Computes the eigen decomposition of one or more square self-adjoint matrices.
tf.raw_ops.SelfAdjointEigV2(
input, compute_v=True, name=None
)
Computes the eigenvalues and (optionally) 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 = self_adjoint_eig(a)
e = self_adjoint_eig(a, compute_v=False)
Args | |
|---|---|
input
|
A Tensor. Must be one of the following types: float64, float32, half, complex64, complex128.
Tensor input of shape [N, N].
|
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. Has the same type as input.
|
v
|
A Tensor. Has the same type as input.
|