code: def _interior_pad(operand, padding_value, padding_config):
      for axis, (_, _, interior) in enumerate(padding_config):
          if interior > 0:
              new_shape = list(operand.shape)
              new_shape[axis] = (
                  new_shape[axis] + (new_shape[axis] - 1) * interior
              )
              new_array = np.full(
                  new_shape, padding_value, dtype=operand.dtype
              )
              src_indices = np.arange(operand.shape[axis])
              dst_indices = src_indices * (interior + 1)
              index_tuple = [slice(None)] * operand.ndim
              index_tuple[axis] = dst_indices
              new_array[tuple(index_tuple)] = operand
              operand = new_array
  
      start_indices = [0] * operand.ndim
      limit_indices = [0] * operand.ndim
      for axis, (low, high, _) in enumerate(padding_config):
          if low < 0:
              start_indices[axis] = abs(low)
          if high < 0:
              limit_indices[axis] = high
          else:
              limit_indices[axis] = operand.shape[axis] + 1
      padded = _slice(operand, start_indices, limit_indices)
  
      pad_width = [(0, 0)] * operand.ndim
      for axis, (low, high, _) in enumerate(padding_config):
          if low > 0 and high > 0:
              pad_width[axis] = (low, high)
          elif low > 0 and not high > 0:
              pad_width[axis] = (low, 0)
          elif high > 0 and not low > 0:
              pad_width[axis] = (0, high)
      padded = np.pad(padded, pad_width, constant_values=padding_value)
      return padded
  
imports: from typing import Iterable, Optional, Union, Sequence, Tuple, NamedTuple, Literal, Callable, Any, List
  from numbers import Number
  from collections import namedtuple
  import numpy
  import ivy
  from ivy.functional.backends.numpy.helpers import _scalar_output_to_0d_array
  from ivy.func_wrapper import with_supported_dtypes
  from .None import backend_version
label_desc: Use image node_id 12 for calling a global function with example usage: _interior_pad(operand, padding_value, padding_config) and returns: padded