Computes the eigen decomposition of one or more square matrices.
tf.raw_ops.Eig( input, Tout, compute_v=True, name=None )
Computes the eigenvalues and (optionally) right eigenvectors of each inner matrix in input
such that input[..., :, :] = v[..., :, :] * diag(e[..., :])
. The eigenvalues are sorted in non-decreasing order.
# a is a tensor. # e is a tensor of eigenvalues. # v is a tensor of eigenvectors. e, v = eig(a) e = eig(a, compute_v=False)
Args | |
---|---|
input | A Tensor . Must be one of the following types: float32 , float64 , complex64 , complex128 . Tensor input of shape [N, N] . |
Tout | A tf.DType from: tf.complex64, tf.complex128 . |
compute_v | An optional bool . Defaults to True . If True then eigenvectors will be computed and returned in v . Otherwise, only the eigenvalues will be computed. |
name | A name for the operation (optional). |
Returns | |
---|---|
A tuple of Tensor objects (e, v). | |
e | A Tensor of type Tout . |
v | A Tensor of type Tout . |
© 2020 The TensorFlow Authors. All rights reserved.
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/raw_ops/Eig