code: def rename_keys(s_dict):
      keys = list(s_dict.keys())
      for key in keys:
          if "transformer_layers" in key:
              s_dict[
                  key.replace("transformer_layers", "layers")
              ] = s_dict.pop(key)
          elif "subsample" in key:
              s_dict[key.replace("subsample", "conv")] = s_dict.pop(key)
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/models/speech_to_text/convert_s2t_fairseq_to_tfms.py
imports: import argparse
  import torch
  from torch import nn
  from transformers import Speech2TextConfig, Speech2TextForConditionalGeneration
label_desc: Use image node_id 2 for calling a global function with example usage: rename_keys(s_dict) without return types