code: def _make_same_padder(
      conv_op: nn.Conv1d | nn.Conv2d | nn.Conv3d, image_size: list[int]
  ):
      """
      Helper for initializing ConstantPadNd with SAME padding similar to Tensorflow.
      Uses output of _get_same_padding_conv_nd() to get the padding size.
  
      This function is generalized for MONAI's N-Dimensional spatial operations (e.g. Conv1D, Conv2D, Conv3D)
  
      Args:
          conv_op: nn.ConvNd operation to extract parameters for op from
          image_size: input image/feature spatial size
  
      Returns:
          If padding required then nn.ConstandNd() padder initialized to paddings otherwise nn.Identity()
      """
      # calculate padding required
      padding: list[int] = _get_same_padding_conv_nd(
          image_size,
          conv_op.kernel_size,
          conv_op.dilation,
          conv_op.stride,
      )
  
      # initialize and return padder
      padder = Pad["constantpad", len(padding) // 2]
      if sum(padding) > 0:
          return padder(padding=padding, value=0.0)
      return nn.Identity()
  
imports: from __future__ import annotations
  import math
  import operator
  import re
  from functools import reduce
  from typing import NamedTuple
  import torch
  from torch import nn
  from torch.utils import model_zoo
  from monai.networks.blocks import BaseEncoder
  from monai.networks.layers.factories import Act, Conv, Pad, Pool
  from monai.networks.layers.utils import get_norm_layer
  from monai.utils.module import look_up_option
label_desc: Use image node_id 5 for calling a global function with example usage: _make_same_padder(conv_op, image_size) and returns: nn, padder