code: def preprocess_copa(
      examples: Dataset, *, lang: str = "en"
  ) -> Dict[str, List[List[str]]]:
      """COPA preprocessing to be applied by the map function.
      Args:
          examples: an instance of Dataset class
          lang: task language. Either `en` or `ru`.
      Returns:
          Dict[str, List[List[str]]]: processed features represented as nested
          list with number of elements corresponding to the number of choices
          (2 in this case)
      """
      if lang == "en":
          question_dict = {
              "cause": "What was the cause of this?",
              "effect": "What happened as a result?",
          }
      elif lang == "ru":
          question_dict = {
              "cause": "Что было причиной этого?",
              "effect": "Что случилось в результате?",
          }
      else:
          raise ValueError(
              f"Incorrect `lang` value '{lang}'. Should be either 'en' or 'ru'."
          )
  
      num_choices = 2
  
      questions = [
          question_dict[question] for question in examples["question"]
      ]
      premises = examples["premise"]
  
      contexts = [
          f"{premise} {question}"
          for premise, question in zip(premises, questions)
      ]
      contexts = [[context] * num_choices for context in contexts]
  
      choices = [
          [choice1, choice2]
          for choice1, choice2 in zip(
              examples["choice1"], examples["choice2"]
          )
      ]
  
      return {"contexts": contexts, "choices": choices}
  
file_path: DeepPavlov/deeppavlov/dataset_readers/huggingface_dataset_reader.py
imports: import re
  from collections import Counter
  from math import floor
  from typing import Dict, Optional, List, Union
  from datasets import load_dataset, Dataset, Features, ClassLabel, concatenate_datasets
  from deeppavlov.core.common.registry import register
  from deeppavlov.core.data.dataset_reader import DatasetReader
label_desc: Use image node_id 2 for calling a global function with example usage: preprocess_copa(examples) and returns: dict