mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 12:21:27 +01:00
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
110 lines
3.3 KiB
C++
110 lines
3.3 KiB
C++
#include <gtest/gtest.h>
|
|
|
|
#include <torch/detail/static.h>
|
|
#include <torch/csrc/utils/variadic.h>
|
|
#include <torch/torch.h>
|
|
|
|
#include <string>
|
|
#include <vector>
|
|
|
|
template <
|
|
typename T,
|
|
typename = torch::enable_if_t<!torch::detail::is_module<T>::value>>
|
|
bool f(T&& m) {
|
|
return false;
|
|
}
|
|
|
|
template <typename T>
|
|
torch::detail::enable_if_module_t<T, bool> f(T&& m) {
|
|
return true;
|
|
}
|
|
|
|
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
|
|
TEST(TestStatic, AllOf) {
|
|
ASSERT_TRUE(torch::all_of<>::value);
|
|
ASSERT_TRUE(torch::all_of<true>::value);
|
|
ASSERT_TRUE((torch::all_of<true, true, true>::value));
|
|
ASSERT_FALSE(torch::all_of<false>::value);
|
|
ASSERT_FALSE((torch::all_of<false, false, false>::value));
|
|
ASSERT_FALSE((torch::all_of<true, true, false>::value));
|
|
}
|
|
|
|
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
|
|
TEST(TestStatic, AnyOf) {
|
|
ASSERT_FALSE(torch::any_of<>::value);
|
|
ASSERT_TRUE(bool((torch::any_of<true>::value)));
|
|
ASSERT_TRUE(bool((torch::any_of<true, true, true>::value)));
|
|
ASSERT_FALSE(bool((torch::any_of<false>::value)));
|
|
}
|
|
|
|
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
|
|
TEST(TestStatic, EnableIfModule) {
|
|
ASSERT_TRUE(f(torch::nn::LinearImpl(1, 2)));
|
|
ASSERT_FALSE(f(5));
|
|
ASSERT_TRUE(torch::detail::check_not_lvalue_references<int>());
|
|
ASSERT_TRUE((torch::detail::check_not_lvalue_references<float, int, char>()));
|
|
ASSERT_FALSE(
|
|
(torch::detail::check_not_lvalue_references<float, int&, char>()));
|
|
ASSERT_TRUE(torch::detail::check_not_lvalue_references<std::string>());
|
|
ASSERT_FALSE(torch::detail::check_not_lvalue_references<std::string&>());
|
|
}
|
|
|
|
struct A : torch::nn::Module {
|
|
int forward() {
|
|
// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
|
|
return 5;
|
|
}
|
|
};
|
|
|
|
struct B : torch::nn::Module {
|
|
std::string forward(torch::Tensor tensor) {
|
|
return "";
|
|
}
|
|
};
|
|
|
|
struct C : torch::nn::Module {
|
|
float forward(torch::Tensor& tensor) {
|
|
// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
|
|
return 5.0;
|
|
}
|
|
};
|
|
|
|
struct D : torch::nn::Module {
|
|
char forward(torch::Tensor&& tensor) {
|
|
return 'x';
|
|
}
|
|
};
|
|
|
|
struct E : torch::nn::Module {};
|
|
|
|
// Put in a function because macros don't handle the comma between arguments to
|
|
// is_same well ...
|
|
template <typename Module, typename ExpectedType, typename... Args>
|
|
void assert_has_expected_type() {
|
|
using ReturnType =
|
|
typename torch::detail::return_type_of_forward<Module, Args...>::type;
|
|
constexpr bool is_expected_type =
|
|
std::is_same<ReturnType, ExpectedType>::value;
|
|
ASSERT_TRUE(is_expected_type) << Module().name();
|
|
}
|
|
|
|
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
|
|
TEST(TestStatic, ReturnTypeOfForward) {
|
|
assert_has_expected_type<A, int>();
|
|
assert_has_expected_type<B, std::string, torch::Tensor>();
|
|
assert_has_expected_type<C, float, torch::Tensor&>();
|
|
assert_has_expected_type<D, char, torch::Tensor&&>();
|
|
assert_has_expected_type<E, void>();
|
|
}
|
|
|
|
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
|
|
TEST(TestStatic, Apply) {
|
|
std::vector<int> v;
|
|
// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
|
|
torch::apply([&v](int x) { v.push_back(x); }, 1, 2, 3, 4, 5);
|
|
ASSERT_EQ(v.size(), 5);
|
|
for (size_t i = 0; i < v.size(); ++i) {
|
|
ASSERT_EQ(v.at(i), i + 1);
|
|
}
|
|
}
|