class_docstr: Task for training cross-lingual language models.
  For more details look at: https://arxiv.org/pdf/1901.07291.pdf
  Args:
      dictionary (MaskedLMDictionary): the dictionary for the input of the task
class_docstr_tok: ["Task","for","training","cross-lingual","language","models",".","For","more","details","look","at",":","https",":","\/\/arxiv.org\/pdf\/1901.07291.pdf","Args",":","dictionary","(","MaskedLMDictionary",")",":","the","dictionary","for","the","input","of","the","task"]
docstr: Setup the task.
docstr_tok: ["Setup","the","task","."]
code: def setup_task(cls, args, **kwargs):
      """Setup the task."""
      if getattr(args, "raw_text", False):
          args.dataset_impl = "raw"
      elif getattr(args, "lazy_load", False):
          args.dataset_impl = "lazy"
  
      dictionary = MaskedLMDictionary.load(
          os.path.join(args.data, args.source_vocab_file)
      )
  
      print("| dictionary: {} types".format(len(dictionary)))
  
      return cls(args, dictionary)
  
file_path: translate/pytorch_translate/tasks/cross_lingual_lm.py
imports: import os
  from fairseq import tokenizer
  from fairseq.tasks import register_task
  from fairseq.tasks.cross_lingual_lm import CrossLingualLMTask
  from pytorch_translate.data.masked_lm_dictionary import MaskedLMDictionary
label_desc: Use image node_id 4 for calling the PytorchTranslateCrossLingualLMTask obj's underlying member method code with example usage: obj.setup_task(cls, args) and returns: cls