SelfAdjointEig

public final class SelfAdjointEig

Computes the eigen decomposition of a batch of self-adjoint matrices

(Note: Only real inputs are supported).

Computes the eigenvalues and eigenvectors of the innermost N-by-N matrices in tensor such that tensor[...,:,:] * v[..., :,i] = e[..., i] * v[...,:,i], for i=0...N-1.

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

static <T extends TType> SelfAdjointEig<T>	create(Scope scope, Operand<T> a, Boolean lower, Long maxIter, Float epsilon) Factory method to create a class wrapping a new SelfAdjointEig operation.
Output<T>	v() The column v[..., :, i] is the normalized eigenvector corresponding to the eigenvalue w[..., i].
Output<T>	w() The eigenvalues in ascending order, each repeated according to its multiplicity.

Inherited Methods

From class org.tensorflow.op.RawOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Return this unit of computation as a single `Operation`.
final String	toString()

From class java.lang.Object

boolean	equals(Object arg0)
final Class<?>	getClass()
int	hashCode()
final void	notify()
final void	notifyAll()
String	toString()
final void	wait(long arg0, int arg1)
final void	wait(long arg0)
final void	wait()

From interface org.tensorflow.op.Op

abstract ExecutionEnvironment	env() Return the execution environment this op was created in.
abstract Operation	op() Return this unit of computation as a single `Operation`.

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "XlaSelfAdjointEig"

Public Methods

public static SelfAdjointEig<T> create (Scope scope, Operand<T> a, Boolean lower, Long maxIter, Float epsilon)

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

Parameters

scope	current scope
a	the input tensor.
lower	a boolean specifies whether the calculation is done with the lower triangular part or the upper triangular part.
maxIter	maximum number of sweep update, i.e., the whole lower triangular part or upper triangular part based on parameter lower. Heuristically, it has been argued that approximately logN sweeps are needed in practice (Ref: Golub & van Loan "Matrix Computation").
epsilon	the tolerance ratio.

Returns

a new instance of SelfAdjointEig

public Output<T> v ()

The column v[..., :, i] is the normalized eigenvector corresponding to the eigenvalue w[..., i].

public Output<T> w ()

The eigenvalues in ascending order, each repeated according to its multiplicity.