'Creates a PerformanceRnnSequenceGenerator.
Args:
model: Instance of PerformanceRnnModel.
details: A generator_pb2.GeneratorDetails for this generator.
steps_per_second: Number of quantized steps per second.
num_velocity_bins: Number of quantized velocity bins. If 0, don\'t use
velocity.
note_density_conditioning: If True, generate conditional on note density.
pitch_histogram_conditioning: If True, generate conditional on pitch class
histogram.
max_note_duration: The maximum note duration in seconds to allow during
generation. This model often forgets to release notes; specifying a
maximum duration can force it to do so.
fill_generate_section: If True, the model will generate RNN steps until
the entire generate section has been filled. If False, the model will
estimate the number of RNN steps needed and then generate that many
events, even if the generate section isn\'t completely filled.
checkpoint: Where to search for the most recent model checkpoint. Mutually
exclusive with `bundle`.
bundle: A GeneratorBundle object that includes both the model checkpoint
and metagraph. Mutually exclusive with `checkpoint`.
Raises:
ValueError: If both `note_density_conditioning` and
`pitch_histogram_conditioning` are enabled.'

def __init__(self, model, details, steps_per_second=performance_lib.DEFAULT_STEPS_PER_SECOND, num_velocity_bins=0, note_density_conditioning=False, pitch_histogram_conditioning=False, max_note_duration=MAX_NOTE_DURATION_SECONDS, fill_generate_section=True, checkpoint=None, bundle=None):

    super(PerformanceRnnSequenceGenerator, self).__init__(model, details, checkpoint, bundle)
    self.steps_per_second = steps_per_second
    self.num_velocity_bins = num_velocity_bins
    self.note_density_conditioning = note_density_conditioning
    self.pitch_histogram_conditioning = pitch_histogram_conditioning
    self.max_note_duration = max_note_duration
    self.fill_generate_section = fill_generate_section
