torch.linalg.matrix_exp
torch.linalg.matrix_exp(A) -> Tensor
Computes the matrix exponential of a square matrix.
Letting \mathbb{K} be \mathbb{R} or \mathbb{C}, this function
   computes the matrix exponential of A \in \mathbb{K}^{n \times
   n}, which is defined as
  \mathrm{matrix_exp}(A) = \sum_{k=0}^\infty \frac{1}{k!}A^k \in
  \mathbb{K}^{n \times n}.

If the matrix A has eigenvalues \lambda_i \in \mathbb{C}, the
   matrix \mathrm{matrix_exp}(A) has eigenvalues e^{\lambda_i} \in
   \mathbb{C}.
Supports input of bfloat16, float, double, cfloat and cdouble
   dtypes. Also supports batches of matrices, and if "A" is a batch of
   matrices then the output has the same batch dimensions.
Parameters:
      A (Tensor) -- tensor of shape (, n, n)* where *** is
      zero or more batch dimensions.
Example:
  >>> A = torch.empty(2, 2, 2)
  >>> A[0, :, :] = torch.eye(2, 2)
  >>> A[1, :, :] = 2 * torch.eye(2, 2)
  >>> A
