code: def add_tonic_start_stat(
      rl_tuner,
      action_note,
      stat_dict,
      tonic_note=rl_tuner_ops.C_MAJOR_TONIC,
  ):
      """Updates stat dict based on whether composition started with the tonic.
  
      Args:
        rl_tuner: An RLTuner object.
        action_note: An integer representing the chosen action.
        stat_dict: A dictionary containing fields for statistics about
          compositions.
        tonic_note: The tonic/1st note of the desired key.
      Returns:
        A dictionary of composition statistics with 'num_starting_tonic' field
        updated.
      """
      if rl_tuner.beat == 0 and action_note == tonic_note:
          stat_dict["num_starting_tonic"] += 1
      return stat_dict
  
file_path: magenta/magenta/models/rl_tuner/rl_tuner_eval_metrics.py
imports: from magenta.models.rl_tuner import rl_tuner_ops
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 7 for calling a global function with example usage: add_tonic_start_stat(rl_tuner, action_note, stat_dict, tonic_note) and returns: stat_dict