Note:
 When the inputs are on a CUDA device, this function synchronizes
 only when "check_errors"*= True*.

Warning:
 This function is "experimental" and it may change in a future
 PyTorch release.

See also:
 "torch.linalg.inv()" is a NumPy compatible variant that always
 checks for errors.

Parameters:
      * A (Tensor) -- tensor of shape (, n, n)* where *** is
        zero or more batch dimensions consisting of square matrices.
  * **check_errors** (*bool**, **optional*) -- controls whether to
    check the content of "info". Default: *False*.

Keyword Arguments:
      out (tuple, optional) -- tuple of two tensors to write
      the output to. Ignored if None. Default: None.
Examples:
  >>> A = torch.randn(3, 3)
  >>> Ainv, info = torch.linalg.inv_ex(A)
  >>> torch.dist(torch.linalg.inv(A), Ainv)
  tensor(0.)
  >>> info
  tensor(0, dtype=torch.int32)
