underlying storage of the output tensor. If "None", the
        storage_offset of the output tensor will match the input
        tensor.
Example:
  >>> x = torch.randn(3, 3)
  >>> x
  tensor([[ 0.9039,  0.6291,  1.0795],
          [ 0.1586,  2.1939, -0.4900],
          [-0.1909, -0.7503,  1.9355]])
  >>> t = torch.as_strided(x, (2, 2), (1, 2))
  >>> t
  tensor([[0.9039, 1.0795],
          [0.6291, 0.1586]])
  >>> t = torch.as_strided(x, (2, 2), (1, 2), 1)
  tensor([[0.6291, 0.1586],
          [1.0795, 2.1939]])
