tf.linalg.expm
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Computes the matrix exponential of one or more square matrices.
tf.linalg.expm(
input, name=None
)
\[exp(A) = \sum_{n=0}^\infty A^n/n!\]
The exponential is computed using a combination of the scaling and squaring
method and the Pade approximation. Details can be found 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 [..., :, :].
Args |
|---|
input
|
A Tensor. Must be float16, float32, float64, complex64, or
complex128 with shape [..., M, M].
|
name
|
A name to give this Op (optional).
|
Returns |
|---|
|
the matrix exponential of the input.
|
Raises |
|---|
ValueError
|
An unsupported type is provided as input.
|
Equivalent to scipy.linalg.expm
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Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf.linalg.expm\n\n|--------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/linalg/linalg_impl.py#L232-L347) |\n\nComputes the matrix exponential 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.linalg.expm`](https://www.tensorflow.org/api_docs/python/tf/linalg/expm)\n\n\u003cbr /\u003e\n\n tf.linalg.expm(\n input, name=None\n )\n\n\\\\\\[exp(A) = \\\\sum_{n=0}\\^\\\\infty A\\^n/n!\\\\\\]\n\nThe exponential is computed using a combination of the scaling and squaring\nmethod and the Pade approximation. Details can be found in:\nNicholas J. Higham, \"The scaling and squaring method for the matrix\nexponential revisited,\" SIAM J. Matrix Anal. Applic., 26:1179-1193, 2005.\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 `float16`, `float32`, `float64`, `complex64`, or `complex128` with shape `[..., M, M]`. |\n| `name` | A name to give this `Op` (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| the matrix exponential of the input. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|--------------|-------------------------------------------|\n| `ValueError` | An unsupported type is provided as input. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\nscipy compatibility\n-------------------\n\n\u003cbr /\u003e\n\nEquivalent to scipy.linalg.expm\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e"]]
View source on GitHub