code: def main(unused_argv):
      restore_dir = (
          FLAGS.save_dir if not FLAGS.restore_dir else FLAGS.restore_dir
      )
  
      cluster_config, save_dir = get_worker_behavior_info(
          FLAGS.save_dir
      )
      gin_search_path = parse_list_params(
          FLAGS.gin_search_path, "gin_search_path"
      )
      gin_file = parse_list_params(FLAGS.gin_file, "gin_file")
      gin_param = parse_list_params(FLAGS.gin_param, "gin_param")
  
      ddsp_run_command = (
          [
              "ddsp_run",
              "--mode=train",
              "--alsologtostderr",
              "--gin_file=models/solo_instrument.gin",
              "-gin_file=datasets/tfrecord.gin",
              f"--cluster_config={cluster_config}",
              f"--save_dir={save_dir}",
              f"--restore_dir={restore_dir}",
              f"--hypertune={FLAGS.hypertune}",
              f"--early_stop_loss_value={FLAGS.early_stop_loss_value}",
              f"--gin_param=batch_size={FLAGS.batch_size}",
              f"--gin_param=learning_rate={FLAGS.learning_rate}",
              f"--gin_param=TFRecordProvider.file_pattern='{FLAGS.file_pattern}'",
              f"--gin_param=train_util.train.num_steps={FLAGS.num_steps}",
              f"--gin_param=train_util.train.steps_per_save={FLAGS.steps_per_save}",
              (
                  "--gin_param=train_util.train.steps_per_summary="
                  f"{FLAGS.steps_per_summary}"
              ),
          ]
          + gin_search_path
          + gin_file
          + gin_param
      )
  
      subprocess.run(args=ddsp_run_command, check=True)
  
file_path: ddsp/ddsp/training/docker/task.py
imports: import json
  import os
  import subprocess
  from absl import app
  from absl import flags
label_desc: Use image node_id 3 for calling a global function with example usage: main(unused_argv) without return types