points.
Parameters:
      * A (Tensor) -- tensor of shape (, m, n)* where *** is
        zero or more batch dimensions.
  * **pivot** (*bool**, **optional*) -- Controls whether to
    compute the LU decomposition with partial pivoting or no
    pivoting. Default: *True*.

Keyword Arguments:
      out (tuple, optional) -- output tuple of three
      tensors. Ignored if None. Default: None.
Returns:
      A named tuple (P, L, U).
Examples:
  >>> A = torch.randn(3, 2)
  >>> P, L, U = torch.linalg.lu(A)
  >>> P
  tensor([[0., 1., 0.],
          [0., 0., 1.],
          [1., 0., 0.]])
  >>> L
  tensor([[1.0000, 0.0000],
          [0.5007, 1.0000],
          [0.0633, 0.9755]])
  >>> U
  tensor([[0.3771, 0.0489],
          [0.0000, 0.9644]])
  >>> torch.dist(A, P @ L @ U)
  tensor(5.9605e-08)

  >>> A = torch.randn(2, 5, 7, device="cuda")
  >>> P, L, U = torch.linalg.lu(A, pivot=False)
