Matrix_rank
Matrix_rank
torch_matrix_rank(self, tol, symmetric = FALSE)
self |
(Tensor) the input 2-D tensor |
tol |
(float, optional) the tolerance value. Default: |
symmetric |
(bool, optional) indicates whether |
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.
if (torch_is_installed()) {
a = torch_eye(10)
torch_matrix_rank(a)
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