Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/46227
Follow up from https://github.com/pytorch/pytorch/issues/45419, in
this PR I've removed as many PyCFunction casts as I could from the codebase.
The only ones I didn't remove were the ones with `METH_VARARGS | METH_KEYWORDS`
which have 3 parameters instead of 2 and had to be casted. Example: `
{"copy_", (PyCFunction)(void(*)(void))THPStorage_(copy_), METH_VARARGS |
METH_KEYWORDS, nullptr},`
ghstack-source-id: 114632704
Test Plan: waitforbuildbot
Reviewed By: albanD
Differential Revision: D24269435
fbshipit-source-id: 025cfd43a9a2a3e59f6b2951c1a78749193d77cf
Summary:
Fixes https://github.com/pytorch/pytorch/issues/33899
In the issue, we have
```
TypeError("expected %s (got %s)", dispatch_key, toString(other.key_set()).c_str());
```
which results in `dispatch_key` being interpreted as a c-string by `sprintf`. Adding `__attrbute__((format))` to the `TypeError` constructor allows gcc or clang to detect this at compile time. Then `-Werror=format` makes it a hard error at compile time.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/34019
Differential Revision: D20194842
Pulled By: ezyang
fbshipit-source-id: fa4448916c309d91e3d949fa65bb3aa7cca5c6a8
Summary:
Back in April, malmaud added type annotations for `dataloader.py`. However, at about the same time, SsnL in https://github.com/pytorch/pytorch/issues/19228 replaced `_DataLoaderIter` with `_BaseDataLoaderIter` and two subclasses, `_SingleProcessDataLoaderIter`, and `_MultiProcessingDataLoaderIter`. However - probably because these changes happened in parallel at roughly the same time, the type stubs and several other references in the codebase were never updated to match this refactoring.
I've gone ahead and done the updates to reflect the refactoring in https://github.com/pytorch/pytorch/issues/19228, which fixes the specific type stub/impelementation mismatch pointed out in https://github.com/pytorch/pytorch/issues/26673, although not the broader problem that pytorch doesn't have a test to make sure that the `.pyi` type stub files match the real API defined in `.py` files.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/27105
Differential Revision: D17813641
Pulled By: ezyang
fbshipit-source-id: ed7ac025c8d6ad3f298dd073347ec83bb4b6600c
Summary:
Follow-up to gh-25483, more of the same fixes for warnings like:
```
../torch/csrc/autograd/python_variable.cpp:503:31: warning: cast between incompatible function types from ‘PyObject* (*)(THPVariable*)’ {aka ‘_object* (*)(THPVariable*)’} to ‘getter’ {aka ‘_object* (*)(_object*, void*)’} [-Wcast-function-type]
503 | {"_backward_hooks", (getter)THPVariable_get_backwards_hooks, (setter)THPVariable_set_backwards_hooks, nullptr, nullptr},
| ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
This takes the build log output for a full rebuild with GCC 9.1 from ~10,000 to ~7,000 lines.
`clang-tidy` is going to complain, no way around that - see discussion at the end of gh-25483.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/26104
Differential Revision: D17396831
Pulled By: ezyang
fbshipit-source-id: d71696bfe4dbe25519e4bcb7753151c118bd39f7
Summary:
Same as #14668, and was approved there.
ailzhang , please apply this patch to Horizon's `data_streamer.py`: https://gist.github.com/SsnL/020fdb3d6b7016d81b6ba1d04cc41459 Thank you!
Below is the original description at #14668:
As I am working on tasks in https://github.com/pytorch/pytorch/issues/13023, I realized how unreadable the code is because all functions to be run in multiprocessing must be at top global level. Adding more functionalities to `dataloader.py` will only make things worse.
So in this PR, I refactor `dataloader.py` and move much of it into `data._utils`. E.g., the `_worker_loop` and related methods are now in `data._utils.worker`, signal handling code in `data._utils.signal_handling`, collating code in `data._utils.collate`, etc. This split, IMHO, makes code much clearer. I will base my future changes to DataLoader on top of this.
No functionality is changed, except that I added `torch._six.queue`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15331
Reviewed By: yf225
Differential Revision: D13503120
Pulled By: ailzhang
fbshipit-source-id: 94df16b4d80ad1102c437cde0d5a2e62cffe1f8e
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
Summary:
As I am working on tasks in https://github.com/pytorch/pytorch/issues/13023, I realized how unreadable the code is because all functions to be run in multiprocessing must be at top global level. Adding more functionalities to `dataloader.py` will only make things worse.
So in this PR, I refactor `dataloader.py` and move much of it into `data._utils`. E.g., the `_worker_loop` and related methods are now in `data._utils.worker`, signal handling code in `data._utils.signal_handling`, collating code in `data._utils.collate`, etc. This split, IMHO, makes code much clearer. I will base my future changes to DataLoader on top of this.
No functionality is changed, except that I added `torch._six.queue`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/14668
Reviewed By: soumith
Differential Revision: D13289919
Pulled By: ailzhang
fbshipit-source-id: d701bc7bb48f5dd7b163b5be941a9d27eb277a4c
Summary:
How did we get so many uses of `NULL` again?
ezyang
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11047
Differential Revision: D9566799
Pulled By: goldsborough
fbshipit-source-id: 83469f352ac69aa65bdaf1a1a21f922d892e0db3
Summary:
Tell people to run with num_workers=0 when DataLoader worker failed
Closes https://github.com/pytorch/pytorch/pull/9007
Differential Revision: D8686005
Pulled By: SsnL
fbshipit-source-id: bf872267f609c7b86e943061caab953149507bfe
