code: def qspline1d(signal, lamb=0.0):
      """Compute quadratic spline coefficients for rank-1 array.
  
      Parameters
      ----------
      signal : ndarray
          A rank-1 array representing samples of a signal.
      lamb : float, optional
          Smoothing coefficient (must be zero for now).
  
      Returns
      -------
      c : ndarray
          Quadratic spline coefficients.
  
      See Also
      --------
      qspline1d_eval : Evaluate a quadratic spline at the new set of points.
  
      Notes
      -----
      Find the quadratic spline coefficients for a 1-D signal assuming
      mirror-symmetric boundary conditions. To obtain the signal back from the
      spline representation mirror-symmetric-convolve these coefficients with a
      length 3 FIR window [1.0, 6.0, 1.0]/ 8.0 .
  
      """
      if lamb != 0.0:
          raise ValueError(
              "Smoothing quadratic splines not supported yet."
          )
      else:
          return _quadratic_coeff(signal)
  
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 12 for calling a global function with example usage: qspline1d(signal, lamb) and returns: _quadratic_coeff