code: def split_config(config_path, download):
      """Gets model, data iterator and a task name from the configuration file.
  
      Args:
          config_path: Path to the model configuration file.
          download: If True, the model will be downloaded from the DeepPavlov server.
      """
  
      config = parse_config(config_path)
      data = read_data_by_config(config)
      iterator = get_iterator_from_config(config, data)
      task_name = config["dataset_reader"]["name"]
      if task_name == "mnli":
          task_name = (
              "mnli-m"
              if config["dataset_reader"]["valid"]
              == "validation_matched"
              else "mnli-mm"
          )
      data_gen = iterator.gen_batches(
          1, data_type="test", shuffle=False
      )
      model = build_model(config, download=download)
      return model, data_gen, task_name
  
file_path: DeepPavlov/deeppavlov/utils/benchmarks/benchmarks.py
imports: import argparse
  from collections import defaultdict
  from logging import getLogger
  import numpy
  from tqdm import tqdm
  from deeppavlov import build_model
  from deeppavlov.core.commands.train import read_data_by_config, get_iterator_from_config
  from deeppavlov.core.commands.utils import parse_config, expand_path
  from deeppavlov.core.common.file import save_jsonl
label_desc: Use image node_id 1 for calling a global function with example usage: split_config(config_path, download) and returns: model,  data_gen,  task_name