Have a question? Connect with the community at the TensorFlow Forum Visit Forum

CholeskyGrad

public final class CholeskyGrad

Computes the reverse mode backpropagated gradient of the Cholesky algorithm.

For an explanation see "Differentiation of the Cholesky algorithm" by Iain Murray http://arxiv.org/abs/1602.07527.

Constants

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

Public Methods

Output <T>
asOutput ()
Returns the symbolic handle of the tensor.
static <T extends TNumber > CholeskyGrad <T>
create ( Scope scope, Operand <T> l, Operand <T> grad)
Factory method to create a class wrapping a new CholeskyGrad operation.
Output <T>
output ()
Symmetrized version of df/dA .

Inherited Methods

Constants

public static final String OP_NAME

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

Constant Value: "CholeskyGrad"

Public Methods

public Output <T> asOutput ()

Returns the symbolic handle of the tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static CholeskyGrad <T> create ( Scope scope, Operand <T> l, Operand <T> grad)

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

Parameters
scope current scope
l Output of batch Cholesky algorithm l = cholesky(A). Shape is `[..., M, M]`. Algorithm depends only on lower triangular part of the innermost matrices of this tensor.
grad df/dl where f is some scalar function. Shape is `[..., M, M]`. Algorithm depends only on lower triangular part of the innermost matrices of this tensor.
Returns
  • a new instance of CholeskyGrad

public Output <T> output ()

Symmetrized version of df/dA . Shape is `[..., M, M]`