code: def qspline2d(signal, lamb=0.0, precision=-1.0):
      """
      Coefficients for 2-D quadratic (2nd order) B-spline.
  
      Return the second-order B-spline coefficients over a regularly spaced
      input grid for the two-dimensional input image.
  
      Parameters
      ----------
      input : ndarray
          The input signal.
      lamb : float
          Specifies the amount of smoothing in the transfer function.
      precision : float
          Specifies the precision for computing the infinite sum needed to apply
          mirror-symmetric boundary conditions.
  
      Returns
      -------
      output : ndarray
          The filtered signal.
      """
  
      if lamb > 0:
          raise ValueError("lambda must be negative or zero")
  
      # normal quadratic spline
      r = -3 + 2 * np.sqrt(2.0)
  
      out = _symiirorder1_nd(
          signal, -r * 8.0, r, precision=precision, axis=-1
      )
      out = _symiirorder1_nd(
          out, -r * 8.0, r, precision=precision, axis=0
      )
      return out
  
imports: import cupy
  import cupyx.scipy.ndimage
  from cupyx.scipy.signal._iir_utils import apply_iir_sos
  from cupyx.scipy.signal._splines import _symiirorder1_nd, _symiirorder2_nd
  from cupyx.scipy.interpolate._bspline import BSpline
  import numpy
label_desc: Use image node_id 16 for calling a global function with example usage: qspline2d(signal, lamb, precision) and returns: out