class_docstr: Loads examples from the Ted Talk translation dataset using the
  `datasets` package.
  
  dataset source: http://www.cs.jhu.edu/~kevinduh/a/multitarget-tedtalks/
code: def __init__(
      self,
      source_lang="en",
      target_lang="de",
      split="test",
      shuffle=False,
  ):
      self._dataset = datasets.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.shuffled = shuffle
      self.label_map = None
      self.output_scale_factor = None
      self.label_names = None
      # self.input_columns = ("Source",)
      # self.output_column = "Translation"
  
      if shuffle:
          self._dataset.shuffle()
  
file_path: TextAttack/textattack/datasets/helpers/ted_multi.py
imports: import collections
  import datasets
  import numpy
  from textattack.datasets import HuggingFaceDataset
label_desc: Use image node_id 1 to create a new TedMultiTranslationDataset object from inherited base classes: HuggingFaceDataset with example: obj = TedMultiTranslationDataset(source_lang, target_lang, split, shuffle)