tf.linalg.eig
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Computes the eigen decomposition of a batch of matrices.
View aliases
Main aliases
tf.eig
tf.linalg.eig(
tensor, name=None
)
The eigenvalues
and eigenvectors for a non-Hermitian matrix in general are complex. The
eigenvectors are not guaranteed to be linearly independent.
Computes the eigenvalues and right eigenvectors of the innermost
N-by-N matrices in tensor such that
tensor[...,:,:] * v[..., :,i] = e[..., i] * v[...,:,i], for i=0...N-1.
Args |
|---|
tensor
|
Tensor of shape [..., N, N]. Only the lower triangular part of
each inner inner matrix is referenced.
|
name
|
string, optional name of the operation.
|
Returns |
|---|
e
|
Eigenvalues. Shape is [..., N]. The eigenvalues are not necessarily
ordered.
|
v
|
Eigenvectors. Shape is [..., N, N]. The columns of the inner most
matrices contain eigenvectors of the corresponding matrices in tensor
|
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Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tf.linalg.eig\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/ops/linalg_ops.py#L378-L407) |\n\nComputes the eigen decomposition of a batch of matrices.\n\n#### View aliases\n\n\n**Main aliases**\n\n[`tf.eig`](https://www.tensorflow.org/api_docs/python/tf/linalg/eig)\n\n\u003cbr /\u003e\n\n tf.linalg.eig(\n tensor, name=None\n )\n\nThe eigenvalues\nand eigenvectors for a non-Hermitian matrix in general are complex. The\neigenvectors are not guaranteed to be linearly independent.\n\nComputes the eigenvalues and right eigenvectors of the innermost\nN-by-N matrices in `tensor` such that\n`tensor[...,:,:] * v[..., :,i] = e[..., i] * v[...,:,i]`, for i=0...N-1.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------|-----------------------------------------------------------------------------------------------------------|\n| `tensor` | `Tensor` of shape `[..., N, N]`. Only the lower triangular part of each inner inner matrix is referenced. |\n| `name` | string, optional name of the operation. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|-----|---------------------------------------------------------------------------------------------------------------------------------------------|\n| `e` | Eigenvalues. Shape is `[..., N]`. The eigenvalues are not necessarily ordered. |\n| `v` | Eigenvectors. Shape is `[..., N, N]`. The columns of the inner most matrices contain eigenvectors of the corresponding matrices in `tensor` |\n\n\u003cbr /\u003e"]]
View source on GitHub