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]`