pytorch/test/cpp/api
peter bb788631ce Fix caffe2 windows CI for new Windows AMI (#21452)
Summary:
The alternative of #21410.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21452

Differential Revision: D15701767

Pulled By: ezyang

fbshipit-source-id: e65c1d6bfcc98e88460f4a57e5b99c2f395c0ceb
2019-06-06 13:46:45 -07:00
..
any.cpp Fix Windows build and test in CI (#11716) 2018-11-13 16:35:54 -08:00
CMakeLists.txt Fix caffe2 windows CI for new Windows AMI (#21452) 2019-06-06 13:46:45 -07:00
dataloader.cpp Refactor ChunkDataReader API + fix missing headers (#19485) 2019-05-08 22:20:19 -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 improve error message on inferred type (#21058) 2019-05-30 10:50:34 -07:00
memory.cpp Hide c10::optional and nullopt in torch namespace (#12927) 2018-10-26 00:08:04 -07:00
misc.cpp Kaiming Initialization (#14718) 2019-02-15 14:58:22 -08:00
module.cpp Apply modernize-use-override - 2/2 2019-02-13 21:01:28 -08:00
modules.cpp Rename BatchNorm running_variance to running_var (#17371) 2019-02-22 08:00:25 -08:00
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 Fix C++ data parallel (#20910) 2019-06-06 11:57:31 -07:00
README.md Rewrite C++ API tests in gtest (#11953) 2018-09-21 21:28:16 -07:00
rnn.cpp Pretty printing of C++ modules (#15326) 2018-12-19 21:55:49 -08:00
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 Use torch:: instead of at:: in all C++ APIs (#13523) 2018-11-06 14:32:25 -08:00
tensor_cuda.cpp push magma init into lazyInitCUDA (#18527) 2019-04-03 12:47:34 -07:00
tensor_options_cuda.cpp Add ScalarType argument to Type::options() (#19270) 2019-04-21 21:16:07 -07:00
tensor_options.cpp Add ScalarType argument to Type::options() (#19270) 2019-04-21 21:16:07 -07:00
tensor.cpp Rename _local_scalar to item() (#13676) 2018-12-04 13:19:26 -08:00
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.