code: def get_efficientnet_image_size(model_name: str) -> int:
      """
      Get the input image size for a given efficientnet model.
  
      Args:
          model_name: name of model to initialize, can be from [efficientnet-b0, ..., efficientnet-b7].
  
      Returns:
          Image size for single spatial dimension as integer.
  
      """
      # check if model_name is valid model
      if model_name not in efficientnet_params:
          model_name_string = ", ".join(efficientnet_params.keys())
          raise ValueError(
              f"invalid model_name {model_name} found, must be one of {model_name_string} "
          )
  
      # return input image size (all dims equal so only need to return for one dim)
      _, _, res, _, _ = efficientnet_params[model_name]
      return res
  
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 1 for calling a global function with example usage: get_efficientnet_image_size(model_name) and returns: res