code: def is_share_fusion(
      query_model_names: List[str],
      response_model_names: List[str],
  ):
      """
      Check whether the query and response models share the same fusion part.
  
      Parameters
      ----------
      query_model_names
          Names of single models in the query late-fusion model.
      response_model_names
          Names of single models in the response late-fusion model.
  
      Returns
      -------
      Whether to share the same fusion part.
      """
      query_model_names = [
          n
          for n in query_model_names
          if not n.lower().startswith(FUSION)
      ]
      response_model_names = [
          n
          for n in response_model_names
          if not n.lower().startswith(FUSION)
      ]
      return sorted(query_model_names) == sorted(response_model_names)
  
imports: import copy
  import functools
  import heapq
  import logging
  from typing import Dict, List, Optional, Union
  import pandas
  import torch
  from omegaconf import DictConfig
  from torch import nn
  from torch.nn import functional
  from ..constants import FUSION, QUERY, RESPONSE
  from .data import data_to_df
  from .model import create_model
label_desc: Use image node_id 4 for calling a global function with example usage: is_share_fusion(query_model_names, response_model_names) and returns: unknown