mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 00:21:07 +01:00
4cb534f92e
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
54 lines
1.7 KiB
C++
54 lines
1.7 KiB
C++
#pragma once
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#include <torch/csrc/jit/ir/ir.h>
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#include <torch/csrc/utils/object_ptr.h>
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namespace torch {
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namespace jit {
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void initPythonIRBindings(PyObject* module);
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// execute a Python function, used for Ops we can't optimize but that we want to
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// optimize around
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struct ConcretePythonOp : public PythonOp {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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static Symbol Kind;
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ConcretePythonOp(Graph* graph) : PythonOp(graph, ::c10::prim::PythonOp) {}
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ConcretePythonOp* init(
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THPObjectPtr&& pyobj,
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const std::string& cconv,
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pyobj_list&& scalar_args) {
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this->pyobj = std::move(pyobj);
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this->scalar_args = std::move(scalar_args);
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this->cconv = cconv;
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return this;
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}
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// The Python object which contains the implementation of this function.
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// This is either a class (non-legacy) or an object (legacy). See
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// TraceInterpreterState for execution semantics.
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THPObjectPtr pyobj;
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// The calling convention for the Python function.
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// 'c' -- constant argument
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// 'd' -- dynamic argument
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std::string cconv;
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// Scalar arguments to the Python function. Not necessarily passed to
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// the function in this order; see cconv for the correct order.
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std::vector<THPObjectPtr> scalar_args;
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std::string name() const override;
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void cloneFrom(Node* other_) override;
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Node* allocNewInstance(Graph* g) override {
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return new ConcretePythonOp(g);
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}
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// recover the autograd.Function instance, if this PythonOp's function
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// was originally SomeFunction.apply
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// used in ONNX for discovering symbolics
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c10::optional<THPObjectPtr> autogradFunction() const override;
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void writeScalars(std::ostream& out) const override;
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void lint_python() const override;
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};
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} // namespace jit
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} // namespace torch
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