svdvals(x: array, /) array

Returns the singular values of a matrix (or a stack of matrices) x.

When x is a stack of matrices, the function must compute the singular values for each matrix in the stack.


x (array) – input array having shape (..., M, N) and whose innermost two dimensions form matrices on which to perform singular value decomposition. Should have a floating-point data type.


out (array) – an array with shape (..., K) that contains the vector(s) of singular values of length K, where K = min(M, N). For each vector, the singular values must be sorted in descending order by magnitude, such that s[..., 0] is the largest value, s[..., 1] is the second largest value, et cetera. The first x.ndim-2 dimensions must have the same shape as those of the input x. The returned array must have a real-valued floating-point data type having the same precision as x (e.g., if x is complex64, the returned array must have a float32 data type).


Changed in version 2022.12: Added complex data type support.