tf.linalg.expm( input, name=None )
Defined in 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 [..., :, :]
.
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).A Tensor
. Has the same type as input
.
© 2018 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/linalg/expm