class_docstr: Class for RNN polyphonic sequence generation models.
docstr: Generate a polyphonic track from a primer polyphonic track.
  
  Args:
    num_steps: The integer length in steps of the final track, after
        generation. Includes the primer.
    primer_sequence: The primer sequence, a PolyphonicSequence object.
    temperature: A float specifying how much to divide the logits by
       before computing the softmax. Greater than 1.0 makes tracks more
       random, less than 1.0 makes tracks less random.
    beam_size: An integer, beam size to use when generating tracks via
        beam search.
    branch_factor: An integer, beam search branch factor to use.
    steps_per_iteration: An integer, number of steps to take per beam search
        iteration.
    modify_events_callback: An optional callback for modifying the event list.
        Can be used to inject events rather than having them generated. If not
        None, will be called with 3 arguments after every event: the current
        EventSequenceEncoderDecoder, a list of current EventSequences, and a
        list of current encoded event inputs.
  Returns:
    The generated PolyphonicSequence object (which begins with the provided
    primer track).
code: def generate_polyphonic_sequence(
      self,
      num_steps,
      primer_sequence,
      temperature=1.0,
      beam_size=1,
      branch_factor=1,
      steps_per_iteration=1,
      modify_events_callback=None,
  ):
      """Generate a polyphonic track from a primer polyphonic track.
  
      Args:
        num_steps: The integer length in steps of the final track, after
            generation. Includes the primer.
        primer_sequence: The primer sequence, a PolyphonicSequence object.
        temperature: A float specifying how much to divide the logits by
           before computing the softmax. Greater than 1.0 makes tracks more
           random, less than 1.0 makes tracks less random.
        beam_size: An integer, beam size to use when generating tracks via
            beam search.
        branch_factor: An integer, beam search branch factor to use.
        steps_per_iteration: An integer, number of steps to take per beam search
            iteration.
        modify_events_callback: An optional callback for modifying the event list.
            Can be used to inject events rather than having them generated. If not
            None, will be called with 3 arguments after every event: the current
            EventSequenceEncoderDecoder, a list of current EventSequences, and a
            list of current encoded event inputs.
      Returns:
        The generated PolyphonicSequence object (which begins with the provided
        primer track).
      """
      return self._generate_events(
          num_steps,
          primer_sequence,
          temperature,
          beam_size,
          branch_factor,
          steps_per_iteration,
          modify_events_callback=modify_events_callback,
      )
  
file_path: magenta/magenta/models/polyphony_rnn/polyphony_model.py
imports: from magenta.contrib import training
  from magenta.models.polyphony_rnn import polyphony_encoder_decoder
  from magenta.models.shared import events_rnn_model
  import note_seq
  from note_seq.protobuf import generator_pb2
label_desc: Use image node_id 1 for calling the PolyphonyRnnModel obj's underlying member method code with example usage: obj.generate_polyphonic_sequence(num_steps, primer_sequence, temperature, beam_size, branch_factor, steps_per_iteration, modify_events_callback) and returns: self