code: def rename_state_dict(
      state_dict: OrderedDict, hidden_size: int
  ) -> Tuple[Dict, Dict]:
      """Function that takes the fairseq Musicgen state dict and renames it according to the HF
      module names. It further partitions the state dict into the decoder (LM) state dict, and that for the
      encoder-decoder projection."""
      keys = list(state_dict.keys())
      enc_dec_proj_state_dict = {}
      for key in keys:
          val = state_dict.pop(key)
          key = rename_keys(key)
          if "in_proj_weight" in key:
              # split fused qkv proj
              state_dict[
                  key.replace("in_proj_weight", "q_proj.weight")
              ] = val[:hidden_size, :]
              state_dict[
                  key.replace("in_proj_weight", "k_proj.weight")
              ] = val[hidden_size : 2 * hidden_size, :]
              state_dict[
                  key.replace("in_proj_weight", "v_proj.weight")
              ] = val[-hidden_size:, :]
          elif "enc_to_dec_proj" in key:
              enc_dec_proj_state_dict[
                  key[len("enc_to_dec_proj.") :]
              ] = val
          else:
              state_dict[key] = val
      return state_dict, enc_dec_proj_state_dict
  
file_path: transformers/src/transformers/models/musicgen/convert_musicgen_transformers.py
imports: import argparse
  from pathlib import Path
  from typing import Dict, OrderedDict, Tuple
  import torch
  from audiocraft.models import MusicGen
  from transformers import AutoFeatureExtractor, AutoTokenizer, EncodecModel, MusicgenDecoderConfig, MusicgenForConditionalGeneration, MusicgenProcessor, T5EncoderModel
  from transformers.models.musicgen.modeling_musicgen import MusicgenForCausalLM
  from transformers.utils import logging
label_desc: Use image node_id 2 for calling a global function with example usage: rename_state_dict(state_dict, hidden_size) and returns: state_dict,  enc_dec_proj_state_dict