tf.raw_ops.SelfAdjointEigV2
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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 .
|
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Last updated 2022-10-27 UTC.
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