tf.linalg.eigvalsh
Computes the eigenvalues of one or more self-adjoint matrices.
tf.linalg.eigvalsh(
tensor, name=None
)
Note: If your program backpropagates through this function, you should replace it with a call to tf.linalg.eigh (possibly ignoring the second output) to avoid computing the eigen decomposition twice. This is because the eigenvectors are used to compute the gradient w.r.t. the eigenvalues. See _SelfAdjointEigV2Grad in linalg_grad.py.
| Args | |
|---|---|
tensor |
Tensor of shape [..., N, N]. |
name |
string, optional name of the operation. |
| Returns | |
|---|---|
e |
Eigenvalues. Shape is [..., N]. The vector e[..., :] contains the N eigenvalues of tensor[..., :, :]. |
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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/r2.3/api_docs/python/tf/linalg/eigvalsh