pytorch/torch/csrc/utils/cuda_lazy_init.cpp
Nikita Shulga 4cb534f92e Make PyTorch code-base clang-tidy compliant (#56892)
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
2021-04-28 14:10:25 -07:00

35 lines
947 B
C++

#include <torch/csrc/utils/cuda_lazy_init.h>
#include <torch/csrc/python_headers.h>
#include <mutex>
#include <torch/csrc/Exceptions.h>
#include <torch/csrc/utils/object_ptr.h>
namespace torch {
namespace utils {
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
static bool run_yet = false;
void cuda_lazy_init() {
pybind11::gil_scoped_acquire g;
// Protected by the GIL. We don't use call_once because under ASAN it
// has a buggy implementation that deadlocks if an instance throws an
// exception. In any case, call_once isn't necessary, because we
// have taken a lock.
if (!run_yet) {
auto module = THPObjectPtr(PyImport_ImportModule("torch.cuda"));
if (!module) throw python_error();
auto res = THPObjectPtr(PyObject_CallMethod(module.get(), "_lazy_init", ""));
if (!res) throw python_error();
run_yet = true;
}
}
void set_run_yet_variable_to_false() {
run_yet = false;
}
}
}