returned Tensor. Default: "torch.strided".
  * **device** ("torch.device", optional) -- the desired device of
    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".

Example:
  >>> torch.rand(4)
  tensor([ 0.5204,  0.2503,  0.3525,  0.5673])
  >>> torch.rand(2, 3)
  tensor([[ 0.8237,  0.5781,  0.6879],
          [ 0.3816,  0.7249,  0.0998]])
