code: def create_transducer_compatible_state_dict(
      model_state_dict, encoder_type, encoder_units
  ):
      """Create a compatible transducer model state dict for transfer learning.
  
      If RNN encoder modules from a non-Transducer model are found in
      the pre-trained model state dict, the corresponding modules keys are
      renamed for compatibility.
  
      Args:
          model_state_dict (Dict): Pre-trained model state dict
          encoder_type (str): Type of pre-trained encoder.
          encoder_units (int): Number of encoder units in pre-trained model.
  
      Returns:
          new_state_dict (Dict): Transducer compatible pre-trained model state dict.
  
      """
      if encoder_type.endswith("p") or not encoder_type.endswith(
          ("lstm", "gru")
      ):
          return model_state_dict
  
      new_state_dict = OrderedDict()
      rnn_key_name = "birnn" if "b" in encoder_type else "rnn"
  
      for key, value in list(model_state_dict.items()):
          if any(k in key for k in ["l_last", "nbrnn"]):
              if "nbrnn" in key:
                  layer_name = rnn_key_name + re.search(
                      "_l([0-9]+)", key
                  ).group(1)
  
                  key = re.sub(
                      "_l([0-9]+)",
                      "_l0",
                      key.replace("nbrnn", layer_name),
                  )
  
              if (encoder_units * 2) == value.size(-1):
                  value = (
                      value[:, :encoder_units]
                      + value[:, encoder_units:]
                  )
  
          new_state_dict[key] = value
  
      return new_state_dict
  
file_path: espnet/espnet/asr/pytorch_backend/asr_init.py
imports: import logging
  import os
  import re
  from collections import OrderedDict
  import torch
  from espnet.asr.asr_utils import get_model_conf, torch_load
  from espnet.nets.asr_interface import ASRInterface
  from espnet.nets.mt_interface import MTInterface
  from espnet.nets.pytorch_backend.transducer.utils import custom_torch_load
  from espnet.nets.tts_interface import TTSInterface
  from espnet.utils.dynamic_import import dynamic_import
label_desc: Use image node_id 6 for calling a global function with example usage: create_transducer_compatible_state_dict(model_state_dict, encoder_type, encoder_units) and returns: new_state_dict, model_state_dict