code: def main(
      rng: jnp.ndarray,
      config: ml_collections.ConfigDict,
      workdir: str,
      writer: metric_writers.MetricWriter,
  ):
      """Main function for the BERT project."""
      if "glue_task" in config:
          task_config_file = importlib.import_module(
              f"scenic.projects.baselines.bert.configs.glue.tasks.bert_{config.glue_task}_config"
          )
          config = task_config_file.get_config(
              variant=config.variant, init_from=config.init_from
          )
      # Build the loss_fn, metrics, and flax_model.
      model_cls = get_model_cls(config.model_name)
      data_rng, rng = jax.random.split(rng)
      dataset = train_utils.get_dataset(
          config,
          data_rng,
          dataset_service_address=FLAGS.dataset_service_address,
      )
      bert_trainer.train(
          rng=rng,
          config=config,
          model_cls=model_cls,
          dataset=dataset,
          workdir=workdir,
          writer=writer,
      )
  
file_path: scenic/scenic/projects/baselines/bert/main.py
imports: import importlib
  from typing import Any
  from absl import flags
  from clu import metric_writers
  import jax
  import jax.numpy
  import ml_collections
  from scenic import app
  from scenic.projects.baselines.bert import model
  from scenic.projects.baselines.bert import trainer
  from scenic.train_lib import train_utils
label_desc: Use image node_id 2 for calling a global function with example usage: main(rng, config, workdir, writer) without return types