torch_matrix_rank: Matrix_rank

In torch: Tensors and Neural Networks with 'GPU' Acceleration

Matrix_rank

Description

Matrix_rank

Arguments

self	(Tensor) the input 2-D tensor
tol	(float, optional) the tolerance value. Default: NULL
symmetric	(bool, optional) indicates whether input is symmetric. Default: FALSE

matrix_rank(input, tol=NULL, symmetric=False) -> Tensor

Returns the numerical rank of a 2-D tensor. The method to compute the matrix rank is done using SVD by default. If symmetric is TRUE, then input is assumed to be symmetric, and the computation of the rank is done by obtaining the eigenvalues.

tol is the threshold below which the singular values (or the eigenvalues when symmetric is TRUE) are considered to be 0. If tol is not specified, tol is set to S.max() * max(S.size()) * eps where S is the singular values (or the eigenvalues when symmetric is TRUE), and eps is the epsilon value for the datatype of input.

torch documentation built on May 29, 2024, 9:54 a.m.