class_docstr: Constructs a Pop2Piano tokenizer. This tokenizer does not require training.
  
  This tokenizer inherits from [`PreTrainedTokenizer`] which contains most of the main methods. Users should refer to
  this superclass for more information regarding those methods.
  
  Args:
      vocab (`str`):
          Path to the vocab file which contains the vocabulary.
      default_velocity (`int`, *optional*, defaults to 77):
          Determines the default velocity to be used while creating midi Notes.
      num_bars (`int`, *optional*, defaults to 2):
          Determines cutoff_time_idx in for each token.
docstr: Decodes the token ids generated by the transformer into notes.
  
  Args:
      token_id (`int`):
          This denotes the ids generated by the transformers to be converted to Midi tokens.
  
  Returns:
      `List`: A list consists of token_type (`str`) and value (`int`).
docstr_tok: ["Decodes","the","token","ids","generated","by","the","transformer","into","notes",".","Args",":","token_id","(","`","int","`",")",":","This","denotes","the","ids","generated","by","the","transformers","to","be","converted","to","Midi","tokens",".","Returns",":","`","List","`",":","A","list","consists","of","token_type","(","`","str","`",")","and","value","(","`","int","`",")","."]
code: def _convert_id_to_token(self, token_id: int) -> list:
      """
      Decodes the token ids generated by the transformer into notes.
  
      Args:
          token_id (`int`):
              This denotes the ids generated by the transformers to be converted to Midi tokens.
  
      Returns:
          `List`: A list consists of token_type (`str`) and value (`int`).
      """
  
      token_type_value = self.decoder.get(
          token_id, f"{self.unk_token}_TOKEN_TIME"
      )
      token_type_value = token_type_value.split("_")
      token_type, value = "_".join(token_type_value[1:]), int(
          token_type_value[0]
      )
  
      return [token_type, value]
  
imports: import json
  import os
  from typing import List, Optional, Tuple, Union
  import numpy
  from ...feature_extraction_utils import BatchFeature
  from ...tokenization_utils import AddedToken, BatchEncoding, PaddingStrategy, PreTrainedTokenizer, TruncationStrategy
  from ...utils import TensorType, is_pretty_midi_available, logging, requires_backends, to_numpy
label_desc: Use image node_id 4 for calling the Pop2PianoTokenizer obj's underlying member method code with example usage: obj._convert_id_to_token(token_id) and returns: list