tf.linalg.logm
Computes the matrix logarithm of one or more square matrices:
tf.linalg.logm( input, name=None )
\(log(exp(A)) = A\)
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 | |
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input | A Tensor . Must be one of the following types: complex64 , complex128 . Shape is [..., M, M] . |
name | A name for the operation (optional). |
Returns | |
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A Tensor . Has the same type as input . |
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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/r2.4/api_docs/python/tf/linalg/logm