On big endian systems byteswapping should be done other way around.
This change fixes TestE2ETensorPipe.TestTrainingLoop test from
test_cpp_rpc testsuite on big endian systems.
Use uint64_t when decoding double values.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/99869
Approved by: https://github.com/ezyang
This PR introduces **-Wmissing-prototypes** of clang-tidy to prevent further coding errors such as the one fixed by PR #96714.
<!--
copilot:summary
-->
### <samp>🤖 Generated by Copilot at fd2cf2a</samp>
This pull request makes several internal functions static to improve performance and avoid name clashes. It also fixes some typos, formatting, and missing includes in various files. It adds a new .clang-tidy check to warn about missing prototypes for non-static functions.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/96805
Approved by: https://github.com/malfet, https://github.com/albanD
Fixes#92831
This PR fixes a test failure of `TestTorch.test_from_buffer` on a big-endian machine. The root cause of this failure is that current `THPStorage_fromBuffer` does not perform endian handling correctly on a big-endian.
In `THPStorage_fromBuffer`, the given buffer is stored as machine native-endian. Thus, if the specified byte order (e.g. `big`) is equal to machine native-endian, swapping elements should not be performed. However, in the current implementation, [`decode*BE()`](https://github.com/pytorch/pytorch/blob/master/torch/csrc/utils/byte_order.cpp#L72-L109) always swaps elements regardless of machine native-endian (i.e. these methods assume buffer is stored as little-endian).
Thus, this PR uses the following approaches:
- if the specified byte order (e.g. `big`) is equal to machine native-endian, call `decode*LE()` that does not swap elements by passing `torch::utils::THP_LITTLE_ENDIAN` to `THP_decode*Buffer()`.
- if the specified byte order (e.g. `big`) is not equal to machine native-endian, call `decode*BE()` that always swap elements by passing `torch::utils::THP_BIG_ENDIAN` to `THP_decode*Buffer()`.
After applying this PR to the master branch, I confirmed that the test passes on a big-endian machine.
```
% python test/test_torch.py TestTorch.test_from_buffer
/home/ishizaki/PyTorch/master/test/test_torch.py:6367: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
self.assertEqual(torch.ByteStorage.from_buffer(a).tolist(), [1, 2, 3, 4])
...
/home/ishizaki/PyTorch/master/test/test_torch.py:6396: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
self.assertEqual(bytes.tolist(), [1, 2, 3, 4])
.
----------------------------------------------------------------------
Ran 1 test in 0.021s
OK
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/92834
Approved by: https://github.com/ezyang
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73378
1) ran check_for_c10_loops.py to automatically update all files (*.h, *.hpp, *.cpp) under fbcode/caffe2/torch (this is the path in the check_for_c10_loops.py, slightly different from the task description where the path mentioned was fbcode/caffe2. since current commit already contains 27 files, will use a separate commit for additional files).
2) manually reviewed each change, and reverted a few files:
(a) select_keys.cpp, bucketize_calibration.cpp, index_mmh and TCPStore.cpp: iterator modified in loop
(b) qlinear_4bit_ops.cpp and id_list_feature_merge_conversion.cpp: condition containing multiple expressions.
Test Plan:
Doing the following (still in progress, will address issues as they appear):
buck build ...
buck test ...
Reviewed By: r-barnes
Differential Revision: D34435473
fbshipit-source-id: b8d3c94768b02cf71ecb24bb58d29ee952f672c2
(cherry picked from commit fa9b0864f3761a501868fe0373204b12fdfc2b32)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/69041
`TH_CONCAT_{N}` is still being used by THP so I've moved that into
it's own header but all the compiled code is gone.
Test Plan: Imported from OSS
Reviewed By: anjali411
Differential Revision: D32872477
Pulled By: ngimel
fbshipit-source-id: 06c82d8f96dbcee0715be407c61dfc7d7e8be47a
Summary:
Delete `-Wno-unused-variable` from top level `CMakeLists.txt`
Still suppress those warnings for tests and `torch_python`
Delete number of unused variables from caffe2 code
Use `(void)var;` to suppress unused variable in range loops
Use `C10_UNUSED` for global constructors and use `constexpr` instead of `static` for global constants
Do not delete `caffe2::OperatorBase::Output` calls as they have side effects
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66041
Reviewed By: ngimel
Differential Revision: D31360142
Pulled By: malfet
fbshipit-source-id: 6fdfb9f91efdc49ca984a2f2a17ee377d28210c8
Summary:
Delete `-Wno-unused-variable` from top level `CMakeLists.txt`
Still suppress those warnings for tests and `torch_python`
Delete number of unused variables from caffe2 code
Use `(void)var;` to suppress unused variable in range loops
Use `C10_UNUSED` for global constructors and use `constexpr` instead of `static` for global constants
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65954
Reviewed By: ngimel
Differential Revision: D31326599
Pulled By: malfet
fbshipit-source-id: 924155f1257a2ba1896c50512f615e45ca1f61f3
Summary:
This PR suppresses clang-tidy warnings in the codebase (for now) so that we can re-enable clang-tidy checks on master.
I ran this script to add the `NOLINTNEXTLINE` comments (on a devserver):
```bash
python3 setup.py develop
# Uses same script that's run on CI and adds the -j (parallel), -s (add comments), -k (continue if diagnostic errors are found) options
python3 tools/clang_tidy.py \
-j \
-s \
-k \
-v \
--paths torch/csrc/ \
-g"-torch/csrc/jit/passes/onnx/helper.cpp" \
-g"-torch/csrc/jit/passes/onnx/shape_type_inference.cpp" \
-g"-torch/csrc/jit/serialization/onnx.cpp" \
-g"-torch/csrc/jit/serialization/export.cpp" \
-g"-torch/csrc/jit/serialization/import.cpp" \
-g"-torch/csrc/jit/serialization/import_legacy.cpp" \
-g"-torch/csrc/onnx/init.cpp" \
-g"-torch/csrc/cuda/nccl.*" \
-g"-torch/csrc/cuda/python_nccl.cpp" \
-g"-torch/csrc/autograd/FunctionsManual.cpp" \
-g"-torch/csrc/generic/*.cpp" \
-g"-torch/csrc/jit/codegen/cuda/runtime/*" \
-g"-torch/csrc/deploy/interpreter/interpreter.cpp" \
-g"-torch/csrc/deploy/interpreter/interpreter.h" \
-g"-torch/csrc/deploy/interpreter/interpreter_impl.h" \
-g"-torch/csrc/deploy/interpreter/test_main.cpp"
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/60649
Test Plan: Verified changes by re-running the script (without the `-s` option) and seeing no warnings/errors.
Reviewed By: walterddr, janeyx99
Differential Revision: D29504258
Pulled By: 1ntEgr8
fbshipit-source-id: 78310b30ee8213b73ddb4771ad874665323e7a4e
Summary:
This is an automatic change generated by the following script:
```
#!/usr/bin/env python3
from subprocess import check_output, check_call
import os
def get_compiled_files_list():
import json
with open("build/compile_commands.json") as f:
data = json.load(f)
files = [os.path.relpath(node['file']) for node in data]
for idx, fname in enumerate(files):
if fname.startswith('build/') and fname.endswith('.DEFAULT.cpp'):
files[idx] = fname[len('build/'):-len('.DEFAULT.cpp')]
return files
def run_clang_tidy(fname):
check_call(["python3", "tools/clang_tidy.py", "-c", "build", "-x", fname,"-s"])
changes = check_output(["git", "ls-files", "-m"])
if len(changes) == 0:
return
check_call(["git", "commit","--all", "-m", f"NOLINT stubs for {fname}"])
def main():
git_files = check_output(["git", "ls-files"]).decode("ascii").split("\n")
compiled_files = get_compiled_files_list()
for idx, fname in enumerate(git_files):
if fname not in compiled_files:
continue
if fname.startswith("caffe2/contrib/aten/"):
continue
print(f"[{idx}/{len(git_files)}] Processing {fname}")
run_clang_tidy(fname)
if __name__ == "__main__":
main()
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56892
Reviewed By: H-Huang
Differential Revision: D27991944
Pulled By: malfet
fbshipit-source-id: 5415e1eb2c1b34319a4f03024bfaa087007d7179
Summary:
Following up on this: https://github.com/pytorch/pytorch/pull/35851 cross dtype storage copy is not being used internally, so I have not included cross dtype copy for complex.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/35771
Differential Revision: D21319650
Pulled By: anjali411
fbshipit-source-id: 07c72996ee598eba0cf401ad61534494d6f5b5b3
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/25527
Master GH issue: https://github.com/pytorch/pytorch/issues/23110.
This change builds upon https://github.com/pytorch/pytorch/pull/24876 and
provides all the autograd hooks needed for a forward pass with distributed rpc
for builtin operators. This change does not address distributed rpc for python
UDFs and that will be addressed in follow up PRs.
Summary of changes:
1. Attach send autograd functions when a request is sent from the client and
response is sent from the server.
2. Attach receive autograd functions when a request is received on the server
and a response is received on the client.
3. Generate a globally unique autograd_message_id for each send/recv autograd
function pair to uniquely identify them.
ghstack-source-id: 91240466
Test Plan: unit tests.
Differential Revision: D17148077
fbshipit-source-id: 192d8a3f552ed7cc939f55dcca332965c9bd3233
