returned tensor. Default: if "None", uses the current device
        for the default tensor type (see
        "torch.set_default_tensor_type()"). "device" will be the CPU
        for CPU tensor types and the current CUDA device for CUDA
        tensor types.
  * **requires_grad** (*bool**, **optional*) -- If autograd should
    record operations on the returned tensor. Default: "False".

  * **pin_memory** (*bool**, **optional*) -- If set, returned
    tensor would be allocated in the pinned memory. Works only for
    CPU tensors. Default: "False".

  * **memory_format** ("torch.memory_format", optional) -- the
    desired memory format of returned Tensor. Default:
    "torch.contiguous_format".

Example:
  >>> torch.empty((2,3), dtype=torch.int64)
  tensor([[ 9.4064e+13,  2.8000e+01,  9.3493e+13],
          [ 7.5751e+18,  7.1428e+18,  7.5955e+18]])
