code: def _get_return_layers(feature_info, out_map):
      module_names = feature_info.module_name()
      return_layers = {}
      for i, name in enumerate(module_names):
          return_layers[name] = (
              out_map[i]
              if out_map is not None
              else feature_info.out_indices[i]
          )
      return return_layers
  
imports: from collections import OrderedDict, defaultdict
  from copy import deepcopy
  from functools import partial
  from typing import Dict, List, Sequence, Tuple, Union
  import torch
  import torch.nn
  from torch.utils.checkpoint import checkpoint
  from timm.layers import Format
label_desc: Use image node_id 3 for calling a global function with example usage: _get_return_layers(feature_info, out_map) and returns: return_layers