This updates ruff to 0.285 which is faster, better, and have fixes a bunch of false negatives with regards to fstrings.
I also enabled RUF017 which looks for accidental quadratic list summation. Luckily, seems like there are no instances of it in our codebase, so enabling it so that it stays like that. :)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/107519
Approved by: https://github.com/ezyang
- BatchLinearAlgebraLib.cpp is now split into one additional file
- BatchLinearAlgebraLib.cpp uses only cusolver APIs
- BatchLinearAlgebraLibBlas.cpp uses only cublas APIs
- hipify operates at the file level and cannot mix cusolver and cublas APIs within the same file
- cmake changes to link against hipblas instead of rocblas
- hipify mappings changes to map cublas -> hipblas instead of rocblas
Pull Request resolved: https://github.com/pytorch/pytorch/pull/105881
Approved by: https://github.com/albanD
This PR fixes the circular issue during hipification process by introducing current_state to track whether a file is processed for hipification. (Iterative DFS)
The issue arises when two header files try to include themselves, which leads to a circular recursion or an infinite loop.
Fixes the related issues such as :
https://github.com/pytorch/pytorch/issues/93827https://github.com/ROCmSoftwarePlatform/hipify_torch/issues/39
Error log:
```
File "/opt/conda/lib/python3.8/posixpath.py", line 471, in relpath
start_list = [x for x in abspath(start).split(sep) if x]
File "/opt/conda/lib/python3.8/posixpath.py", line 375, in abspath
if not isabs(path):
File "/opt/conda/lib/python3.8/posixpath.py", line 63, in isabs
sep = _get_sep(s)
File "/opt/conda/lib/python3.8/posixpath.py", line 42, in _get_sep
if isinstance(path, bytes):
RecursionError: maximum recursion depth exceeded while calling a Python object
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/104085
Approved by: https://github.com/jithunnair-amd, https://github.com/malfet
Enables the hipSolver backend for ROCm builds
--------------------------------------------------------------------------
- Minimum ROCm version requirement - 5.3
- Introduces new macro USE_LINALG_SOLVER the controls enablement of both cuSOLVER and hipSOLVER
- Adds hipSOLVER API to hipification process
- combines hipSOLVER and hipSPARSE mappings into single SPECIAL map that takes priority among normal mappings
- Torch api to be moved to hipsolver backend (as opposed to magma) include: torch.svd(), torch.geqrf(), torch.orgqr(), torch.ormqr()
- Will enable 100+ linalg unit tests for ROCm
Pull Request resolved: https://github.com/pytorch/pytorch/pull/97370
Approved by: https://github.com/malfet
Merges startswith, endswith calls to into a single call that feeds in a tuple. Not only are these calls more readable, but it will be more efficient as it iterates through each string only once.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/96754
Approved by: https://github.com/ezyang
This PR is the first step towards refactors the build for nvfuser in order to have the coegen being a standalone library.
Contents inside this PR:
1. nvfuser code base has been moved to `./nvfuser`, from `./torch/csrc/jit/codegen/cuda/`, except for registration code for integration (interface.h/interface.cpp)
2. splits the build system so nvfuser is generating its own `.so` files. Currently there are:
- `libnvfuser_codegen.so`, which contains the integration, codegen and runtime system of nvfuser
- `nvfuser.so`, which is nvfuser's python API via pybind. Python frontend is now exposed via `nvfuser._C.XXX` instead of `torch._C._nvfuser`
3. nvfuser cpp tests is currently being compiled into `nvfuser_tests`
4. cmake is refactored so that:
- nvfuser now has its own `CMakeLists.txt`, which is under `torch/csrc/jit/codegen/cuda/`.
- nvfuser backend code is not compiled inside `libtorch_cuda_xxx` any more
- nvfuser is added as a subdirectory under `./CMakeLists.txt` at the very end after torch is built.
- since nvfuser has dependency on torch, the registration of nvfuser at runtime is done via dlopen (`at::DynamicLibrary`). This avoids circular dependency in cmake, which will be a nightmare to handle. For details, look at `torch/csrc/jit/codegen/cuda/interface.cpp::LoadingNvfuserLibrary`
Future work that's scoped in following PR:
- Currently since nvfuser codegen has dependency on torch, we need to refactor that out so we can move nvfuser into a submodule and not rely on dlopen to load the library. @malfet
- Since we moved nvfuser into a cmake build, we effectively disabled bazel build for nvfuser. This could impact internal workload at Meta, so we need to put support back. cc'ing @vors
Pull Request resolved: https://github.com/pytorch/pytorch/pull/89621
Approved by: https://github.com/davidberard98
### Description
Enables jiterator for ROCm builds. This includes necessary porting when hiprtc and nvrtc behavior differed. This also ported ROCm versus CUDA differences w.r.t. MAX_DIMS and NUM_THREADS from the non-jiterator code paths into jiterator.
### Testing
CI with ciflow/trunk label to force running ROCm workflows that are currently trunk-only.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77982
Approved by: https://github.com/ngimel
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/76333
The current PyTorch multi-head attention and transformer
implementations are slow. This should speed them up for inference.
ghstack-source-id: 154737857
(Note: this ignores all push blocking failures!)
Test Plan: CI
Reviewed By: cpuhrsch
Differential Revision: D35239925
fbshipit-source-id: 5a7eb8ff79bc6afb4b7d45075ddb2a24a6e2df28
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/70619
This Diff improves `hipify_python`, which is needed for AMD GPUs.
Change 1:
```
if (c == "," or ind == len(kernel_string) - 1) and closure == 0:
```
This is needed to deal with the following case (ex: https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/test/cuda_vectorized_test.cu#L111)
```
kernel<<<val, func()>>>(...)
// In this case, kernel_string is "val, func()"
// so closure gets 0 when ind == len(kernel_string) - 1.
```
Change 2:
```
mask_comments()
```
This is needed to deal with a case where "<<<" is included in a comment or a string literal (ex: https://github.com/pytorch/pytorch/blob/master/torch/csrc/deploy/interpreter/builtin_registry.cpp#L71)
```
abc = "<<<XYZ>>>"
// Though this <<<XYZ>>> is irrelevant to CUDA kernels,
// the current script attempts to hipify this and fails.
```
Test Plan:
This patch fixes errors I encountered by running
```
python3 tools/amd_build/build_amd.py
```
I confirmed, with Linux `diff`, that this patch does not change HIP code that was generated successfully with the original script.
Reviewed By: hyuen
Differential Revision: D33407743
fbshipit-source-id: bec822e040a154be4cda1c294536792ca8d596ae
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/67323
Applied patch proposed by Jeff https://github.com/pytorch/pytorch/pull/63948#issuecomment-952166982.
In PyTorch, we map cuBLAS->rocBLAS and cuSPARSE->hipSPARSE. Note the prefix, roc versus hip.
The 'hip' APIs offer a more direct CUDA-friendly mapping, but calling rocBLAS directly has better performance.
Unfortunately, the `roc*` types and `hip*` types differ, i.e., `rocblas_float_complex` versus `hipComplex`.
In the case of SPARSE, we must use the hip types for complex instead of the roc types,
but the pytorch mappings assume roc. Therefore, we create a new SPARSE mapping that has a higher priority.
Its mappings will trigger first, and only when a miss occurs will the lower-priority pytorch mapping take place.
When a file contains "sparse" in the filename, a mapping marked with API_SPARSE is preferred over other choices.
cc jeffdaily sunway513 jithunnair-amd ROCmSupport KyleCZH
Test Plan: Imported from OSS
Reviewed By: ngimel
Differential Revision: D31969246
Pulled By: cpuhrsch
fbshipit-source-id: 4ce1b35eaf9ef0d146a0955ce70c354ddd8f4669
Summary:
- [x] Fixed the Pyre type checking errors in `torch/utils/hipify/hipify_python.py`:
```
torch/utils/hipify/hipify_python.py:196:8 Incompatible variable type [9]: clean_ctx is declared to have type `GeneratedFileCleaner` but is used as type `None`.
torch/utils/hipify/hipify_python.py:944:4 Incompatible variable type [9]: clean_ctx is declared to have type `GeneratedFileCleaner` but is used as type `None`.
```
Fixing the issue: https://github.com/MLH-Fellowship/pyre-check/issues/78
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66164
Reviewed By: onionymous
Differential Revision: D31411443
Pulled By: 0xedward
fbshipit-source-id: c69f8fb839ad1d5ba5e4a223e1322ae7207e1574
Summary:
Some machines don't have a versionless `python` on their PATH, which breaks these existing shebangs.
I'm assuming that all the existing versionless `python` shebangs are meant to be `python3` and not `python2`; please let me know if my assumption was incorrect for any of these.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/58275
Test Plan: CI.
Reviewed By: zhouzhuojie
Differential Revision: D28428143
Pulled By: samestep
fbshipit-source-id: 6562be3d12924db72a92a0207b060ef740f61ebf
Summary:
Two changes:
- Print a warning rather than fail if creating hipified file fails with permission denied error
- Do not attempt to create /usr/include/libpng/png_hip.h in the first place
Pull Request resolved: https://github.com/pytorch/pytorch/pull/52709
Reviewed By: walterddr
Differential Revision: D26625033
Pulled By: malfet
fbshipit-source-id: ff82dc24aee12eac2daaa6e5bc938811b49ebbc6
Summary:
The torchvision build error from hipify revamp, "KeyError: '/usr/include/libpng16/png.h'" is fixed in this PR
Description:
Traceback (most recent call last):
File "setup.py", line 471, in <module>
ext_modules=get_extensions(),
File "setup.py", line 329, in get_extensions
extra_compile_args=extra_compile_args
File "/opt/conda/lib/python3.6/site-packages/torch/utils/cpp_extension.py", line 892, in CUDAExtension
is_pytorch_extension=True,
File "/opt/conda/lib/python3.6/site-packages/torch/utils/hipify/hipify_python.py", line 978, in hipify
clean_ctx=clean_ctx)
File "/opt/conda/lib/python3.6/site-packages/torch/utils/hipify/hipify_python.py", line 212, in preprocess
hip_clang_launch, is_pytorch_extension, clean_ctx, show_progress)
File "/opt/conda/lib/python3.6/site-packages/torch/utils/hipify/hipify_python.py", line 175, in preprocess_file_and_save_result
hip_clang_launch, is_pytorch_extension, clean_ctx, show_progress)
File "/opt/conda/lib/python3.6/site-packages/torch/utils/hipify/hipify_python.py", line 792, in preprocessor
output_source = RE_ANGLE_HEADER.sub(mk_repl('#include <{0}>', False), output_source)
File "/opt/conda/lib/python3.6/site-packages/torch/utils/hipify/hipify_python.py", line 785, in repl
value = HIPIFY_FINAL_RESULT[header_filepath]["hipified_path"]
KeyError: '/usr/include/libpng16/png.h'
Pull Request resolved: https://github.com/pytorch/pytorch/pull/51453
Reviewed By: agolynski
Differential Revision: D26459979
Pulled By: fmassa
fbshipit-source-id: f653f55fd34c71314e6c6682217f84b2d1e49335
Summary:
* remove some cases of single characters in
character classes--these can incur the overhead
of a character class with none of the benefits
of a multi-character character class
* for more details, see Chapter 6 of:
Friedl, Jeffrey. Mastering Regular Expressions. 3rd ed.,
O’Reilly Media, 2009.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/50294
Reviewed By: zhangguanheng66
Differential Revision: D25870912
Pulled By: malfet
fbshipit-source-id: 9be5be9ed11fd49876213f0be8121b24739f1c13
Summary:
[Refiled version of earlier PR https://github.com/pytorch/pytorch/issues/45451]
This PR revamps the hipify module in PyTorch to overcome a long list of shortcomings in the original implementation. However, these improvements are applied only when using hipify to build PyTorch extensions, not for PyTorch or Caffe2 itself.
Correspondingly, changes are made to cpp_extension.py to match these improvements.
The list of improvements to hipify is as follows:
1. Hipify files in the same directory as the original file, unless there's a "cuda" subdirectory in the original file path, in which case the hipified file will be in the corresponding file path with "hip" subdirectory instead of "cuda".
2. Never hipify the file in-place if changes are introduced due to hipification i.e. always ensure the hipified file either resides in a different folder or has a different filename compared to the original file.
3. Prevent re-hipification of already hipified files. This avoids creation of unnecessary "hip/hip" etc. subdirectories and additional files which have no actual use.
4. Do not write out hipified versions of files if they are identical to the original file. This results in a cleaner output directory, with minimal number of hipified files created.
5. Update header rewrite logic so that it accounts for the previous improvement.
6. Update header rewrite logic so it respects the rules for finding header files depending on whether "" or <> is used.
7. Return a dictionary of mappings of original file paths to hipified file paths from hipify function.
8. Introduce a version for hipify module to allow extensions to contain back-compatible code that targets a specific point in PyTorch where the hipify functionality changed.
9. Update cuda_to_hip_mappings.py to account for the ROCm component subdirectories inside /opt/rocm/include. This also results in cleanup of the Caffe2_HIP_INCLUDE path to remove unnecessary additions to the include path.
The list of changes to cpp_extension.py is as follows:
1. Call hipify when building a CUDAExtension for ROCm.
2. Prune the list of source files to CUDAExtension to include only the hipified versions of any source files in the list (if both original and hipified versions of the source file are in the list)
3. Add subdirectories of /opt/rocm/include to the include path for extensions, so that ROCm headers for subcomponent libraries are found automatically
cc jeffdaily sunway513 ezyang
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48715
Reviewed By: bdhirsh
Differential Revision: D25272824
Pulled By: ezyang
fbshipit-source-id: 8bba68b27e41ca742781e1c4d7b07c6f985f040e
Summary:
This PR revamps the hipify module in PyTorch to overcome a long list of shortcomings in the original implementation. However, these improvements are applied only when using hipify to build PyTorch extensions, **not for PyTorch or Caffe2 itself**.
Correspondingly, changes are made to `cpp_extension.py` to match these improvements.
The list of improvements to hipify is as follows:
1. Hipify files in the same directory as the original file, unless there's a "cuda" subdirectory in the original file path, in which case the hipified file will be in the corresponding file path with "hip" subdirectory instead of "cuda".
2. Never hipify the file in-place if changes are introduced due to hipification i.e. always ensure the hipified file either resides in a different folder or has a different filename compared to the original file.
3. Prevent re-hipification of already hipified files. This avoids creation of unnecessary "hip/hip" etc. subdirectories and additional files which have no actual use.
4. Do not write out hipified versions of files if they are identical to the original file. This results in a cleaner output directory, with minimal number of hipified files created.
5. Update header rewrite logic so that it accounts for the previous improvement.
6. Update header rewrite logic so it respects the rules for finding header files depending on whether `""` or `<>` is used.
7. Return a dictionary of mappings of original file paths to hipified file paths from `hipify` function.
8. Introduce a version for hipify module to allow extensions to contain back-compatible code that targets a specific point in PyTorch where the hipify functionality changed.
9. Update `cuda_to_hip_mappings.py` to account for the ROCm component subdirectories inside `/opt/rocm/include`. This also results in cleanup of the `Caffe2_HIP_INCLUDE` path to remove unnecessary additions to the include path.
The list of changes to `cpp_extension.py` is as follows:
1. Call `hipify` when building a CUDAExtension for ROCm.
2. Prune the list of source files to CUDAExtension to include only the hipified versions of any source files in the list (if both original and hipified versions of the source file are in the list)
3. Add subdirectories of /opt/rocm/include to the include path for extensions, so that ROCm headers for subcomponent libraries are found automatically
cc jeffdaily sunway513 hgaspar lcskrishna ashishfarmer
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45451
Reviewed By: ezyang
Differential Revision: D24924736
Pulled By: malfet
fbshipit-source-id: 4af42b8ff4f21c3782dedb8719b8f9f86b34bd2d
Summary:
This is to workaround an issue in hipclang wrt templated kernel name arguments to hipLaunchKernelGGL.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/41022
Differential Revision: D22404183
Pulled By: ngimel
fbshipit-source-id: 63135ccb9e087f4c8e8663ed383979f7e2c1ba06
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/35615
Python 2 has reached end-of-life and is no longer supported by PyTorch.
Now we can clean up a lot of cruft that we put in place to support it.
These changes were all done manually, and I skipped anything that seemed
like it would take more than a few seconds, so I think it makes sense to
review it manually as well (though using side-by-side view and ignoring
whitespace change might be helpful).
Test Plan: CI
Differential Revision: D20842886
Pulled By: dreiss
fbshipit-source-id: 8cad4e87c45895e7ce3938a88e61157a79504aed
Summary:
This enables cpp_extensions.load/load_inline. This works by hipify-ing cuda sources.
Also enable tests.
CuDNN/MIOpen extensions aren't yet supported, I propose to not do this in this PR.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/35897
Differential Revision: D20983279
Pulled By: ezyang
fbshipit-source-id: a5d0f5ac592d04488a6a46522c58e2ee0a6fd57c
Summary:
This pull request has changes for:
1. Enabling a torch module with HIP code to be compiled by cpp_extensions.py
2. Fixes for hipify module to be able to be used by a torch extension
cc: ezyang iotamudelta jeffdaily
Pull Request resolved: https://github.com/pytorch/pytorch/pull/32669
Differential Revision: D20033893
Pulled By: zou3519
fbshipit-source-id: fd6ddc8cdcd3930f41008636bb2bc9dd26cdb008
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/31151
same as title. I am not sure why this was not added in the first place.
Test Plan: wait for build to succeed.
Reviewed By: bddppq, xw285cornell
Differential Revision: D18880216
fbshipit-source-id: 8b17d4fbd5dd08c28c52df8b1da77b69d56d65dc
