






from pathlib import Path

import fire
from tqdm import tqdm
def 		lowercase__  (				_UpperCamelCase="ro"       ,							_UpperCamelCase="en"       ,							_UpperCamelCase="wmt16"       ,							_UpperCamelCase=None) ->			None:
      """simple docstring"""

      try:
            import datasets
      except (ModuleNotFoundError, ImportError):
            raise ImportError('run pip install datasets')
      UpperCamelCase					       =  F'{src_lang}-{tgt_lang}'
      print(F'Converting {dataset}-{pair}')
      UpperCamelCase					       =  datasets.load_dataset(_UpperCamelCase       ,							_UpperCamelCase)
      if save_dir is None:
            UpperCamelCase					       =  F'{dataset}-{pair}'
      UpperCamelCase					       =  Path(_UpperCamelCase)
      save_dir.mkdir(exist_ok=_UpperCamelCase)

      for split in ds.keys():
            print(F'Splitting {split} with {ds[split].num_rows} records')

            # to save to val.source, val.target like summary datasets
            UpperCamelCase					       =  'val' if split == 'validation' else split
            UpperCamelCase					       =  save_dir.joinpath(F'{fn}.source')
            UpperCamelCase					       =  save_dir.joinpath(F'{fn}.target')
            UpperCamelCase					       =  src_path.open('w+')
            UpperCamelCase					       =  tgt_path.open('w+')

            # reader is the bottleneck so writing one record at a time doesn't slow things down
            for x in tqdm(ds[split]):
                  UpperCamelCase					       =  x['translation']
                  src_fp.write(ex[src_lang] + '\n')
                  tgt_fp.write(ex[tgt_lang] + '\n')

      print(F'Saved {dataset} dataset to {save_dir}')


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











def 		lowercase__  (				_UpperCamelCase       ,							_UpperCamelCase) ->			bool:
      """simple docstring"""

      return numa ^ numa < 0


if __name__ == "__main__":
       import doctest

       doctest.testmod()



