This PR applies clang-tidy readability checks to jit sources and all headers in the code base.
`readability-redundant-inline-specifier` is suppressed because it incurs too many changes. `readability-redundant-inline-specifier` is used to detect redundant inline specifiers on function and variable declarations. There are many in-class method definitions that are marked inline.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/164652
Approved by: https://github.com/Skylion007
This PR applies clang-tidy readability checks to jit sources and all headers in the code base.
`readability-redundant-inline-specifier` is suppressed because it incurs too many changes. `readability-redundant-inline-specifier` is used to detect redundant inline specifiers on function and variable declarations. There are many in-class method definitions that are marked inline.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/164652
Approved by: https://github.com/Skylion007
Summary:
Previous our implementation for RecordFunction injects Aten into
codegen, which is breaking the ABI contract for AOTInductor.
C10::IValue is aded to call the full record function. The extension of
more profiling info will come in later PRs.
Test Plan:
Included in commit.
Reviewers:
Subscribers:
Tasks:
Tags:
Differential Revision: [D79622071](https://our.internmc.facebook.com/intern/diff/D79622071)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/159842
Approved by: https://github.com/desertfire
Summary:
We used RAIIAtenTensorHandle for ConstantMap, where RAIIAtenTensorHandle
is a unique_ptr, indicating that all memory handling is by the
AOTInductor internally.
In this PR, we introduce ConstantAtenTensorHandle which replaces
RAIIATenTensorHandle. This class holds a raw AtenTensorHandle, and also
owns a RAIIAtenTensorHandle if user decides to delegate memory
management to AOTInductor.
This is a prerequisite for user managed buffer, this PR, however only
introduces this class and make sure it works with existing AOTInductor
and has the default behavior identical as using RAIIAtenTensorHandle.
Test Plan:
Existing tests. No change should be introduced within this PR.
Reviewers:
Subscribers:
Tasks:
Tags:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/150275
Approved by: https://github.com/chenyang78, https://github.com/desertfire
## Description
Fixes https://github.com/pytorch/pytorch/issues/114450. This PR builds upon the work from @imzhuhl done in https://github.com/pytorch/pytorch/pull/114451.
This PR requires https://github.com/pytorch/pytorch/pull/122472 to land firstly.
We leverage the serialization and deserialization API from oneDNN v3.4.1 to save the opaque MKLDNN tensor during the compilation and restore the opaque tensor when loading the compiled .so.
ideep version is updated so that we won't break any pipeline even if third_party/ideep is not updated at the same time.
### Test plan:
```sh
python -u test/inductor/test_aot_inductor.py -k AOTInductorTestNonABICompatibleCpu.test_freezing_non_abi_compatible_cpu
python -u test/inductor/test_aot_inductor.py -k AOTInductorTestNonABICompatibleCpu.test_conv_freezing_non_abi_compatible_cpu
python -u test/inductor/test_aot_inductor.py -k AOTInductorTestNonABICompatibleCpu.test_deconv_freezing_non_abi_compatible_cpu
python -u test/inductor/test_aot_inductor.py -k AOTInductorTestNonABICompatibleCpu.test_linear_freezing_non_abi_compatible_cpu
```
### TODOs in follow-up PRs
1. We found that using `AOTI_TORCH_CHECK` will cause performance drop on several models (`DistillGPT2`, `MBartForConditionalGeneration`, `T5ForConditionalGeneration`, `T5Small`) compared with JIT Inductor which uses `TORCH_CHECK`. This may need further discussion how to address (`AOTI_TORCH_CHECK` is introduced in
https://github.com/pytorch/pytorch/pull/119220).
2. Freezing in non-ABI compatible mode will work with the support in this PR. While for ABI compatible mode, we need to firstly address this issue: `AssertionError: None, i.e. optional output is not supported`.
6c4f43f826/torch/_inductor/codegen/cpp_wrapper_cpu.py (L2023-L2024)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/124350
Approved by: https://github.com/jgong5, https://github.com/desertfire
## Description
Fixes https://github.com/pytorch/pytorch/issues/114450. This PR builds upon the work from @imzhuhl done in https://github.com/pytorch/pytorch/pull/114451.
This PR requires https://github.com/pytorch/pytorch/pull/122472 to land firstly.
We leverage the serialization and deserialization API from oneDNN v3.4.1 to save the opaque MKLDNN tensor during the compilation and restore the opaque tensor when loading the compiled .so.
ideep version is updated so that we won't break any pipeline even if third_party/ideep is not updated at the same time.
### Test plan:
```sh
python -u test/inductor/test_aot_inductor.py -k AOTInductorTestNonABICompatibleCpu.test_freezing_non_abi_compatible_cpu
python -u test/inductor/test_aot_inductor.py -k AOTInductorTestNonABICompatibleCpu.test_conv_freezing_non_abi_compatible_cpu
python -u test/inductor/test_aot_inductor.py -k AOTInductorTestNonABICompatibleCpu.test_deconv_freezing_non_abi_compatible_cpu
python -u test/inductor/test_aot_inductor.py -k AOTInductorTestNonABICompatibleCpu.test_linear_freezing_non_abi_compatible_cpu
```
### TODOs in follow-up PRs
1. We found that using `AOTI_TORCH_CHECK` will cause performance drop on several models (`DistillGPT2`, `MBartForConditionalGeneration`, `T5ForConditionalGeneration`, `T5Small`) compared with JIT Inductor which uses `TORCH_CHECK`. This may need further discussion how to address (`AOTI_TORCH_CHECK` is introduced in
https://github.com/pytorch/pytorch/pull/119220).
2. Freezing in non-ABI compatible mode will work with the support in this PR. While for ABI compatible mode, we need to firstly address this issue: `AssertionError: None, i.e. optional output is not supported`.
6c4f43f826/torch/_inductor/codegen/cpp_wrapper_cpu.py (L2023-L2024)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/124350
Approved by: https://github.com/jgong5, https://github.com/desertfire
