code: def get_generator_map():
      """Returns a map from the generator ID to a SequenceGenerator class creator.
  
      Binds the `config` argument so that the arguments match the
      BaseSequenceGenerator class constructor.
  
      Returns:
        Map from the generator ID to its SequenceGenerator class creator with a
        bound `config` argument.
      """
  
      def create_sequence_generator(config, **kwargs):
          return PerformanceRnnSequenceGenerator(
              performance_model.PerformanceRnnModel(config),
              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,
              fill_generate_section=False,
              note_performance=config.note_performance,
              **kwargs,
          )
  
      return {
          key: functools.partial(create_sequence_generator, config)
          for (key, config) in performance_model.default_configs.items()
      }
  
file_path: magenta/magenta/models/performance_rnn/performance_sequence_generator.py
imports: from __future__ import division
  import ast
  import functools
  import math
  from magenta.models.performance_rnn import performance_model
  from magenta.models.shared import sequence_generator
  from magenta.pipelines import performance_pipeline
  import note_seq
  from note_seq import performance_controls
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling a global function with example usage: get_generator_map() and returns: unknown, PerformanceRnnSequenceGenerator