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CMakeLists.txt
CMakeLists.txt
 
 
README.md
README.md
 
 
any.cpp
any.cpp
 
 
autograd.cpp
autograd.cpp
 
 
dataloader.cpp
dataloader.cpp
 
 
dispatch.cpp
dispatch.cpp
 
 
enum.cpp
enum.cpp
 
 
expanding-array.cpp
expanding-array.cpp
 
 
fft.cpp
fft.cpp
 
 
functional.cpp
functional.cpp
 
 
init.cpp
init.cpp
 
 
init_baseline.h
init_baseline.h
 
 
init_baseline.py
init_baseline.py
 
 
integration.cpp
integration.cpp
 
 
jit.cpp
jit.cpp
 
 
memory.cpp
memory.cpp
 
 
misc.cpp
misc.cpp
 
 
module.cpp
module.cpp
 
 
moduledict.cpp
moduledict.cpp
 
 
modulelist.cpp
modulelist.cpp
 
 
modules.cpp
modules.cpp
 
 
namespace.cpp
namespace.cpp
 
 
nn_utils.cpp
nn_utils.cpp
 
 
operations.cpp
operations.cpp
 
 
optim.cpp
optim.cpp
 
 
optim_baseline.h
optim_baseline.h
 
 
optim_baseline.py
optim_baseline.py
 
 
ordered_dict.cpp
ordered_dict.cpp
 
 
parallel.cpp
parallel.cpp
 
 
parallel_benchmark.cpp
parallel_benchmark.cpp
 
 
parameterdict.cpp
parameterdict.cpp
 
 
parameterlist.cpp
parameterlist.cpp
 
 
rnn.cpp
rnn.cpp
 
 
sequential.cpp
sequential.cpp
 
 
serialize.cpp
serialize.cpp
 
 
static.cpp
static.cpp
 
 
support.cpp
support.cpp
 
 
support.h
support.h
 
 
tensor.cpp
tensor.cpp
 
 
tensor_cuda.cpp
tensor_cuda.cpp
 
 
tensor_flatten.cpp
tensor_flatten.cpp
 
 
tensor_indexing.cpp
tensor_indexing.cpp
 
 
tensor_options.cpp
tensor_options.cpp
 
 
tensor_options_cuda.cpp
tensor_options_cuda.cpp
 
 
torch_include.cpp
torch_include.cpp
 
 
transformer.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.