linalg.tensorsolve(A, B) == torch.tensordot(linalg.tensorinv(A), B)  # When B is a tensor with shape A.shape[:B.ndim]
 It is always preferred to use "tensorsolve()" when possible, as
 it is faster and more numerically stable than computing the
 pseudoinverse explicitly.

See also:
 "torch.linalg.tensorsolve()" computes
 *torch.tensordot(tensorinv(*"A"*), *"B"*)*.

Parameters:
      * A (Tensor) -- tensor to invert. Its shape must satisfy
        prod("A".shape[:"ind"]) == prod("A".shape["ind":]).
  * **ind** (*int*) -- index at which to compute the inverse of
    "torch.tensordot()". Default: *2*.

Keyword Arguments:
      out (Tensor, optional) -- output tensor. Ignored if
      None. Default: None.
Raises:
      RuntimeError -- if the reshaped "A" is not invertible or the
      product of the first     "ind" dimensions is not equal to the
      product of the rest.
Examples: