed By: iseeyuan
Differential Revision: D20194092
fbshipit-source-id: 0d596cd0204308027194af7ed738551d0c32a374
