code: def dict_to_nparr(dd):
      dict_class = []
      dict_idx = []
      for ii, jj in enumerate(dd.symbols):
          dict_idx.append(ii)
          dict_class.append(jj)
      dict_idx = np.array(dict_idx)
      dict_class = np.array(dict_class)
      return dict_class, dict_idx
  
file_path: fairseq/examples/mms/lid/infer.py
imports: import torch
  from fairseq.data.text_compressor import TextCompressionLevel, TextCompressor
  from fairseq import checkpoint_utils, distributed_utils, options, utils
  from fairseq import checkpoint_utils, data, options, tasks
  from fairseq.data import FileAudioDataset, AddTargetDataset, Dictionary
  from fairseq.tasks.audio_classification import LabelEncoder
  import copy
  from tqdm import tqdm
  import tempfile
  import numpy
  import json
label_desc: Use image node_id 5 for calling a global function with example usage: dict_to_nparr(dd) and returns: dict_class,  dict_idx