(rl_tuner,
                              num_compositions=10000,
                              composition_length=32,
                              key=None,
                              tonic_note=rl_tuner_ops.C_MAJOR_TONIC)
return stat_dict
Uses the model to create many compositions, stores statistics about them.

  Args:
    rl_tuner: An RLTuner object.
    num_compositions: The number of compositions to create.
    composition_length: The number of beats in each composition.
    key: The numeric values of notes belonging to this key. Defaults to
      C-major if not provided.
    tonic_note: The tonic/1st note of the desired key.
  Returns:
    A dictionary containing the computed statistics about the compositions.
Uses the model to create many compositions, stores statistics about them.
Uses the model to create many compositions stores statistics about them .
def compute_composition_stats(rl_tuner,
                              num_compositions=10000,
                              composition_length=32,
                              key=None,
                              tonic_note=rl_tuner_ops.C_MAJOR_TONIC):
  """Uses the model to create many compositions, stores statistics about them.

  Args:
    rl_tuner: An RLTuner object.
    num_compositions: The number of compositions to create.
    composition_length: The number of beats in each composition.
    key: The numeric values of notes belonging to this key. Defaults to
      C-major if not provided.
    tonic_note: The tonic/1st note of the desired key.
  Returns:
    A dictionary containing the computed statistics about the compositions.
  """
  stat_dict = initialize_stat_dict()

  for i in range(num_compositions):
    stat_dict = compose_and_evaluate_piece(
        rl_tuner,
        stat_dict,
        composition_length=composition_length,
        key=key,
        tonic_note=tonic_note)
    if i % (num_compositions / 10) == 0:
      stat_dict['num_compositions'] = i
      stat_dict['total_notes'] = i * composition_length

  stat_dict['num_compositions'] = num_compositions
  stat_dict['total_notes'] = num_compositions * composition_length

  tf.logging.info(get_stat_dict_string(stat_dict))

  return stat_dict
def compute_composition_stats ( rl_tuner , num_compositions = 10000 , composition_length = 32 , key = None , tonic_note = rl_tuner_ops . C_MAJOR_TONIC ) : stat_dict = initialize_stat_dict ( ) for i in range ( num_compositions ) : stat_dict = compose_and_evaluate_piece ( rl_tuner , stat_dict , composition_length = composition_length , key = key , tonic_note = tonic_note ) if i % ( num_compositions / 10 ) == 0 : stat_dict [ 'num_compositions' ] = i stat_dict [ 'total_notes' ] = i * composition_length stat_dict [ 'num_compositions' ] = num_compositions stat_dict [ 'total_notes' ] = num_compositions * composition_length tf . logging . info ( get_stat_dict_string ( stat_dict ) ) return stat_dict