MatrixLogarithm

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public final class MatrixLogarithm

Computes the matrix logarithm of one or more square matrices:

\\(log(exp(A)) = A\\)

This op is only defined for complex matrices. If A is positive-definite and real, then casting to a complex matrix, taking the logarithm and casting back to a real matrix will give the correct result.

This function computes the matrix logarithm using the Schur-Parlett algorithm. Details of the algorithm can be found in Section 11.6.2 of: Nicholas J. Higham, Functions of Matrices: Theory and Computation, SIAM 2008. ISBN 978-0-898716-46-7.

The input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions form square matrices. The output is a tensor of the same shape as the input containing the exponential for all input submatrices `[..., :, :]`.

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> MatrixLogarithm<T>
create(Scope scope, Operand<T> input)
Factory method to create a class wrapping a new MatrixLogarithm 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: "MatrixLogarithm"

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

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

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

public Output<T> output ()

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