Python 3.13 added PyObject_GetOptionalAttrString. I'm not 100% certain that it is strictly better than the old approach in all cases, but based on documentation/comments it seems to be meant for this type of use, and it's faster when I profile torchtitan training (which gets to the "check for the `__torch_function__` attr on some object" part of maybe_has_torch_function frequently enough to notice, but wastes a bunch of time generating exceptions that we then suppressed here).
Pull Request resolved: https://github.com/pytorch/pytorch/pull/164624
Approved by: https://github.com/Skylion007
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:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/59758
The underlying call to tp_getattr is const safe but CPython
has not fixed it due to BC problems. No reason not to advertise
the better type here though!
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Test Plan: Imported from OSS
Reviewed By: albanD
Differential Revision: D29017911
Pulled By: ezyang
fbshipit-source-id: 8d55983fe6416c03eb69c6367bcc431c30000133
Summary:
In my last PR I've missed CUDA and distributed folders, fixing this now
This change is autogenerated by `python tool/clang_tidy.py -s`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/57235
Reviewed By: janeyx99
Differential Revision: D28084444
Pulled By: malfet
fbshipit-source-id: bf222f69ee90c7872c3cb0931e8cdb84f0cb3cda
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48965
This PR pulls `__torch_function__` checking entirely into C++, and adds a special `object_has_torch_function` method for ops which only have one arg as this lets us skip tuple construction and unpacking. We can now also do away with the Python side fast bailout for `Tensor` (e.g. `if any(type(t) is not Tensor for t in tensors) and has_torch_function(tensors)`) because they're actually slower than checking with the Python C API.
Test Plan: Existing unit tests. Benchmarks are in #48966
Reviewed By: ezyang
Differential Revision: D25590732
Pulled By: robieta
fbshipit-source-id: 6bd74788f06cdd673f3a2db898143d18c577eb42
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/35614
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.
Test Plan: CI
Differential Revision: D20842876
Pulled By: dreiss
fbshipit-source-id: 18abf0d324ed2185ec6d27c864e935d856dcc6ad
Summary:
Add automatic translations for a few argument names that commonly differ between PyTorch and NumPy.
For now, they are as follows:
* `keepdim` -> `keepdims`
* `dim` -> `axis`
* `input` -> (any of `a`, `x`, `x1`)
* `other` -> `x2`
Basic examples:
```python
>>> t=torch.randn(10,10)
>>> torch.sum(x=t, axis=1)
tensor([ 0.5199, -0.3768, 4.3619, -0.9105, 1.1804, 1.0837, -0.9036, 0.2365,
1.1171, -0.0999])
```
```python
>>> torch.add(x1=5, x2=6)
tensor(11)
```
The additional overhead is zero when using traditional PyTorch argument names, and a few (usually 1) extra PyDict lookups when using NumPy argument names.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20451
Differential Revision: D15337521
Pulled By: umanwizard
fbshipit-source-id: 7a7d389786f4ccf5c86a14ecb2002c61730c51b5
Summary:
Anywhere we used #include "foo.h", we now say #include <foo.h>
Paths are adjusted to be rooted out of aten/src, torch/lib, or
the root level directory.
I modified CMakeLists.txt by hand to remove TH and THC from
the include paths.
I used the following script to do the canonicalization:
```
import subprocess
import re
import os.path
files = subprocess.check_output(['git', 'ls-files']).decode('utf-8').rstrip().split('\n')
for fn in files:
if not any(fn.endswith(suff) for suff in ['.cu', '.cpp', '.in', '.h', '.hpp', '.cu', '.cuh', '.cc']):
continue
if not any(fn.startswith(pref) for pref in ["aten/", "torch/"]):
continue
with open(fn, 'r') as f:
c = f.read()
def fmt(p):
return "#include <{}>".format(p)
def repl(m):
p = m.group(1)
if p in ["dlfcn.h", "unistd.h", "nvrtc.h", "cuda.h", "cuda_runtime.h", "cstdint", "cudnn.h", "Python.h", "cusparse.h", "cuda_runtime_api.h", "cuda_fp16.h", "cublas_v2.h", "stdint.h", "curand_kernel.h"]:
return fmt(p)
if any(p.startswith(pref) for pref in ["torch/csrc", "c10/", "ATen/", "caffe2/", "TH/", "THC/", "Eigen/", "gtest/", "zdl/", "gloo/", "onnx/", "miopen/"]):
return fmt(p)
for root in ["aten/src", "torch/lib", ""]:
for bad_root in [os.path.dirname(fn), "aten/src/TH", "aten/src/THC", "torch/csrc"]:
new_p = os.path.relpath(os.path.join(bad_root, p), root)
if not new_p.startswith("../") and (os.path.exists(os.path.join(root, new_p)) or os.path.exists(os.path.join(root, new_p + ".in"))):
return fmt(new_p)
print("ERROR: ", fn, p)
return m.group(0)
new_c = re.sub(r'#include "([^"]+)"', repl, c)
if new_c != c:
print(fn)
with open(fn, 'w') as f:
f.write(new_c)
```
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/14849
Reviewed By: dzhulgakov
Differential Revision: D13363445
Pulled By: ezyang
fbshipit-source-id: 52361f878a672785f9306c9e9ab2513128092b68
