code: def main(unused_argv):
      """Saves bundle or runs generator based on flags."""
      tf.logging.set_verbosity(FLAGS.log)
  
      bundle = get_bundle()
  
      config_id = (
          bundle.generator_details.id if bundle else FLAGS.config
      )
      config = performance_model.default_configs[config_id]
      config.hparams.parse(FLAGS.hparams)
      # Having too large of a batch size will slow generation down unnecessarily.
      config.hparams.batch_size = min(
          config.hparams.batch_size,
          FLAGS.beam_size * FLAGS.branch_factor,
      )
  
      generator = performance_sequence_generator.PerformanceRnnSequenceGenerator(
          model=performance_model.PerformanceRnnModel(config),
          details=config.details,
          steps_per_second=config.steps_per_second,
          num_velocity_bins=config.num_velocity_bins,
          control_signals=config.control_signals,
          optional_conditioning=config.optional_conditioning,
          checkpoint=get_checkpoint(),
          bundle=bundle,
          note_performance=config.note_performance,
      )
  
      if FLAGS.save_generator_bundle:
          bundle_filename = os.path.expanduser(FLAGS.bundle_file)
          if FLAGS.bundle_description is None:
              tf.logging.warning("No bundle description provided.")
          tf.logging.info(
              "Saving generator bundle to %s", bundle_filename
          )
          generator.create_bundle_file(
              bundle_filename, FLAGS.bundle_description
          )
      else:
          run_with_flags(generator)
  
file_path: magenta/magenta/models/performance_rnn/performance_rnn_generate.py
imports: import ast
  import os
  import time
  from magenta.models.performance_rnn import performance_model
  from magenta.models.performance_rnn import performance_sequence_generator
  from magenta.models.shared import sequence_generator
  from magenta.models.shared import sequence_generator_bundle
  import note_seq
  from note_seq.protobuf import generator_pb2
  from note_seq.protobuf import music_pb2
  import tensorflow.compat.v1
label_desc: Use image node_id 4 for calling a global function with example usage: main(unused_argv) without return types