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8d570bc708
Summary: Decouple DataParallel/DistributedDataParallel from CUDA to support more device types. - Move torch/cuda/comm.py to torch/nn/parallel/comm.py with minor changes for common devices support. Torch.cuda.comm is kept as is for backward compatibility - Provide common APIs to arbitrary device types without changing existing CUDA APIs in torch.cuda space. - Replace the torch.cuda calls in DataParellel/DistributedDataParallel with the new APIs. Related RFC: [https://github.com/pytorch/pytorch/issues/36160](https://github.com/pytorch/pytorch/issues/36160) Pull Request resolved: https://github.com/pytorch/pytorch/pull/38454 Differential Revision: D22051557 Pulled By: mrshenli fbshipit-source-id: 7842dad0e5d3ca0f6fb760bda49182dcf6653af8
41 lines
1.7 KiB
Python
41 lines
1.7 KiB
Python
import torch
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from typing import Union
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from torch.types import Device
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# The _get_device_index has been moved to torch.utils._get_device_index
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from torch._utils import _get_device_index as _torch_get_device_index
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def _get_device_index(device: Union[Device, str, int], optional: bool = False,
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allow_cpu: bool = False) -> int:
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r"""Gets the device index from :attr:`device`, which can be a torch.device
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object, a Python integer, or ``None``.
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If :attr:`device` is a torch.device object, returns the device index if it
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is a CUDA device. Note that for a CUDA device without a specified index,
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i.e., ``torch.device('cuda')``, this will return the current default CUDA
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device if :attr:`optional` is ``True``. If :attr:`allow_cpu` is ``True``,
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CPU devices will be accepted and ``-1`` will be returned in this case.
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If :attr:`device` is a Python integer, it is returned as is.
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If :attr:`device` is ``None``, this will return the current default CUDA
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device if :attr:`optional` is ``True``.
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"""
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if isinstance(device, str):
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device = torch.device(device)
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if isinstance(device, torch.device):
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if allow_cpu:
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if device.type not in {'cuda', 'cpu'}:
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raise ValueError('Expected a cuda or cpu device, but got: {}'.format(device))
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elif device.type != 'cuda':
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raise ValueError('Expected a cuda device, but got: {}'.format(device))
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return _torch_get_device_index(device, optional, allow_cpu)
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def _dummy_type(name: str) -> type:
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def init_err(self):
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class_name = self.__class__.__name__
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raise RuntimeError(
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"Tried to instantiate dummy base class {}".format(class_name))
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return type(name, (object,), {"__init__": init_err})
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