linalg_svdvals: Computes the singular values of a matrix.

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

Computes the singular values of a matrix.

Description

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_ex(), linalg_cholesky(), linalg_det(), linalg_eigh(), linalg_eigvalsh(), linalg_eigvals(), linalg_eig(), linalg_householder_product(), linalg_inv_ex(), linalg_inv(), linalg_lstsq(), linalg_matrix_norm(), linalg_matrix_power(), linalg_matrix_rank(), linalg_multi_dot(), linalg_norm(), linalg_pinv(), linalg_qr(), linalg_slogdet(), linalg_solve_triangular(), linalg_solve(), 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 documentation built on May 29, 2024, 9:54 a.m.