pytorch/test/cpp/api
Will Feng bb1d9b238d torch::nn::FractionalMaxPool{2,3}d module and functional
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/29933

Test Plan: Imported from OSS

Differential Revision: D18548174

Pulled By: yf225

fbshipit-source-id: 070776db6e8b7ad94d9b7cbd82b3d6966f061a46
2019-11-19 17:24:07 -08:00
..
any.cpp
autograd.cpp Fix bugs in torch::tensor constructor (#28523) 2019-10-31 12:53:06 -07:00
CMakeLists.txt Use default dtype for torch::tensor(floating_point_values) and torch::tensor(empty braced-init-list) when dtype is not specified (#29632) 2019-11-13 15:17:11 -08:00
dataloader.cpp Fix bugs in torch::tensor constructor (#28523) 2019-10-31 12:53:06 -07:00
enum.cpp Use c10::variant-based enums for F::grid_sample 2019-11-12 16:05:26 -08:00
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 torch::nn::FractionalMaxPool{2,3}d module and functional 2019-11-19 17:24:07 -08:00
init.cpp Use default dtype for torch::tensor(floating_point_values) and torch::tensor(empty braced-init-list) when dtype is not specified (#29632) 2019-11-13 15:17:11 -08:00
init_baseline.h
init_baseline.py
integration.cpp C++ API parity: Dropout, Dropout2d, Dropout3d 2019-11-15 20:32:06 -08:00
jit.cpp Remove attempToRecoverType (#26767) 2019-10-16 11:07:13 -07:00
memory.cpp
misc.cpp Change C++ API test files to only include torch/torch.h (#27067) 2019-10-10 09:46:29 -07:00
module.cpp Allow passing undefined Tensor to Module::register_parameter (#27948) 2019-10-15 10:10:42 -07:00
modulelist.cpp C++ API parity: Dropout, Dropout2d, Dropout3d 2019-11-15 20:32:06 -08:00
modules.cpp torch::nn::FractionalMaxPool{2,3}d module and functional 2019-11-19 17:24:07 -08:00
nn_utils.cpp Add C++ API clip_grad_value_ for nn:utils (#28736) 2019-10-31 19:11:54 -07:00
optim.cpp Use default dtype for torch::tensor(floating_point_values) and torch::tensor(empty braced-init-list) when dtype is not specified (#29632) 2019-11-13 15:17:11 -08:00
optim_baseline.h
optim_baseline.py
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 Fix bugs in torch::tensor constructor (#28523) 2019-10-31 12:53:06 -07:00
README.md
rnn.cpp Change C++ API test files to only include torch/torch.h (#27067) 2019-10-10 09:46:29 -07:00
sequential.cpp C++ API parity: Dropout, Dropout2d, Dropout3d 2019-11-15 20:32:06 -08:00
serialize.cpp Implement more of of the nn.Module API (#28828) 2019-11-06 22:58:25 -08:00
static.cpp
support.cpp Use default dtype for torch::tensor(floating_point_values) and torch::tensor(empty braced-init-list) when dtype is not specified (#29632) 2019-11-13 15:17:11 -08:00
support.h Use default dtype for torch::tensor(floating_point_values) and torch::tensor(empty braced-init-list) when dtype is not specified (#29632) 2019-11-13 15:17:11 -08:00
tensor.cpp Remove TensorImpl::is_variable, deprecate Tensor::is_variable (#29653) 2019-11-14 11:41:02 -08:00
tensor_cuda.cpp
tensor_options.cpp Use default dtype for torch::tensor(floating_point_values) and torch::tensor(empty braced-init-list) when dtype is not specified (#29632) 2019-11-13 15:17:11 -08:00
tensor_options_cuda.cpp Rename getNonVariableDeprecatedTypeProperties to getDeprecatedTypeProperties (#29203) 2019-11-13 07:43:32 -08:00
torch_include.cpp Relax set_num_threads restriction in parallel native case (#27947) 2019-10-16 21:53:36 -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.