# tf.linalg.expm

Computes the matrix exponential of one or more square matrices.

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


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 found 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 float16, float32, float64, complex64, or complex128 with shape [..., M, M].
• name: A name to give this Op (optional).

#### Returns:

the matrix exponential of the input.

#### Raises:

• ValueError: An unsupported type is provided as input.

#### Scipy Compatibility

Equivalent to scipy.linalg.expm