rank, singular_values). For inputs "A", "B" of shape (, m, n),
   (, m, k)* respectively, it contains


solution: the least squares solution. It has shape (, n, k)*.


residuals: the squared residuals of the solutions, that is,
     |AX - B|_F^2. It has shape equal to the batch dimensions of
     "A". It is computed when m > n and every matrix in "A" is full-
     rank, otherwise, it is an empty tensor. If "A" is a batch of
     matrices and any matrix in the batch is not full rank, then an
     empty tensor is returned. This behavior may change in a future
     PyTorch release.


rank: tensor of ranks of the matrices in "A". It has shape
     equal to the batch dimensions of "A". It is computed when
     "driver" is one of ('gelsy', 'gelsd', 'gelss'), otherwise
     it is an empty tensor.


singular_values: tensor of singular values of the matrices in
     "A". It has shape (, min(m, n))*. It is computed when "driver"

