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https://github.com/zebrajr/pytorch.git
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52528c041a
Summary: Hi yf225 , I had to create a new branch to tackle merge conflict since I am using cloud due to some limitations on my PC. Therefore, I don't have enough command there. Also, I have incorporated the changes you have put before here https://github.com/pytorch/pytorch/pull/27613 Also, it would be great if you could recommend me some resources to work smmothly on GCP..:-D Thank you Pull Request resolved: https://github.com/pytorch/pytorch/pull/27713 Differential Revision: D17899695 Pulled By: yf225 fbshipit-source-id: eb6643223148774a5cbbd093bdcc5623872e5bba |
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| .. | ||
| any.cpp | ||
| autograd.cpp | ||
| CMakeLists.txt | ||
| dataloader.cpp | ||
| expanding-array.cpp | ||
| functional.cpp | ||
| init_baseline.h | ||
| init_baseline.py | ||
| init.cpp | ||
| integration.cpp | ||
| jit.cpp | ||
| memory.cpp | ||
| misc.cpp | ||
| module.cpp | ||
| modulelist.cpp | ||
| modules.cpp | ||
| nn_utils.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 | ||
| 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.