pytorch/test/cpp/api
Pavel Belevich 795c913636 C++ API parity: CELU
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/27487

Test Plan: Imported from OSS

Differential Revision: D17835406

Pulled By: pbelevich

fbshipit-source-id: a8282ae65d8996efcc8b8d846cfa637c3f89eda6
2019-10-11 06:23:57 -07:00
..
any.cpp Separate libtorch tests from libtorch build. (#26927) 2019-10-02 08:04:52 -07:00
autograd.cpp Change C++ API test files to only include torch/torch.h (#27067) 2019-10-10 09:46:29 -07:00
CMakeLists.txt Add clip_grad_norm_ to c++ api (#26140) 2019-10-04 13:50:36 -07:00
dataloader.cpp Change C++ API test files to only include torch/torch.h (#27067) 2019-10-10 09:46:29 -07:00
expanding-array.cpp Change C++ API test files to only include torch/torch.h (#27067) 2019-10-10 09:46:29 -07:00
functional.cpp C++ API parity: CELU 2019-10-11 06:23:57 -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 Change C++ API test files to only include torch/torch.h (#27067) 2019-10-10 09:46:29 -07:00
integration.cpp Change C++ API test files to only include torch/torch.h (#27067) 2019-10-10 09:46:29 -07:00
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 Change C++ API test files to only include torch/torch.h (#27067) 2019-10-10 09:46:29 -07:00
module.cpp Re-organize C++ API torch::nn folder structure (#26262) 2019-09-17 10:07:29 -07:00
modulelist.cpp Implement torch.nn.Embedding / EmbeddingBag in PyTorch C++ API (#26358) 2019-10-08 22:13:39 -07:00
modules.cpp C++ API parity: CELU 2019-10-11 06:23:57 -07:00
nn_utils.cpp Add clip_grad_norm_ to c++ api (#26140) 2019-10-04 13:50:36 -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 Re-organize C++ API torch::nn folder structure (#26262) 2019-09-17 10:07:29 -07:00
ordered_dict.cpp Change C++ API test files to only include torch/torch.h (#27067) 2019-10-10 09:46:29 -07:00
parallel.cpp C++ API parity: at::Tensor::grad 2019-09-18 09:20:38 -07:00
README.md Rewrite C++ API tests in gtest (#11953) 2018-09-21 21:28:16 -07:00
rnn.cpp Change C++ API test files to only include torch/torch.h (#27067) 2019-10-10 09:46:29 -07:00
sequential.cpp Implement torch.nn.Embedding / EmbeddingBag in PyTorch C++ API (#26358) 2019-10-08 22:13:39 -07:00
serialize.cpp Include iteration_ in SGD optimizer serialization (#26906) 2019-09-27 09:37:20 -07:00
static.cpp Re-organize C++ API torch::nn folder structure (#26262) 2019-09-17 10:07:29 -07:00
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 Change C++ API test files to only include torch/torch.h (#27067) 2019-10-10 09:46:29 -07:00
tensor_options.cpp Change C++ API test files to only include torch/torch.h (#27067) 2019-10-10 09:46:29 -07:00
tensor.cpp Change C++ API test files to only include torch/torch.h (#27067) 2019-10-10 09:46:29 -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.