tf.linalg.expm | TensorFlow v2.16.1 (original) (raw)
tf.linalg.expm
Stay organized with collections Save and categorize content based on your preferences.
Computes the matrix exponential of one or more square matrices.
View aliases
Compat aliases for migration
SeeMigration guide for more details.
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, orcomplex128 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