





from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
    LineByLineTextDataset,
    LineByLineWithRefDataset,
    LineByLineWithSOPTextDataset,
    TextDataset,
    TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments









from pathlib import Path

import fire



def    __lowercase   (      _SCREAMING_SNAKE_CASE ,						_SCREAMING_SNAKE_CASE ,						_SCREAMING_SNAKE_CASE	) ->   List[str]:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE		=						Path(_SCREAMING_SNAKE_CASE	)
      SCREAMING_SNAKE_CASE		=						Path(_SCREAMING_SNAKE_CASE	)
      dest_dir.mkdir(exist_ok=_SCREAMING_SNAKE_CASE	)
      for path in src_dir.iterdir():
            SCREAMING_SNAKE_CASE		=						[x.rstrip() for x in list(path.open().readlines()	)][:n]
            SCREAMING_SNAKE_CASE		=						dest_dir.joinpath(path.name	)
            print(_SCREAMING_SNAKE_CASE	)
            dest_path.open("""w"""	).write("""\n""".join(_SCREAMING_SNAKE_CASE	)	)


if __name__ == "__main__":
      fire.Fire(minify)


