pytorch/test/cpp/jit/test_dce.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

53 lines
1.6 KiB
C++

#include <gtest/gtest.h>
#include <torch/csrc/jit/ir/irparser.h>
#include <torch/csrc/jit/passes/dead_code_elimination.h>
#include <torch/csrc/jit/testing/file_check.h>
namespace torch {
namespace jit {
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
TEST(EliminateDeadCodeTest, Basic) {
auto graph = std::make_shared<Graph>();
// Consider the following loop:
// for i in range(3):
// tot += a[0][0]
// b = a[0]
// b[0] += 1
// print(tot)
// We want to check that b[0] and b are properly marked as live and thus not
// DCE'd.
const std::string input =
R"IR(
graph():
%48 : None = prim::Constant()
%50 : bool = prim::Constant[value=1]()
%0 : int = prim::Constant[value=2]()
%12 : int = prim::Constant[value=1]()
%24 : int = prim::Constant[value=3]()
%31 : int = prim::Constant[value=0]()
%2 : int[] = prim::ListConstruct(%0, %0)
%a.1 : Tensor = prim::MakeTestTensor()
%14 : int[] = prim::ListConstruct(%12)
%tot.1 : Tensor = prim::MakeTestTensor()
%tot : Tensor = prim::Loop(%24, %50, %tot.1)
block0(%i : int, %tot.6 : Tensor):
%33 : Tensor = aten::select(%a.1, %31, %31)
%35 : Tensor = aten::select(%33, %31, %31)
# CHECK: add_
%tot.3 : Tensor = aten::add_(%tot.6, %35, %12)
%b.1 : Tensor = aten::select(%a.1, %31, %31)
%44 : Tensor = aten::select(%b.1, %31, %31)
# CHECK: add_
%46 : Tensor = aten::add_(%44, %12, %12)
-> (%50, %tot.3)
return (%tot)
)IR";
parseIR(input, graph.get());
EliminateDeadCode(graph);
// Check that dead code elimin
testing::FileCheck().run(input, *graph);
}
} // namespace jit
} // namespace torch