pytorch/test/cpp/api
Sebastian Messmer 800f4936f0 Deprecate untyped Lists (#22517)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/22517

Force anybody creating an untyped Dict to call c10::impl::deprecatedUntypedDict().
This should hopefully make it clear that this is not public API and prevent people from using it.

Reviewed By: dzhulgakov

Differential Revision: D16115214

fbshipit-source-id: 2c8d0e4e375339c699d583995f79c05c59693c3e
2019-07-15 11:33:35 -07:00
..
any.cpp Fix Windows build and test in CI (#11716) 2018-11-13 16:35:54 -08:00
CMakeLists.txt Switch to out-source builds for LibTorch 2019-06-14 21:00:18 -07:00
dataloader.cpp Add support for cross-chunk shuffling in ChunkDataset (#22347) 2019-07-01 19:13:34 -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 Deprecate untyped Lists (#22517) 2019-07-15 11:33:35 -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 Fixed RNNImplBase reset and flat_weights methods to handle bidirectional flag correctly (#22493) 2019-07-08 10:34:04 -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 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 Stop using Type in Python bindings (#21963) 2019-06-30 04:11:32 -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.