code: def detokenize(
      idx, n_special=4, n_note=128, n_velocity=2, time_idx_offset=0
  ):
      if idx >= n_special + n_note + n_velocity:
          return (
              "TOKEN_TIME",
              (idx - (n_special + n_note + n_velocity))
              + time_idx_offset,
          )
      elif idx >= n_special + n_note:
          return "TOKEN_VELOCITY", idx - (n_special + n_note)
      elif idx >= n_special:
          return "TOKEN_NOTE", idx - n_special
      else:
          return "TOKEN_SPECIAL", idx
  
imports: import json
  import torch
  from transformers import Pop2PianoConfig, Pop2PianoForConditionalGeneration
label_desc: Use image node_id 2 for calling a global function with example usage: detokenize(idx, n_special, n_note, n_velocity, time_idx_offset) and returns: str,  unknown, str,  unknown, str,  unknown, str,  idx