mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-06 12:20:52 +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
87 lines
3.3 KiB
C++
87 lines
3.3 KiB
C++
#include <gtest/gtest.h>
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#include <torch/torch.h>
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#include <torch/cuda.h>
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// NB: This file is compiled even in CPU build (for some reason), so
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// make sure you don't include any CUDA only headers.
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using namespace at;
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// TODO: This might be generally helpful aliases elsewhere.
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at::Device CPUDevice() {
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return at::Device(at::kCPU);
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}
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at::Device CUDADevice(DeviceIndex index) {
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return at::Device(at::kCUDA, index);
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}
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// A macro so we don't lose location information when an assertion fails.
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#define REQUIRE_OPTIONS(device_, index_, type_, layout_) \
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ASSERT_EQ(options.device().type(), Device((device_), (index_)).type()); \
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ASSERT_TRUE( \
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options.device().index() == Device((device_), (index_)).index()); \
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ASSERT_EQ(typeMetaToScalarType(options.dtype()), (type_)); \
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ASSERT_TRUE(options.layout() == (layout_))
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#define REQUIRE_TENSOR_OPTIONS(device_, index_, type_, layout_) \
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ASSERT_EQ(tensor.device().type(), Device((device_), (index_)).type()); \
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ASSERT_EQ(tensor.device().index(), Device((device_), (index_)).index()); \
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ASSERT_EQ(tensor.scalar_type(), (type_)); \
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ASSERT_TRUE(tensor.options().layout() == (layout_))
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(TensorOptionsTest, ConstructsWellFromCUDATypes_CUDA) {
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auto options = CUDA(kFloat).options();
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REQUIRE_OPTIONS(kCUDA, -1, kFloat, kStrided);
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options = CUDA(kInt).options();
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REQUIRE_OPTIONS(kCUDA, -1, kInt, kStrided);
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options = getDeprecatedTypeProperties(Backend::SparseCUDA, kFloat).options();
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REQUIRE_OPTIONS(kCUDA, -1, kFloat, kSparse);
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options = getDeprecatedTypeProperties(Backend::SparseCUDA, kByte).options();
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REQUIRE_OPTIONS(kCUDA, -1, kByte, kSparse);
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// NOLINTNEXTLINE(bugprone-argument-comment,cppcoreguidelines-avoid-magic-numbers)
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options = CUDA(kFloat).options(/*device=*/5);
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REQUIRE_OPTIONS(kCUDA, 5, kFloat, kStrided);
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options =
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// NOLINTNEXTLINE(bugprone-argument-comment,cppcoreguidelines-avoid-magic-numbers)
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getDeprecatedTypeProperties(Backend::SparseCUDA, kFloat).options(/*device=*/5);
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REQUIRE_OPTIONS(kCUDA, 5, kFloat, kSparse);
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(TensorOptionsTest, ConstructsWellFromCUDATensors_MultiCUDA) {
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto options = empty(5, device(kCUDA).dtype(kDouble)).options();
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REQUIRE_OPTIONS(kCUDA, 0, kDouble, kStrided);
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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options = empty(5, getDeprecatedTypeProperties(Backend::SparseCUDA, kByte)).options();
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REQUIRE_OPTIONS(kCUDA, 0, kByte, kSparse);
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if (torch::cuda::device_count() > 1) {
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Tensor tensor;
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{
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DeviceGuard guard(CUDADevice(1));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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tensor = empty(5, device(kCUDA));
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}
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options = tensor.options();
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REQUIRE_OPTIONS(kCUDA, 1, kFloat, kStrided);
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{
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DeviceGuard guard(CUDADevice(1));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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tensor = empty(5, device(kCUDA).layout(kSparse));
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}
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options = tensor.options();
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REQUIRE_OPTIONS(kCUDA, 1, kFloat, kSparse);
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}
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}
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