

dtype (torch.dtype, optional) -- if "None", this
        function returns a tensor with dtype "torch.int64".


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.randint(3, 5, (3,))
  tensor([4, 3, 4])


  >>> torch.randint(10, (2, 2))
  tensor([[0, 2],
          [5, 5]])


  >>> torch.randint(3, 10, (2, 2))
  tensor([[4, 5],
          [6, 7]])
