mirror of
https://github.com/saymrwulf/pytorch.git
synced 2026-05-14 20:57:59 +00:00
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
125 lines
3.2 KiB
C++
125 lines
3.2 KiB
C++
#include <gtest/gtest.h>
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#include <test/cpp/jit/test_utils.h>
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#include <torch/csrc/jit/ir/ir.h>
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#include <torch/csrc/jit/ir/irparser.h>
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#include <torch/csrc/jit/passes/peephole.h>
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namespace torch {
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namespace jit {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(PeepholeOptimizeTest, IsAndIsNot)
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// test is / is not none optimization
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{
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auto graph = std::make_shared<Graph>();
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parseIR(
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R"IR(
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graph(%0 : int):
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%1 : None = prim::Constant()
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%2 : bool = aten::__is__(%0, %1)
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%3 : bool = aten::__isnot__(%0, %1)
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return (%2, %3)
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)IR",
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graph.get());
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PeepholeOptimize(graph);
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testing::FileCheck()
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.check_not("aten::__is__")
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->check_not("aten::__isnot__")
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->run(*graph);
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(PeepholeOptimizeTest, IsAndIsNot2) {
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auto graph = std::make_shared<Graph>();
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parseIR(
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R"IR(
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graph(%0: int?):
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%1 : None = prim::Constant()
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%2 : bool = aten::__is__(%0, %1)
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%3 : bool = aten::__isnot__(%0, %1)
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return (%2, %3)
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)IR",
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graph.get());
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PeepholeOptimize(graph);
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testing::FileCheck()
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.check("aten::__is__")
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->check("aten::__isnot__")
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->run(*graph);
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(PeepholeOptimizeTest, IsAndIsNot3) {
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auto graph = std::make_shared<Graph>();
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parseIR(
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R"IR(
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graph(%0: int?):
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%1 : Tensor = prim::AutogradZero()
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%2 : None = prim::Constant()
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%4 : bool = aten::__is__(%0, %1)
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%5 : bool = aten::__isnot__(%1, %2)
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return (%4, %5)
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)IR",
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graph.get());
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PeepholeOptimize(graph);
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testing::FileCheck()
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.check("aten::__is__")
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->check_not("aten::__isnot__")
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->run(*graph);
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(PeepholeOptimizeTest, UnwrapOptional)
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// test unwrap optional
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{
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auto graph = std::make_shared<Graph>();
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parseIR(
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R"IR(
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graph():
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%1 : Float(*, *, *) = prim::Constant()
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%2 : bool = aten::_unwrap_optional(%1)
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%3 : bool = prim::unchecked_unwrap_optional(%1)
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return (%2, %3)
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)IR",
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graph.get());
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PeepholeOptimize(graph);
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testing::FileCheck().check_not("unwrap")->run(*graph);
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(PeepholeOptimizeTest, UnwrapOptional2) {
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auto graph = std::make_shared<Graph>();
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parseIR(
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R"IR(
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graph(%1 : Float(*, *, *)?):
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%2 : bool = aten::_unwrap_optional(%1)
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%3 : bool = prim::unchecked_unwrap_optional(%1)
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return (%2, %3)
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)IR",
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graph.get());
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PeepholeOptimize(graph);
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testing::FileCheck().check_count("unwrap", 2)->run(*graph);
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(PeepholeOptimizeTest, AddMMFusion) {
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auto graph = std::make_shared<Graph>();
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parseIR(
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R"IR(
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graph(
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%0 : Float(2, 3, 4),
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%1 : Float(2, 3, 4),
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%2 : Float(1, 1, 1)):
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%3 : int = prim::Constant[value=1]()
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%4 : Tensor = aten::mm(%0, %1)
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%5 : Tensor = aten::add(%4, %2, %3)
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%6 : Tensor = aten::add(%5, %2, %3)
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return (%6)
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)IR",
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graph.get());
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FuseAddMM(graph);
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testing::FileCheck().check("addmm")->run(*graph);
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}
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} // namespace jit
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} // namespace torch
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