text: import collections
  
  import nlp
  import numpy as np
  
  from textattack.datasets import HuggingFaceNLPDataset
  
  
  class TedMultiTranslationDataset(HuggingFaceNLPDataset):
      """ Loads examples from the Ted Talk translation dataset using the `nlp`
          package.
  
          dataset source: http://www.cs.jhu.edu/~kevinduh/a/multitarget-tedtalks/
      """
  
      def __init__(self, source_lang="en", target_lang="de", split="test"):
          self._dataset = nlp.load_dataset("ted_multi")[split]
          self.examples = self._dataset["translations"]
          language_options = set(self.examples[0]["language"])
          if source_lang not in language_options:
              raise ValueError(
                  f"Source language {source_lang} invalid. Choices: {sorted(language_options)}"
              )
          if target_lang not in language_options:
              raise ValueError(
                  f"Target language {target_lang} invalid. Choices: {sorted(language_options)}"
              )
          self.source_lang = source_lang
          self.target_lang = target_lang
          self.label_names = ("Translation",)
  
      def _format_raw_example(self, raw_example):
          translations = np.array(raw_example["translation"])
          languages = np.array(raw_example["language"])
          source = translations[languages == self.source_lang][0]
          target = translations[languages == self.target_lang][0]
          source_dict = collections.OrderedDict([("Source", source)])
          return (source_dict, target)
  