code: def pad_to_full(A, B, axes):
      A_pad = [(0, 0)] * A.ndim
      for ax_A, ax_B in zip(*axes):
          A_pad[ax_A] = (B.shape[ax_B] - 1,) * 2
      return npo.pad(A, A_pad, mode="constant")
  
file_path: autograd/autograd/scipy/signal.py
imports: from __future__ import absolute_import
  from builtins import range, zip
  from functools import partial
  import autograd.numpy
  import numpy
  from autograd.extend import primitive, defvjp
  from numpy.lib.stride_tricks import as_strided
  from six import iteritems
label_desc: Use image node_id 3 for calling a global function with example usage: pad_to_full(A, B, axes) and returns: npo