tf.raw_ops.SelfAdjointEigV2

Computes the eigen decomposition of one or more square self-adjoint matrices.

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tf.compat.v1.raw_ops.SelfAdjointEigV2

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.