Warning:
 If you plan to backpropagate through QR, note that the current
 backward implementation is only well-defined when the first
 \min(input.size(-1), input.size(-2)) columns of "input" are
 linearly independent. This behavior will probably change once QR
 supports pivoting.

Note:
 This function uses LAPACK for CPU inputs and MAGMA for CUDA
 inputs, and may produce different (valid) decompositions on
 different device types or different platforms.

Parameters:
      * input (Tensor) -- the input tensor of size (*, m, n)
        where *** is zero or more batch dimensions consisting of
        matrices of dimension m \times n.
  * **some** (*bool**, **optional*) --

    Set to "True" for reduced QR decomposition and "False" for
    complete QR decomposition. If *k = min(m, n)* then:

       * "some=True" : returns *(Q, R)* with dimensions (m, k),
         (k, n) (default)
