tf.self_adjoint_eigvals

Aliases:

• tf.linalg.eigvalsh
• tf.self_adjoint_eigvals

tf.self_adjoint_eigvals(
    tensor,
    name=None
)

Defined in tensorflow/python/ops/linalg_ops.py.

See the guide: Math > Matrix Math Functions

Computes the eigenvalues of one or more self-adjoint matrices.

Note: If your program backpropagates through this function, you should replace it with a call to tf.self_adjoint_eig (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[..., :, :].