pytorch/test/cpp/tensorexpr/test_cpp_codegen.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

65 lines
1.8 KiB
C++

#include <gtest/gtest.h>
#include <test/cpp/tensorexpr/test_base.h>
#include <torch/csrc/jit/tensorexpr/cpp_codegen.h>
#include <torch/csrc/jit/tensorexpr/mem_arena.h>
#include <torch/csrc/jit/tensorexpr/stmt.h>
#include <torch/csrc/jit/testing/file_check.h>
namespace torch {
namespace jit {
using namespace torch::jit::tensorexpr;
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
TEST(CppPrinter, AllocateOnStackThenFree) {
KernelScope kernel_scope;
std::vector<const Expr*> dims = {new IntImm(2), new IntImm(3)};
const Buf* buf = new Buf("x", dims, kInt);
Allocate* alloc = new Allocate(buf);
Free* free = new Free(buf);
Block* block = Block::make({alloc, free});
std::stringstream ss;
CppPrinter printer(&ss);
printer.visit(block);
const std::string expected = R"(
# CHECK: {
# CHECK: int x[6];
# CHECK: }
)";
torch::jit::testing::FileCheck().run(expected, ss.str());
}
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
TEST(CppPrinter, AllocateOnHeapThenFree) {
KernelScope kernel_scope;
std::vector<const Expr*> dims = {
// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
new IntImm(20),
// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
new IntImm(50),
new IntImm(3)};
const Buf* buf = new Buf("y", dims, kLong);
Allocate* alloc = new Allocate(buf);
Free* free = new Free(buf);
Block* block = Block::make({alloc, free});
std::stringstream ss;
CppPrinter printer(&ss);
printer.visit(block);
// size(long) = 8;
// dim0 * dim1 * dim2 * size(long) = 24000.
const std::string expected = R"(
# CHECK: {
# CHECK: int64_t* y = static_cast<int64_t*>(malloc(24000));
# CHECK: free(y);
# CHECK: }
)";
torch::jit::testing::FileCheck().run(expected, ss.str());
}
} // namespace jit
} // namespace torch