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https://github.com/zebrajr/pytorch.git
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3ae721d350
Summary: Replaces the `DefaultTensorOptions` with just a global default dtype that you can set and get like in Python. Also, calls `set_default_dtype` in the implementation of `torch.set_default_dtype`. Right now these two default values are separate but will always be the same. Should we just bind `set_default_dtype` into Python? I think that might be good to do in a separate PR though. ezyang gchanan Also CC colesbury who wanted to do this for ATen for a while? What do you think about it? Pull Request resolved: https://github.com/pytorch/pytorch/pull/13748 Differential Revision: D13340207 Pulled By: goldsborough fbshipit-source-id: 2689b09eb137fabb3a92d1ad1635782bee9398e8 |
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|---|---|---|
| .. | ||
| any.cpp | ||
| CMakeLists.txt | ||
| dataloader.cpp | ||
| expanding-array.cpp | ||
| integration.cpp | ||
| jit.cpp | ||
| memory.cpp | ||
| misc.cpp | ||
| module.cpp | ||
| modules.cpp | ||
| optim_baseline.h | ||
| optim_baseline.py | ||
| optim.cpp | ||
| ordered_dict.cpp | ||
| parallel.cpp | ||
| README.md | ||
| rnn.cpp | ||
| sequential.cpp | ||
| serialize.cpp | ||
| static.cpp | ||
| support.h | ||
| tensor_cuda.cpp | ||
| tensor_options_cuda.cpp | ||
| tensor_options.cpp | ||
| tensor.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.