# tf.linalg.expm

tf.linalg.expm(
input,
name=None
)


Defined in generated file: tensorflow/python/ops/gen_linalg_ops.py.

Computes the matrix exponential of one or more square matrices:

exp(A) = \sum_{n=0}^\infty A^n/n!

The exponential is computed using a combination of the scaling and squaring method and the Pade approximation. Details can be founds in: Nicholas J. Higham, "The scaling and squaring method for the matrix exponential revisited," SIAM J. Matrix Anal. Applic., 26:1179-1193, 2005.

The input is a tensor of shape [..., M, M] whose inner-most 2 dimensions form square matrices. The output is a tensor of the same shape as the input containing the exponential for all input submatrices [..., :, :].

#### Args:

• input: A Tensor. Must be one of the following types: float64, float32, complex64, complex128. Shape is [..., M, M].
• name: A name for the operation (optional).

#### Returns:

A Tensor. Has the same type as input.