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tf.linalg.logm

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

Defined in tensorflow/python/ops/gen_linalg_ops.py.

Computes the matrix logarithm of one or more square matrices:

log(exp(A)) = A

This op is only defined for complex matrices. If A is positive-definite and real, then casting to a complex matrix, taking the logarithm and casting back to a real matrix will give the correct result.

This function computes the matrix logarithm using the Schur-Parlett algorithm. Details of the algorithm can be found in Section 11.6.2 of: Nicholas J. Higham, Functions of Matrices: Theory and Computation, SIAM 2008. ISBN 978-0-898716-46-7.

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: complex64, complex128. Shape is [..., M, M].
  • name: A name for the operation (optional).

Returns:

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/logm