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Files

Nikita Shulga c4d1ff02f8 [Lint] Update clang-format to 19.1.4 (#153889 )

All changes other than the one to `tools/linter/adapters/s3_init_config.json` are generated by newer clang-format
Pull Request resolved: https://github.com/pytorch/pytorch/pull/153889
Approved by: https://github.com/cyyever, https://github.com/atalman

2025-05-20 14:12:46 +00:00

any.cpp

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autograd.cpp

c10::optional -> std::optional (#142514 )

2024-12-12 17:23:46 +00:00

CMakeLists.txt

Fix some CMake issues (#153686 )

2025-05-19 00:31:34 +00:00

dataloader.cpp

[Lint] Update clang-format to 19.1.4 (#153889 )

2025-05-20 14:12:46 +00:00

dispatch.cpp

[Environment Variable][2/N] Use thread-safe setenv wrapper (#124485 )

2024-10-04 07:30:51 +00:00

enum.cpp

[2/N] Move c10::variant to std::variant (#109723 )

2023-09-24 02:47:43 +00:00

expanding-array.cpp

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fft.cpp

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functional.cpp

Expose bicubic mode for torch::nn::functional::grid_sample in LibTorch (#150817 )

2025-04-21 08:55:27 +00:00

grad_mode.cpp

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inference_mode.cpp

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init_baseline.h

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init_baseline.py

[BE][Easy][7/19] enforce style for empty lines in import segments in test/[a-c]*/ and test/[q-z]*/ (#129758 )

2024-07-31 10:54:03 +00:00

init.cpp

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integration.cpp

C10_UNUSED to [[maybe_unused]] (#6357 ) (#138364 )

2024-10-19 13:17:43 +00:00

ivalue.cpp

Use object identity for deepcopy memo (#126126 )

2024-05-17 00:06:26 +00:00

jit.cpp

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memory.cpp

[codemod] c10:optional -> std::optional (#126135 )

2024-05-14 19:35:51 +00:00

meta_tensor.cpp

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misc.cpp

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module.cpp

torch::optional -> std::optional (#138987 )

2024-10-28 19:09:46 +00:00

moduledict.cpp

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modulelist.cpp

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modules.cpp

[Lint] Update clang-format to 19.1.4 (#153889 )

2025-05-20 14:12:46 +00:00

namespace.cpp

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nested_int.cpp

Rename singleton int to nested int (#119661 )

2024-02-16 19:21:17 +00:00

nested.cpp

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nn_utils.cpp

C10_UNUSED to [[maybe_unused]] (#6357 ) (#138364 )

2024-10-19 13:17:43 +00:00

operations.cpp

C10_UNUSED to [[maybe_unused]] (#6357 ) (#138364 )

2024-10-19 13:17:43 +00:00

optim_baseline.h

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optim_baseline.py

UFMT formatting on test/autograd test/ao test/cpp test/backends (#123369 )

2024-04-05 18:51:38 +00:00

optim.cpp

[14/N] Fix extra warnings brought by clang-tidy-17 (#141644 )

2024-12-13 06:22:13 +00:00

ordered_dict.cpp

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parallel_benchmark.cpp

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parallel.cpp

torch::optional -> std::optional (#138987 )

2024-10-28 19:09:46 +00:00

parameterdict.cpp

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parameterlist.cpp

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README.md

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rnn.cpp

Fix broken URLs (#152237 )

2025-04-27 09:56:42 +00:00

sequential.cpp

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serialize.cpp

Remove more unused variables in tests (#127510 )

2024-05-31 03:39:45 +00:00

special.cpp

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static.cpp

std::value/std::type -> std::_v/std::_t (#138746 )

2024-10-26 20:59:24 +00:00

support.cpp

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support.h

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tensor_cuda.cpp

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tensor_flatten.cpp

Fix typo under test directory (#111304 )

2023-10-16 23:06:06 +00:00

tensor_indexing.cpp

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tensor_options_cuda.cpp

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tensor_options.cpp

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tensor.cpp

[Lint] Update clang-format to 19.1.4 (#153889 )

2025-05-20 14:12:46 +00:00

torch_include.cpp

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transformer.cpp

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README.md

C++ Frontend Tests

In this folder live the tests for PyTorch's C++ Frontend. They use the GoogleTest test framework.

CUDA Tests

To make a test runnable only on platforms with CUDA, you should suffix your test with _CUDA, e.g.

TEST(MyTestSuite, MyTestCase_CUDA) { }

To make it runnable only on platforms with at least two CUDA machines, suffix it with _MultiCUDA instead of _CUDA, e.g.

TEST(MyTestSuite, MyTestCase_MultiCUDA) { }

There is logic in main.cpp that detects the availability and number of CUDA devices and supplies the appropriate negative filters to GoogleTest.

Integration Tests

Integration tests use the MNIST dataset. You must download it by running the following command from the PyTorch root folder:

$ python tools/download_mnist.py -d test/cpp/api/mnist

The required paths will be referenced as test/cpp/api/mnist/... in the test code, so you must run the integration tests from the PyTorch root folder.