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# torch.set_default_device

torch.set_default_device(device)

  Sets the default `torch.Tensor` to be allocated on `device`. This does not affect factory function calls which are called with an explicit `device` argument. Factory calls will be performed as if they were passed `device` as an argument.

  To only temporarily change the default device instead of setting it globally, use `with torch.device(device):` instead.

  The default device is initially `cpu`. If you set the default tensor device to another device (e.g., `cuda`) without a device index, tensors will be allocated on whatever the current device for the device type, even after `torch.cuda.set_device()` is called.

  Warning

  This function imposes a slight performance cost on every Python call to the torch API (not just factory functions). If this is causing problems for you, please comment on https://github.com/pytorch/pytorch/issues/92701

  Parameters:

    device (device or string) – the device to set as default

  Example:

      >>> torch.tensor([1.2, 3]).device
      device(type='cpu')
      >>> torch.set_default_device('cuda')  # current device is 0
      >>> torch.tensor([1.2, 3]).device
      device(type='cuda', index=0)
      >>> torch.set_default_device('cuda:1')
      >>> torch.tensor([1.2, 3]).device
      device(type='cuda', index=1)

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