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"]
code: def build_dictionary(
      cls,
      filenames,
      workers=1,
      threshold=-1,
      nwords=-1,
      padding_factor=8,
  ):
      d = MaskedLMDictionary()
      for filename in filenames:
          MaskedLMDictionary.add_file_to_dictionary(
              filename, d, tokenizer.tokenize_line, workers
          )
      d.finalize(
          threshold=threshold,
          nwords=nwords,
          padding_factor=padding_factor,
      )
      return d
  
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 3 for calling the PytorchTranslateCrossLingualLMTask obj's underlying member method code with example usage: obj.build_dictionary(cls, filenames, workers, threshold, nwords, padding_factor) and returns: d