pytorch/test/cpp/api
albanD 3655975565 Add allow_rebase_history flag and fix codegen functions for multiple views (#32790)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/32790

Same as https://github.com/pytorch/pytorch/pull/31990 but without the first commit in the stack that is problematic for a lot of people.

Test Plan: Imported from OSS

Differential Revision: D19814116

Pulled By: albanD

fbshipit-source-id: d104911a5b098a5807b4bc08b69803ebd4f69fa6
2020-02-11 07:16:02 -08:00
..
any.cpp Remove dead includes in caffe2/test 2020-01-21 11:30:34 -08:00
autograd.cpp Fix version counter bump in cpp Function (#33068) 2020-02-10 07:22:29 -08:00
CMakeLists.txt C++ tensor indexing: add Slice / TensorIndex (#30424) 2020-01-10 17:53:41 -08:00
dataloader.cpp Fix typos (#30606) 2019-12-02 20:17:42 -08:00
enum.cpp Use c10::variant-based enums for F::grid_sample 2019-11-12 16:05:26 -08:00
expanding-array.cpp
functional.cpp Fix torch::allclose to handle std::numeric_limits<T>::lowest() for integral types (#32978) 2020-02-04 19:06:52 -08:00
init.cpp Add allow_rebase_history flag and fix codegen functions for multiple views (#32790) 2020-02-11 07:16:02 -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
memory.cpp
misc.cpp
module.cpp Remove dead includes in caffe2/test 2020-01-21 11:30:34 -08:00
modulelist.cpp C++ API parity: Dropout, Dropout2d, Dropout3d 2019-11-15 20:32:06 -08:00
modules.cpp Remove dead includes in caffe2/test 2020-01-21 11:30:34 -08:00
nn_utils.cpp Remove dead includes in caffe2/test 2020-01-21 11:30:34 -08:00
optim.cpp Adagrad optimizer - updated step function, added param_groups, state to optimizers 2020-01-21 14:41:12 -08:00
optim_baseline.h
optim_baseline.py
ordered_dict.cpp
parallel.cpp
README.md
rnn.cpp Fix typos, via a Levenshtein-type corrector (#31523) 2020-01-17 16:03:19 -08:00
sequential.cpp C++ API parity: Dropout, Dropout2d, Dropout3d 2019-11-15 20:32:06 -08:00
serialize.cpp Adagrad optimizer - updated step function, added param_groups, state to optimizers 2020-01-21 14:41:12 -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 Exclude undefined tensors in the result of Module::parameters() / named_paramters() / buffers() / named_buffers() (#30626) 2019-12-02 21:59:58 -08:00
tensor.cpp Bug fixes: torch::tensor(floating-point values) -> default dtype, and torch::tensor(integer values) ->at::kLong (#32367) 2020-02-01 15:00:07 -08:00
tensor_cuda.cpp Fix MagmaInitializesCorrectly_CUDA by using an invertible matrix (#32547) 2020-01-25 20:00:54 -08:00
tensor_indexing.cpp Fix typo in config script to re-enable libtorch build and test in macOS CI (#32072) 2020-01-14 16:23:57 -08:00
tensor_options.cpp Deprecate tensor.type() (#30281) 2019-12-05 10:55:34 -08:00
tensor_options_cuda.cpp Deprecate tensor.type() (#30281) 2019-12-05 10:55:34 -08:00
torch_include.cpp

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.