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Cholesky

public final class Cholesky

Computes the Cholesky decomposition of one or more square matrices.

The input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions form square matrices.

The input has to be symmetric and positive definite. Only the lower-triangular part of the input will be used for this operation. The upper-triangular part will not be read.

The output is a tensor of the same shape as the input containing the Cholesky decompositions for all input submatrices `[..., :, :]`.

Note : The gradient computation on GPU is faster for large matrices but not for large batch dimensions when the submatrices are small. In this case it might be faster to use the CPU.

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 TType > Cholesky <T>
create ( Scope scope, Operand <T> input)
Factory method to create a class wrapping a new Cholesky operation.
Output <T>
output ()
Shape is `[..., M, M]`.

Inherited Methods

Constants

public static final String OP_NAME

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

Constant Value: "Cholesky"

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 Cholesky <T> create ( Scope scope, Operand <T> input)

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

Parameters
scope current scope
input Shape is `[..., M, M]`.
Returns
  • a new instance of Cholesky

public Output <T> output ()

Shape is `[..., M, M]`.