5 examples of 'pytorch cuda 11.4' in Python

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def cuda(xs, gpu_id):
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    if torch.cuda.is_available():
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        if not isinstance(xs, (list, tuple)):
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            return xs.cuda(int(gpu_id[0]))
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        else:
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            return [x.cuda(int(gpu_id[0])) for x in xs]
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    return xs

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def to_cuda(list_modules):
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    for m in list_modules:
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        m.cuda()

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def _tensor_to_cuda(x):
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    if x.is_cuda:
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        return x
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    else:
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        return x.cuda()

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@pytest.mark.skipif(not torch.cuda.is_available(), reason="Require cuda")
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def test_to_device_cuda():
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    obj = {"a": [torch.tensor([0, 1])]}
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    obj2 = to_device(obj, "cuda")
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    assert obj2["a"][0].device == torch.device("cuda:0")

770
def cuda(self, device_id=None):
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    """
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    This method operates identically to :func:`torch.nn.Module.cuda`.
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    Args:
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        device_id (:obj:`str`, optional):
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            Device ID of GPU to use.
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    Returns:
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        :obj:`~gpytorch.lazy.LazyTensor`:
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            a new LazyTensor identical to ``self``, but on the GPU.
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    """
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    new_args = []
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    new_kwargs = {}
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    for arg in self._args:
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        if hasattr(arg, "cuda"):
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            new_args.append(arg.cuda(device_id))
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        else:
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            new_args.append(arg)
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    for name, val in self._kwargs.items():
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        if hasattr(val, "cuda"):
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            new_kwargs[name] = val.cuda(device_id)
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        else:
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            new_kwargs[name] = val
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    return self.__class__(*new_args, **new_kwargs)