code: def get_fused_module_list(
      module_name: str, mode: str, fused_module_names: List[Tuple[str]]
  ) -> Tuple:
      if mode != "quantization" and len(fused_module_names) > 0:
          raise ValueError(
              f"Only quantization supports model fusion, but got {mode}"
          )
      elif len(fused_module_names) == 0:
          return ()
      for fuse_pair in fused_module_names:
          if module_name == fuse_pair[0]:
              return fuse_pair
  
      return ()
  
file_path: nni/nni/compression/utils/fused_utils.py
imports: from typing import List, Dict, Any, Tuple
  import torch
  import torch.nn
  from ..base.setting import OUTPUT_PREFIX
label_desc: Use image node_id 2 for calling a global function with example usage: get_fused_module_list(module_name, mode, fused_module_names) and returns: , , fuse_pair