pytorch/test/cpp/api
Will Feng a88f310151 Simplify header inclusion in test/cpp/api/modules.cpp (#25921)
Summary:
This PR simplifies header inclusion in `test/cpp/api/modules.cpp`, so that when we add a new `torch::nn` module and add the test in `modules.cpp`, we can check that the new module's header is included in `torch/torch.h`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/25921

Differential Revision: D17303220

Pulled By: yf225

fbshipit-source-id: 327db0ff2f075d52e7b594b3dffc5a59441e0931
2019-09-10 18:37:39 -07:00
..
any.cpp Fix Windows build and test in CI (#11716) 2018-11-13 16:35:54 -08:00
autograd.cpp Improve handling of mixed-type tensor operations (#22273) 2019-09-05 18:26:09 -07:00
CMakeLists.txt C++ ModuleList 2019-08-19 10:02:40 -07:00
dataloader.cpp add sorting policy to ChunkDataset (#23053) 2019-07-29 12:34:02 -07:00
expanding-array.cpp Rewrite C++ API tests in gtest (#11953) 2018-09-21 21:28:16 -07:00
init_baseline.h Kaiming Initialization (#14718) 2019-02-15 14:58:22 -08:00
init_baseline.py Kaiming Initialization (#14718) 2019-02-15 14:58:22 -08:00
init.cpp Fix torch::nn::init::orthogonal_ with CNNs (#18915) 2019-04-09 10:39:15 -07:00
integration.cpp Move isnan to C++ (#15722) 2019-01-08 10:42:33 -08:00
jit.cpp Add Pickler C++ API (#23241) 2019-08-12 14:43:31 -07:00
memory.cpp Hide c10::optional and nullopt in torch namespace (#12927) 2018-10-26 00:08:04 -07:00
misc.cpp Add TORCH_WARN_ONCE, and use it in Tensor.data<T>() (#25207) 2019-08-27 21:42:44 -07:00
module.cpp Deprecate tensor.data<T>(), and codemod tensor.data<T>() to tensor.data_ptr<T>() (#24886) 2019-08-21 20:11:24 -07:00
modulelist.cpp Adding ModuleList to modules.h (#25346) 2019-08-29 10:49:22 -07:00
modules.cpp Simplify header inclusion in test/cpp/api/modules.cpp (#25921) 2019-09-10 18:37:39 -07:00
optim_baseline.h Use torch:: instead of at:: in all C++ APIs (#13523) 2018-11-06 14:32:25 -08:00
optim_baseline.py Use torch:: instead of at:: in all C++ APIs (#13523) 2018-11-06 14:32:25 -08:00
optim.cpp Replace cursors with OrderedDict (#13427) 2018-11-07 11:10:05 -08:00
ordered_dict.cpp Replace cursors with OrderedDict (#13427) 2018-11-07 11:10:05 -08:00
parallel.cpp Deprecate tensor.data<T>(), and codemod tensor.data<T>() to tensor.data_ptr<T>() (#24886) 2019-08-21 20:11:24 -07:00
README.md Rewrite C++ API tests in gtest (#11953) 2018-09-21 21:28:16 -07:00
rnn.cpp Bidirectional GRU and LSTM C++ API forward fix (#22850) 2019-07-22 12:59:47 -07:00
sequential.cpp Include named_any.h in modules.h (#21437) 2019-06-06 09:57:33 -07:00
serialize.cpp Ignore nn::Functional submodules in nn::Module serialization (#19740) 2019-04-26 12:47:23 -07:00
static.cpp Make call operator on module holder call forward (#15831) 2019-01-14 14:40:33 -08:00
support.h Add TORCH_WARN_ONCE, and use it in Tensor.data<T>() (#25207) 2019-08-27 21:42:44 -07:00
tensor_cuda.cpp Deprecate tensor.data<T>(), and codemod tensor.data<T>() to tensor.data_ptr<T>() (#24886) 2019-08-21 20:11:24 -07:00
tensor_options_cuda.cpp Revert D15920763: Move TensorOptions to ATen/core 2019-08-13 12:07:18 -07:00
tensor_options.cpp Revert D15920763: Move TensorOptions to ATen/core 2019-08-13 12:07:18 -07:00
tensor.cpp Deprecate tensor.data<T>(), and codemod tensor.data<T>() to tensor.data_ptr<T>() (#24886) 2019-08-21 20:11:24 -07:00
torch_include.cpp Add get/set_num_interop_threads into torch.h include (#20659) 2019-05-20 00:34:59 -07:00

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.