cross-product in.
Keyword Arguments:
      out (Tensor, optional) -- the output tensor.
Example:
  >>> a = torch.randn(4, 3)
  >>> a
  tensor([[-0.3956,  1.1455,  1.6895],
          [-0.5849,  1.3672,  0.3599],
          [-1.1626,  0.7180, -0.0521],
          [-0.1339,  0.9902, -2.0225]])
  >>> b = torch.randn(4, 3)
  >>> b
  tensor([[-0.0257, -1.4725, -1.2251],
          [-1.1479, -0.7005, -1.9757],
          [-1.3904,  0.3726, -1.1836],
          [-0.9688, -0.7153,  0.2159]])
  >>> torch.cross(a, b, dim=1)
  tensor([[ 1.0844, -0.5281,  0.6120],
          [-2.4490, -1.5687,  1.9792],
          [-0.8304, -1.3037,  0.5650],
          [-1.2329,  1.9883,  1.0551]])
  >>> torch.cross(a, b)
  tensor([[ 1.0844, -0.5281,  0.6120],
          [-2.4490, -1.5687,  1.9792],
          [-0.8304, -1.3037,  0.5650],
          [-1.2329,  1.9883,  1.0551]])
