-
Notifications
You must be signed in to change notification settings - Fork 12
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
Showing
12 changed files
with
421 additions
and
253 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,134 @@ | ||
|
|
||
|
|
||
| # We should be able to handle these: | ||
|
|
||
|
|
||
| def issue1(): | ||
| # ISSUE: DOES NOT SKIP CORRECTLY | ||
|
|
||
| def foo1(): | ||
| """ | ||
| >>> # xdoctest: +SKIP("Undefined variables") | ||
| >>> @custom_sharded_op_impl(torch.nn.functional.linear) | ||
| >>> def my_custom_sharded_linear(types, args, kwargs, process_group): | ||
| >>> ... | ||
| >>> input = torch.rand(10, 32) | ||
| >>> weight = sharded_tensor.rand(32, 16) | ||
| >>> bias = torch.rand(16) | ||
| >>> # This will call 'my_custom_sharded_linear' | ||
| >>> torch.nn.functional.linear(input, weight, bias) | ||
| """ | ||
|
|
||
| # DOES SKIP CORRECTLY, WHY? | ||
| def foo2(): | ||
| """ | ||
| >>> @custom_sharded_op_impl(torch.nn.functional.linear) | ||
| >>> def my_custom_sharded_linear(types, args, kwargs, process_group): | ||
| >>> ... | ||
| >>> # xdoctest: +SKIP("Undefined variables") | ||
| >>> input = torch.rand(10, 32) | ||
| >>> weight = sharded_tensor.rand(32, 16) | ||
| >>> bias = torch.rand(16) | ||
| >>> # This will call 'my_custom_sharded_linear' | ||
| >>> torch.nn.functional.linear(input, weight, bias) | ||
| """ | ||
|
|
||
|
|
||
| def issue2(): | ||
| # Should be able to parse that setup | ||
| def CppExtension(name, sources, *args, **kwargs): | ||
| r''' | ||
| Creates a :class:`setuptools.Extension` for C++. | ||
| Convenience method that creates a :class:`setuptools.Extension` with the | ||
| bare minimum (but often sufficient) arguments to build a C++ extension. | ||
| All arguments are forwarded to the :class:`setuptools.Extension` | ||
| constructor. | ||
| Example: | ||
| >>> from setuptools import setup | ||
| >>> from torch.utils.cpp_extension import BuildExtension, CppExtension | ||
| >>> setup( | ||
| name='extension', | ||
| ext_modules=[ | ||
| CppExtension( | ||
| name='extension', | ||
| sources=['extension.cpp'], | ||
| extra_compile_args=['-g']), | ||
| ], | ||
| cmdclass={ | ||
| 'build_ext': BuildExtension | ||
| }) | ||
| ''' | ||
| include_dirs = kwargs.get('include_dirs', []) | ||
| include_dirs += include_paths() | ||
| kwargs['include_dirs'] = include_dirs | ||
|
|
||
| library_dirs = kwargs.get('library_dirs', []) | ||
| library_dirs += library_paths() | ||
| kwargs['library_dirs'] = library_dirs | ||
|
|
||
| libraries = kwargs.get('libraries', []) | ||
| libraries.append('c10') | ||
| libraries.append('torch') | ||
| libraries.append('torch_cpu') | ||
| libraries.append('torch_python') | ||
| kwargs['libraries'] = libraries | ||
|
|
||
| kwargs['language'] = 'c++' | ||
| return setuptools.Extension(name, sources, *args, **kwargs) | ||
|
|
||
| class LSTMCell(torch.nn.Module): | ||
| r"""A quantizable long short-term memory (LSTM) cell. | ||
| For the description and the argument types, please, refer to :class:`~torch.nn.LSTMCell` | ||
| Examples:: | ||
| >>> import torch.nn.quantizable as nnqa | ||
| >>> rnn = nnqa.LSTMCell(10, 20) | ||
| >>> input = torch.randn(3, 10) | ||
| >>> hx = torch.randn(3, 20) | ||
| >>> cx = torch.randn(3, 20) | ||
| >>> output = [] | ||
| >>> for i in range(6): | ||
| hx, cx = rnn(input[i], (hx, cx)) | ||
| output.append(hx) | ||
| """ | ||
| _FLOAT_MODULE = torch.nn.LSTMCell | ||
|
|
||
|
|
||
| def non_doctests(): | ||
| """ | ||
| ~/code/pytorch/torch/distributed/launch.py | ||
| 1. Single-Node multi-process distributed training | ||
| :: | ||
| >>> python -m torch.distributed.launch --nproc_per_node=NUM_GPUS_YOU_HAVE | ||
| YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 and all other | ||
| arguments of your training script) | ||
| 2. Multi-Node multi-process distributed training: (e.g. two nodes) | ||
| Node 1: *(IP: 192.168.1.1, and has a free port: 1234)* | ||
| :: | ||
| >>> python -m torch.distributed.launch --nproc_per_node=NUM_GPUS_YOU_HAVE | ||
| --nnodes=2 --node_rank=0 --master_addr="192.168.1.1" | ||
| --master_port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 | ||
| and all other arguments of your training script) | ||
| Node 2: | ||
| :: | ||
| >>> python -m torch.distributed.launch --nproc_per_node=NUM_GPUS_YOU_HAVE | ||
| --nnodes=2 --node_rank=1 --master_addr="192.168.1.1" | ||
| --master_port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 | ||
| and all other arguments of your training script) | ||
| """ |
Oops, something went wrong.