code: def get_config(run_local: str = "") -> ml_collections.ConfigDict:
      """Returns the experiment configuration."""
      config = base_clip_bert.get_config(run_local)
  
      config.experiment_name = "clip_bert_with_pretraining"
  
      config.model.text_encoder.config_name = "base"
      config.model.text_encoder.pretraining_mode = True
      config.model.text_encoder.embedding_size = 512
      config.model.text_encoder.compute_mlm = True
  
      config.text_dataset_name = "bert_wikibooks"
  
      config.text_dataset_configs = ml_collections.ConfigDict()
  
      config.text_dataset_configs.prefetch_to_device = 2
  
      config.text_dataset_configs.truncate_to_max_num_words = False
  
      config.text_dataset_configs.train_data_loader = (
          ml_collections.ConfigDict()
      )
      wikibooks_train_loader = (
          config.text_dataset_configs.train_data_loader
      )
      # The values of `seq_length` and `max_predictions_per_seq` cannot be changed
      # because they are used to parse the features. They could be changed once the
      # data is loaded.
      wikibooks_train_loader.seq_length = 512
      wikibooks_train_loader.max_predictions_per_seq = 76
      wikibooks_train_loader.use_next_sentence_label = True
      wikibooks_train_loader.use_position_id = False
      wikibooks_train_loader.use_v2_feature_names = False
      # Add path to training files containing tf.records.
      wikibooks_train_loader.input_path = ""
      wikibooks_train_loader.drop_remainder = True
      wikibooks_train_loader.shuffle_buffer_size = 100
      wikibooks_train_loader.cycle_length = None
      wikibooks_train_loader.block_length = 1
      wikibooks_train_loader.deterministic = None
      wikibooks_train_loader.sharding = True
      wikibooks_train_loader.enable_tf_data_service = False
      wikibooks_train_loader.tf_data_service_address = None
      wikibooks_train_loader.tfds_name = None
      wikibooks_train_loader.tfds_split = None
      wikibooks_train_loader.tfds_as_supervised = False
      wikibooks_train_loader.tfds_skip_decoding_feature = ""
      wikibooks_train_loader.global_batch_size = config.get_ref(
          "batch_size"
      )
      wikibooks_train_loader.prefetch_buffer_size = None  # Autotune.
      wikibooks_train_loader.enable_shared_tf_data_service_between_parallel_trainers = (
          False
      )
      wikibooks_train_loader.apply_tf_data_service_before_batching = (
          False
      )
      wikibooks_train_loader.trainer_id = None
  
      # The val split is actually unused, but the config is required.
  
      config.text_dataset_configs.val_data_loader = (
          ml_collections.ConfigDict()
      )
      wikibooks_val_loader = config.text_dataset_configs.val_data_loader
      wikibooks_val_loader.seq_length = 512
      wikibooks_val_loader.max_predictions_per_seq = 76
      wikibooks_val_loader.use_next_sentence_label = True
      wikibooks_val_loader.use_position_id = False
      wikibooks_val_loader.use_v2_feature_names = False
      # Add path to validation files containing tf.records.
      wikibooks_val_loader.input_path = ""
      wikibooks_val_loader.drop_remainder = False
      wikibooks_val_loader.cycle_length = None
      wikibooks_val_loader.block_length = 1
      wikibooks_val_loader.deterministic = None
      wikibooks_val_loader.sharding = True
      wikibooks_val_loader.enable_tf_data_service = False
      wikibooks_val_loader.tf_data_service_address = None
      wikibooks_val_loader.tfds_name = None
      wikibooks_val_loader.tfds_split = None
      wikibooks_val_loader.tfds_as_supervised = False
      wikibooks_val_loader.tfds_skip_decoding_feature = ""
      wikibooks_val_loader.global_batch_size = config.get_ref(
          "eval_batch_size"
      )
      wikibooks_val_loader.prefetch_buffer_size = None  # Autotune.
      wikibooks_val_loader.enable_shared_tf_data_service_between_parallel_trainers = (
          False
      )
      wikibooks_val_loader.apply_tf_data_service_before_batching = False
      wikibooks_val_loader.trainer_id = None
  
      return config
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_config(run_local) and returns: config