code: def main(_):
      gin.parse_config_files_and_bindings(
          FLAGS.gin_file, FLAGS.gin_params
      )
      params = train_utils.parse_configuration(FLAGS)
      model_dir = FLAGS.model_dir
      if "train" in FLAGS.mode:
          # Pure eval modes do not output yaml files. Otherwise continuous eval job
          # may race against the train job for writing the same file.
          train_utils.serialize_config(params, model_dir)
  
      # Sets mixed_precision policy. Using 'mixed_float16' or 'mixed_bfloat16'
      # can have significant impact on model speeds by utilizing float16 in case of
      # GPUs, and bfloat16 in the case of TPUs. loss_scale takes effect only when
      # dtype is float16
      if params.runtime.mixed_precision_dtype:
          performance.set_mixed_precision_policy(
              params.runtime.mixed_precision_dtype
          )
      distribution_strategy = distribute_utils.get_distribution_strategy(
          distribution_strategy=params.runtime.distribution_strategy,
          all_reduce_alg=params.runtime.all_reduce_alg,
          num_gpus=params.runtime.num_gpus,
          tpu_address=params.runtime.tpu,
          **params.runtime.model_parallelism(),
      )
      with distribution_strategy.scope():
          task = task_factory.get_task(
              params.task,
              label_spec=(
                  "relevance",
                  tf.io.FixedLenFeature(
                      shape=[
                          1,
                      ],
                      dtype=tf.int64,
                      default_value=-1,
                  ),
              ),
              logging_dir=model_dir,
          )
  
      train_lib.run_experiment(
          distribution_strategy=distribution_strategy,
          task=task,
          mode=FLAGS.mode,
          params=params,
          model_dir=model_dir,
      )
  
imports: from absl import app
  from absl import flags
  import gin
  import tensorflow
  from tensorflow_ranking.examples.keras import tfrbert_task_experiments
label_desc: Use image node_id 1 for calling a global function with example usage: main(_) without return types