code: def get_config(batch_size=None):
      """Returns a standard-ish fewshot eval configuration for BERT."""
      config = ml_collections.ConfigDict()
      config.batch_size = batch_size
      config.rng_seed = 42
      # We use the prelogits of the the next_sentence_prediction head for fewshot
      # eval on classification tasks.
      config.representation_layer = (
          "next_sentence_prediction_head/pre_logits"
      )
      config.log_steps = 50_000
      config.datasets = [
          get_glue_task_config(task_name, batch_size)
          for task_name in FEW_SHOT_TASKS
      ]
      config.shots = [1, 5, 10, 25, 100, 500, 1000]
      config.l2_regs = [2.0**i for i in range(-10, 20)]
      config.walk_first = ("sst2", 100)
  
      return config
  
label_desc: Use image node_id 2 for calling a global function with example usage: get_config(batch_size) and returns: config