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cyy 8629f9b3f2 Remove more unused variables in tests (#127510 ) Follows #127379 Pull Request resolved: https://github.com/pytorch/pytorch/pull/127510 Approved by: https://github.com/Skylion007, https://github.com/r-barnes		2024-05-31 03:39:45 +00:00
..
any.cpp
autograd.cpp	[codemod] `c10:optional` -> `std::optional` (#126135 )	2024-05-14 19:35:51 +00:00
CMakeLists.txt	Remove more unused variables in tests (#127510 )	2024-05-31 03:39:45 +00:00
dataloader.cpp
dispatch.cpp
enum.cpp
expanding-array.cpp
fft.cpp
functional.cpp
grad_mode.cpp
inference_mode.cpp
init_baseline.h
init_baseline.py	UFMT formatting on test/autograd test/ao test/cpp test/backends (#123369 )	2024-04-05 18:51:38 +00:00
init.cpp
integration.cpp
ivalue.cpp	Use object identity for deepcopy memo (#126126 )	2024-05-17 00:06:26 +00:00
jit.cpp
memory.cpp	[codemod] `c10:optional` -> `std::optional` (#126135 )	2024-05-14 19:35:51 +00:00
meta_tensor.cpp
misc.cpp
module.cpp
moduledict.cpp
modulelist.cpp
modules.cpp
namespace.cpp
nested_int.cpp
nested.cpp
nn_utils.cpp
operations.cpp
optim_baseline.h
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	include scheduler_on_plateau in optim.h (#121722 )	2024-03-27 19:45:25 +00:00
ordered_dict.cpp
parallel_benchmark.cpp
parallel.cpp
parameterdict.cpp
parameterlist.cpp
README.md
rnn.cpp
sequential.cpp
serialize.cpp	Remove more unused variables in tests (#127510 )	2024-05-31 03:39:45 +00:00
special.cpp
static.cpp
support.cpp
support.h
tensor_cuda.cpp
tensor_flatten.cpp
tensor_indexing.cpp
tensor_options_cuda.cpp
tensor_options.cpp
tensor.cpp
torch_include.cpp
transformer.cpp

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.