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History

soulitzer abe96654de [reland][BE][autograd Function] Raise an error if input is returned a… (#98051 ) …s-is and saved for forward or backward in setup_context Fixes #ISSUE_NUMBER Relanding this in a new non-ghstack PR so I can import this to do co-dev Pull Request resolved: https://github.com/pytorch/pytorch/pull/98051 Approved by: https://github.com/zou3519		2023-04-11 15:42:54 +00:00
..
any.cpp
autograd.cpp	[reland][BE][autograd Function] Raise an error if input is returned a… (#98051 )	2023-04-11 15:42:54 +00:00
CMakeLists.txt
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
init.cpp
integration.cpp
jit.cpp
memory.cpp
meta_tensor.cpp
misc.cpp
module.cpp
moduledict.cpp	[fix] nn c++ : segfault in modulelist and moduledict (#93074 )	2023-01-27 12:20:19 +00:00
modulelist.cpp	[fix] nn c++ : segfault in modulelist and moduledict (#93074 )	2023-01-27 12:20:19 +00:00
modules.cpp	Adding nn.ZeroPad1d and nn.ZeroPad3d (#96295 )	2023-03-10 03:51:41 +00:00
namespace.cpp
nested.cpp
nn_utils.cpp
operations.cpp
optim_baseline.h
optim_baseline.py
optim.cpp	[nn] add set_to_none flag for C++ optim endpoint (#92989 )	2023-01-26 04:16:52 +00:00
ordered_dict.cpp
parallel_benchmark.cpp
parallel.cpp
parameterdict.cpp
parameterlist.cpp
README.md
rnn.cpp	distinguish mutability of untyped Storage::data (#97690 )	2023-04-08 02:02:28 +00:00
sequential.cpp
serialize.cpp
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	Extend TensorImpl with BackendMeta (#97429 )	2023-04-04 23:47:03 +00:00
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.