FM / cuda

/usr/local/lib64/python3.6/site-packages/torch/cuda/

/usr/local/lib64/python3.6/site-packages/torch/cuda

Name	Size	Mode	Actions
amp/	-	0755	rm
__pycache__/	-	0755	rm
comm.py	293	0644	edit dl rm
error.py	0	0644	edit dl rm
graphs.py	18835	0644	edit dl rm
memory.py	22599	0644	edit dl rm
nccl.py	3942	0644	edit dl rm
nvtx.py	1508	0644	edit dl rm
profiler.py	1221	0644	edit dl rm
random.py	5223	0644	edit dl rm
sparse.py	67	0644	edit dl rm
streams.py	8093	0644	edit dl rm
_utils.py	1845	0644	edit dl rm
__init__.py	24370	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/torch/cuda/_utils.py (1845B)

import torch
from typing import Any
# The _get_device_index has been moved to torch.utils._get_device_index
from torch._utils import _get_device_index as _torch_get_device_index

def _get_device_index(device: Any, optional: bool = False,
                      allow_cpu: bool = False) -> int:
    r"""Gets the device index from :attr:`device`, which can be a torch.device
    object, a Python integer, or ``None``.

If :attr:`device` is a torch.device object, returns the device index if it
    is a CUDA device. Note that for a CUDA device without a specified index,
    i.e., ``torch.device('cuda')``, this will return the current default CUDA
    device if :attr:`optional` is ``True``. If :attr:`allow_cpu` is ``True``,
    CPU devices will be accepted and ``-1`` will be returned in this case.

If :attr:`device` is a Python integer, it is returned as is.

If :attr:`device` is ``None``, this will return the current default CUDA
    device if :attr:`optional` is ``True``.
    """
    if isinstance(device, str):
        device = torch.device(device)
    if isinstance(device, torch.device):
        if allow_cpu:
            if device.type not in ['cuda', 'cpu']:
                raise ValueError('Expected a cuda or cpu device, but got: {}'.format(device))
        elif device.type != 'cuda':
            raise ValueError('Expected a cuda device, but got: {}'.format(device))
    if not torch.jit.is_scripting():
        if isinstance(device, torch.cuda.device):
            return device.idx
    return _torch_get_device_index(device, optional, allow_cpu)

def _dummy_type(name: str) -> type:
    def init_err(self):
        class_name = self.__class__.__name__
        raise RuntimeError(
            "Tried to instantiate dummy base class {}".format(class_name))
    return type(name, (object,), {"__init__": init_err})

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