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
135 lines
5.5 KiB
C++
135 lines
5.5 KiB
C++
#include <gtest/gtest.h>
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#include <ATen/ATen.h>
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#include <cmath>
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#define REQUIRE_TENSOR_OPTIONS(device_, index_, type_, layout_) \
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ASSERT_TRUE( \
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tensor.device().type() == at::Device((device_), (index_)).type()); \
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ASSERT_TRUE( \
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tensor.device().index() == at::Device((device_), (index_)).index()); \
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ASSERT_EQ(tensor.dtype(), (type_)); \
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ASSERT_TRUE(tensor.layout() == (layout_))
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(TensorTest, AllocatesTensorOnTheCorrectDevice_MultiCUDA) {
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auto tensor = at::tensor({1, 2, 3}, at::device({at::kCUDA, 1}));
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ASSERT_EQ(tensor.device().type(), at::Device::Type::CUDA);
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ASSERT_EQ(tensor.device().index(), 1);
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(TensorTest, ToDevice_MultiCUDA) {
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auto tensor = at::empty({3, 4});
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REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kFloat, at::kStrided);
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tensor = tensor.to({at::kCUDA, 1});
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REQUIRE_TENSOR_OPTIONS(at::kCUDA, 1, at::kFloat, at::kStrided);
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tensor = tensor.to({at::kCUDA, 0});
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REQUIRE_TENSOR_OPTIONS(at::kCUDA, 0, at::kFloat, at::kStrided);
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tensor = tensor.to({at::kCUDA, 1});
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REQUIRE_TENSOR_OPTIONS(at::kCUDA, 1, at::kFloat, at::kStrided);
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tensor = tensor.to(at::Device(at::kCPU));
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REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kFloat, at::kStrided);
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tensor = tensor.to(at::kCUDA);
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REQUIRE_TENSOR_OPTIONS(at::kCUDA, 0, at::kFloat, at::kStrided);
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tensor = tensor.to(at::TensorOptions({at::kCUDA, 1}));
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REQUIRE_TENSOR_OPTIONS(at::kCUDA, 1, at::kFloat, at::kStrided);
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tensor = tensor.to(at::TensorOptions({at::kCUDA, 0}));
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REQUIRE_TENSOR_OPTIONS(at::kCUDA, 0, at::kFloat, at::kStrided);
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tensor = tensor.to(at::TensorOptions(at::kDouble));
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REQUIRE_TENSOR_OPTIONS(at::kCUDA, 0, at::kDouble, at::kStrided);
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tensor = tensor.to(at::TensorOptions({at::kCUDA, 1}));
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REQUIRE_TENSOR_OPTIONS(at::kCUDA, 1, at::kDouble, at::kStrided);
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tensor = tensor.to(at::TensorOptions(at::kInt));
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REQUIRE_TENSOR_OPTIONS(at::kCUDA, 1, at::kInt, at::kStrided);
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tensor = tensor.to(at::TensorOptions(at::Device(at::kCPU)));
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REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kInt, at::kStrided);
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tensor = tensor.to(at::TensorOptions(at::kCUDA));
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REQUIRE_TENSOR_OPTIONS(at::kCUDA, 0, at::kInt, at::kStrided);
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(TensorTest, ToTensorAndTensorAttributes_MultiCUDA) {
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auto tensor = at::empty({3, 4});
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REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kFloat, at::kStrided);
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auto other = at::empty({3, 4}, at::kFloat);
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tensor = tensor.to(other);
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REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kFloat, at::kStrided);
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other = at::empty({3, 4}, at::TensorOptions(at::kCUDA).dtype(at::kDouble));
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tensor = tensor.to(other.dtype());
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REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kDouble, at::kStrided);
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tensor = tensor.to(other.device());
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REQUIRE_TENSOR_OPTIONS(at::kCUDA, 0, at::kDouble, at::kStrided);
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other = at::empty({3, 4}, at::TensorOptions({at::kCUDA, 1}).dtype(at::kLong));
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tensor = tensor.to(other.device(), other.dtype());
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REQUIRE_TENSOR_OPTIONS(at::kCUDA, 1, at::kLong, at::kStrided);
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other = at::empty({3, 4}, at::kFloat);
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tensor = tensor.to(other.options());
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REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kFloat, at::kStrided);
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(TensorTest, ToDoesNotCopyWhenOptionsAreAllTheSame_CUDA) {
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auto tensor = at::empty({3, 4}, at::TensorOptions(at::kFloat).device(at::Device("cuda")));
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auto hopefully_not_copy = tensor.to(tensor.options());
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ASSERT_EQ(hopefully_not_copy.data_ptr<float>(), tensor.data_ptr<float>());
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hopefully_not_copy = tensor.to(at::kFloat);
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ASSERT_EQ(hopefully_not_copy.data_ptr<float>(), tensor.data_ptr<float>());
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hopefully_not_copy = tensor.to("cuda");
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ASSERT_EQ(hopefully_not_copy.data_ptr<float>(), tensor.data_ptr<float>());
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hopefully_not_copy = tensor.to(at::TensorOptions("cuda"));
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ASSERT_EQ(hopefully_not_copy.data_ptr<float>(), tensor.data_ptr<float>());
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hopefully_not_copy = tensor.to(at::TensorOptions(at::kFloat));
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ASSERT_EQ(hopefully_not_copy.data_ptr<float>(), tensor.data_ptr<float>());
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(TensorTest, ToDeviceAndDtype_MultiCUDA) {
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auto tensor = at::empty({3, 4});
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REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kFloat, at::kStrided);
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tensor = tensor.to({at::kCUDA, 1}, at::kInt);
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REQUIRE_TENSOR_OPTIONS(at::kCUDA, 1, at::kInt, at::kStrided);
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tensor = tensor.to(at::TensorOptions({at::kCUDA, 0}).dtype(at::kLong));
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REQUIRE_TENSOR_OPTIONS(at::kCUDA, 0, at::kLong, at::kStrided);
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tensor = tensor.to(at::TensorOptions({at::kCUDA, 1}).dtype(at::kDouble));
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REQUIRE_TENSOR_OPTIONS(at::kCUDA, 1, at::kDouble, at::kStrided);
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tensor = tensor.to(at::kCPU, at::kInt);
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REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kInt, at::kStrided);
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
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TEST(TensorTest, MagmaInitializesCorrectly_CUDA) {
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// Any tensor will work here as long as it's invertible
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-c-arrays,modernize-avoid-c-arrays)
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float data[] = { 1, 1, 1, 0,
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0, 3, 1, 2,
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2, 3, 1, 0,
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1, 0, 2, 1 };
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auto tensor = at::from_blob(data, {4, 4}, at::TensorOptions(at::kFloat)).cuda();
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if (at::hasMAGMA()) {
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at::inverse(tensor);
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}
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}
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