code: def svdvals(a):
      r"""
      Computes the singular values of a matrix (or a stack of matrices) `x`.
  
      Parameters
      ----------
      a : (..., M, N) ndarray
          A real array with ``a.ndim >= 2`` and ``M <= N``.
  
      Returns
      -------
      out : (..., M) ndarray
          Vector(s) with the singular values, within each vector sorted in
          descending order. The first ``a.ndim - 2`` dimensions have the same
          size as those of the input `a`.
  
      .. note::
         `svdvals` is a standard api in
         https://data-apis.org/array-api/latest/extensions/linear_algebra_functions.html#linalg-svdvals-x
         instead of an official NumPy operator.
      """
      _, s, _ = _mx_nd_np.linalg.svd(a)
      return s
  
imports: from functools import reduce
  from ..ndarray import numpy
  from ..util import wrap_data_api_linalg_func
  from .fallback_linalg import *
  from .None import fallback_linalg
label_desc: Use image node_id 15 for calling a global function with example usage: svdvals(a) and returns: s