pytorch/test/cpp/api
Will Feng eb7b39e02f Templatize Tensor.data_ptr() (#24847)
Summary:
This PR templatizes `Tensor.data_ptr()`, to prepare for the deprecation of `Tensor.data<T>()` and introduction of `Tensor.data()` that has the same semantics as `Variable.data()`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/24847

Differential Revision: D16906061

Pulled By: yf225

fbshipit-source-id: 8f9db9fd105b146598a9d759aa4b4332011da8ea
2019-08-19 17:02:18 -07:00
..
any.cpp
autograd.cpp Hooks for C++ API (#24393) 2019-08-16 12:44:20 -07:00
CMakeLists.txt C++ ModuleList 2019-08-19 10:02:40 -07:00
dataloader.cpp add sorting policy to ChunkDataset (#23053) 2019-07-29 12:34:02 -07:00
expanding-array.cpp
init.cpp
init_baseline.h
init_baseline.py
integration.cpp
jit.cpp Add Pickler C++ API (#23241) 2019-08-12 14:43:31 -07:00
memory.cpp
misc.cpp
module.cpp Avoid unnecessary tensor clone in Cloneable (#20995) 2019-07-26 12:46:42 -07:00
modulelist.cpp C++ ModuleList 2019-08-19 10:02:40 -07:00
modules.cpp
optim.cpp
optim_baseline.h
optim_baseline.py
ordered_dict.cpp
parallel.cpp Fix C++ data parallel (#20910) 2019-06-06 11:57:31 -07:00
README.md
rnn.cpp Bidirectional GRU and LSTM C++ API forward fix (#22850) 2019-07-22 12:59:47 -07:00
sequential.cpp Include named_any.h in modules.h (#21437) 2019-06-06 09:57:33 -07:00
serialize.cpp
static.cpp
support.h
tensor.cpp Templatize Tensor.data_ptr() (#24847) 2019-08-19 17:02:18 -07:00
tensor_cuda.cpp
tensor_options.cpp Revert D15920763: Move TensorOptions to ATen/core 2019-08-13 12:07:18 -07:00
tensor_options_cuda.cpp Revert D15920763: Move TensorOptions to ATen/core 2019-08-13 12:07:18 -07:00
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.