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[..., :, :]. |