code: def update_config(
      config: ml_collections.ConfigDict, meta_data: Dict[str, Any]
  ):
      config.num_train_examples = meta_data["num_train_examples"]
      steps_per_epoch = config.num_train_examples // config.batch_size
      config.lr_configs.total_steps = int(
          config.num_training_epochs * steps_per_epoch
      )
  
imports: import dataclasses
  import operator
  import re
  from typing import Any, Dict, List, Mapping, Optional, Tuple, Union
  from absl import logging
  from big_vision import utils
  from big_vision.models import vit
  from clu import metric_writers
  import flax
  from flax import jax_utils
  from flax.core import frozen_dict
  import jax
  import jax.numpy
  import ml_collections
  import optax
  from scenic.dataset_lib import dataset_utils
  from scenic.dataset_lib import datasets
  from scenic.projects.knowledge_visual_language.models import constants
  from scenic.projects.t5 import model
  from scenic.train_lib import train_utils
  from scenic.train_lib.train_utils import TrainState
label_desc: Use image node_id 2 for calling a global function with example usage: update_config(config, meta_data) without return types