close to not being full rank, the gradient will be numerically
     unstable as it depends on the computation of L^{-1} and U^{-1}.
Parameters:
      * A (Tensor) -- the tensor to factor of size (*, m, n)
  * **pivot** (*bool**, **optional*) -- controls whether pivoting
    is done. Default: "True"

  * **get_infos** (*bool**, **optional*) -- if set to "True",
    returns an info IntTensor. Default: "False"

  * **out** (*tuple**, **optional*) -- optional output tuple. If
    "get_infos" is "True", then the elements in the tuple are
    Tensor, IntTensor, and IntTensor. If "get_infos" is "False",
    then the elements in the tuple are Tensor, IntTensor. Default:
    "None"

Returns:
      A tuple of tensors containing
     * **factorization** (*Tensor*): the factorization of size (*,
       m, n)

     * **pivots** (*IntTensor*): the pivots of size (*,
       \text{min}(m, n)). "pivots" stores all the intermediate
