As such, the returned QR decomposition is only unique up to the
     sign of the diagonal of R. Therefore, different platforms, like
     NumPy, or inputs on different devices, may produce different
     valid decompositions.
Warning:
 The QR decomposition is only well-defined if the first *k =
 min(m, n)* columns of every matrix in "A" are linearly
 independent. If this condition is not met, no error will be
 thrown, but the QR produced may be incorrect and its autodiff may
 fail or produce incorrect results.

Parameters:
      * A (Tensor) -- tensor of shape (, m, n)* where *** is
        zero or more batch dimensions.
  * **mode** (*str**, **optional*) -- one of *'reduced'*,
    *'complete'*, *'r'*. Controls the shape of the returned
    tensors. Default: *'reduced'*.

Keyword Arguments:
      out (tuple, optional) -- output tuple of two tensors.
      Ignored if None. Default: None.
Returns:
      A named tuple (Q, R).