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# Motivation Refactor utils code to make it possible to share across CUDA, XPU, and other backends. # Solution Move `_dummy_type` and `_LazySeedTracker` to torch._utils; # Additional Context When upstreaming, refactor these code changes by isolating them into in an additional PR to minimize their impact on the CUDA code. Pull Request resolved: https://github.com/pytorch/pytorch/pull/120602 Approved by: https://github.com/albanD, https://github.com/jgong5, https://github.com/gujinghui, https://github.com/EikanWang
39 lines
1.6 KiB
Python
39 lines
1.6 KiB
Python
from typing import Any
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import torch
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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(
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device: Any, optional: bool = False, allow_cpu: bool = False
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) -> int:
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r"""Get the device index from :attr:`device`, which can be a torch.device 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, int):
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return device
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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(f"Expected a cuda or cpu device, but got: {device}")
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elif device.type != "cuda":
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raise ValueError(f"Expected a cuda device, but got: {device}")
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if not torch.jit.is_scripting():
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if isinstance(device, torch.cuda.device):
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return device.idx
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return _torch_get_device_index(device, optional, allow_cpu)
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