perform the computation in. Default: if None, uses the global
        default dtype (see torch.get_default_dtype()) when both
        "start" and "end" are real, and corresponding complex dtype
        when either is complex.
  * **layout** ("torch.layout", optional) -- the desired layout of
    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".

Example:
  >>> torch.linspace(3, 10, steps=5)
  tensor([  3.0000,   4.7500,   6.5000,   8.2500,  10.0000])
  >>> torch.linspace(-10, 10, steps=5)
