code: def _prepad_for_spline_filter(input, mode, cval):
      if mode in ["nearest", "grid-constant"]:
          npad = 12
          if mode == "grid-constant":
              padded = numpy.pad(
                  input, npad, mode="constant", constant_values=cval
              )
          elif mode == "nearest":
              padded = numpy.pad(input, npad, mode="edge")
      else:
          # other modes have exact boundary conditions implemented so
          # no prepadding is needed
          npad = 0
          padded = input
      return padded, npad
  
file_path: catboost/contrib/python/scipy/py3/scipy/ndimage/interpolation.py
imports: import itertools
  import warnings
  import numpy
  from numpy.core.multiarray import normalize_axis_index
  from scipy import special
  from .None import _ni_support
  from .None import _nd_image
  from ._ni_docstrings import docfiller
label_desc: Use image node_id 3 for calling a global function with example usage: _prepad_for_spline_filter(input, mode, cval) and returns: padded,  npad