tf.raw_ops.MatrixLogarithm
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Computes the matrix logarithm of one or more square matrices:
tf.raw_ops.MatrixLogarithm(
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 |
|---|
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.
|
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Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf.raw_ops.MatrixLogarithm\n\nComputes the matrix logarithm of one or more square matrices:\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.raw_ops.MatrixLogarithm`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/MatrixLogarithm)\n\n\u003cbr /\u003e\n\n tf.raw_ops.MatrixLogarithm(\n input, name=None\n )\n\n\\\\(log(exp(A)) = A\\\\)\n\nThis op is only defined for complex matrices. If A is positive-definite and\nreal, then casting to a complex matrix, taking the logarithm and casting back\nto a real matrix will give the correct result.\n\nThis function computes the matrix logarithm using the Schur-Parlett algorithm.\nDetails of the algorithm can be found in Section 11.6.2 of:\nNicholas J. Higham, Functions of Matrices: Theory and Computation, SIAM 2008.\nISBN 978-0-898716-46-7.\n\nThe input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions\nform square matrices. The output is a tensor of the same shape as the input\ncontaining the exponential for all input submatrices `[..., :, :]`.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------|----------------------------------------------------------------------------------------------------|\n| `input` | A `Tensor`. Must be one of the following types: `complex64`, `complex128`. Shape is `[..., M, M]`. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor`. Has the same type as `input`. ||\n\n\u003cbr /\u003e"]]
