tf.linalg.logm  |  TensorFlow v2.16.1 (original) (raw)

tf.linalg.logm

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Computes the matrix logarithm of one or more square matrices:

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tf.compat.v1.linalg.logm

tf.linalg.logm(
    input: Annotated[Any, TV_MatrixLogarithm_T], name=None
) -> Annotated[Any, TV_MatrixLogarithm_T]

\(log(exp(A)) = A\)

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 [..., :, :].