mirror of https://github.com/zebrajr/pytorch.git synced 2025-12-06 12:20:52 +01:00

History

Nikita Shulga 88920b26be [Cmake] Check that gcc-9.4 or newer is used (#112858 ) As this is the oldest gcc that is fully compatible with C++17 standard. - Replace number of conditional version with simpler `if(CMAKE_COMPILER_IS_GNUCXX)` or `append_cxx_flag_if_supported`. - As `-Wsuggest-override` condition was hidden before incorrect guard, add missing `override` keywords to `torch::autograd::PyFunctionTensorPostAccGradHooks::apply_with_saved` , `caffe2::python::TensorFeeder::Feed` and `cafee2::NetObserverReporterPrint::report``` Fixes https://github.com/pytorch/pytorch/issues/101839 Pull Request resolved: https://github.com/pytorch/pytorch/pull/112858 Approved by: https://github.com/Skylion007, https://github.com/albanD		2023-11-06 17:19:53 +00:00
..
any.cpp
autograd.cpp	Fix Tensor::register_hook behavior on undefined tensors (#105587 )	2023-07-21 14:37:21 +00:00
CMakeLists.txt	[Cmake] Check that gcc-9.4 or newer is used (#112858 )	2023-11-06 17:19:53 +00:00
dataloader.cpp	Fix typo under test directory (#111304 )	2023-10-16 23:06:06 +00:00
dispatch.cpp
enum.cpp	[2/N] Move c10::variant to std::variant (#109723 )	2023-09-24 02:47:43 +00:00
expanding-array.cpp
fft.cpp
functional.cpp	Fix `functional::smooth_l1_loss` signatures to not override `beta` (#109798 )	2023-10-11 21:37:37 +00:00
grad_mode.cpp
inference_mode.cpp
init_baseline.h
init_baseline.py	[BE] Enable ruff's UP rules and autoformat test/ (#105434 )	2023-07-19 20:36:06 +00:00
init.cpp
integration.cpp
jit.cpp
memory.cpp	[Reland] Move torch::make_unique to std::make_unique (#109780 )	2023-09-21 18:30:21 +00:00
meta_tensor.cpp
misc.cpp
module.cpp
moduledict.cpp
modulelist.cpp
modules.cpp	add check for torch_arg (#108397 )	2023-09-08 23:18:27 +00:00
namespace.cpp
nested.cpp
nn_utils.cpp
operations.cpp
optim_baseline.h
optim_baseline.py	[BE] Enable ruff's UP rules and autoformat test/ (#105434 )	2023-07-19 20:36:06 +00:00
optim.cpp	[Reland] Elimates c10::guts::to_string (#108748 )	2023-09-07 13:35:17 +00:00
ordered_dict.cpp
parallel_benchmark.cpp
parallel.cpp
parameterdict.cpp
parameterlist.cpp
README.md
rnn.cpp	Add checks to `num_layers` for `RNN`, `LSTM`, `GRU` (#108853 )	2023-09-09 19:33:52 +00:00
sequential.cpp
serialize.cpp	[Reland] Elimates c10::guts::to_string (#108748 )	2023-09-07 13:35:17 +00:00
special.cpp
static.cpp
support.cpp
support.h	[BE] Add missing override to remove build warning spam (#107191 )	2023-08-15 17:32:34 +00:00
tensor_cuda.cpp
tensor_flatten.cpp	Fix typo under test directory (#111304 )	2023-10-16 23:06:06 +00:00
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.