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
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/linalg/expm