Warning: This API is deprecated and will be removed in a future version of TensorFlow after the replacement is stable.

Eig

public final class Eig

Computes the eigen decomposition of one or more square matrices.

Computes the eigenvalues and (optionally) right 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 = eig(a)
 e = eig(a, compute_v=False)
 

Nested Classes

class Eig.Options Optional attributes for Eig  

Public Methods

static Eig.Options
computeV(Boolean computeV)
static <U, T> Eig<U>
create(Scope scope, Operand<T> input, Class<U> Tout, Options... options)
Factory method to create a class wrapping a new Eig operation.
Output<U>
e()
Eigenvalues.
Output<U>
v()
Eigenvectors.

Inherited Methods

Public Methods

public static Eig.Options computeV (Boolean computeV)

Parameters
computeV If `True` then eigenvectors will be computed and returned in `v`. Otherwise, only the eigenvalues will be computed.

public static Eig<U> create (Scope scope, Operand<T> input, Class<U> Tout, Options... options)

Factory method to create a class wrapping a new Eig operation.

Parameters
scope current scope
input `Tensor` input of shape `[N, N]`.
options carries optional attributes values
Returns
  • a new instance of Eig

public Output<U> e ()

Eigenvalues. Shape is `[N]`.

public Output<U> v ()

Eigenvectors. Shape is `[N, N]`.