Computes the singular values of a matrix.

Supports input of float, double, cfloat and cdouble dtypes. Also supports batches of matrices, and if A is a batch of matrices then the output has the same batch dimensions. The singular values are returned in descending order.

Usage

linalg_svdvals(A)

Arguments

A

(Tensor): tensor of shape (*, m, n) where * is zero or more batch dimensions.

Value

A real-valued tensor, even when A is complex.

See also

linalg_svd() computes the full singular value decomposition.

Other linalg: linalg_cholesky(), linalg_cholesky_ex(), linalg_det(), linalg_eig(), linalg_eigh(), linalg_eigvals(), linalg_eigvalsh(), linalg_householder_product(), linalg_inv(), linalg_inv_ex(), linalg_lstsq(), linalg_matrix_norm(), linalg_matrix_power(), linalg_matrix_rank(), linalg_multi_dot(), linalg_norm(), linalg_pinv(), linalg_qr(), linalg_slogdet(), linalg_solve(), linalg_solve_triangular(), linalg_svd(), linalg_tensorinv(), linalg_tensorsolve(), linalg_vector_norm()

Examples

if (torch_is_installed()) {
A <- torch_randn(5, 3)
S <- linalg_svdvals(A)
S
}
#> torch_tensor
#>  2.6906
#>  1.5760
#>  0.8236
#> [ CPUFloatType{3} ]