





import argparse
import shutil
from pathlib import Path

from tqdm import tqdm

from transformers import AutoTokenizer



def A_      (						A__						, A__						, A__						, A__=1024							)    ->						List[str]:
       a__		:      int					=							[], []

       a__		:      Optional[Any]					=							list(zip(__snake_case						, __snake_case							)							)
       a__		:      str					=							sorted_examples[0]

       def is_too_big(A__							):
              return tok(__snake_case						, return_tensors='pt'							).input_ids.shape[1] > max_tokens

       for src, tgt in tqdm(sorted_examples[1:]							):
              a__		:      List[str]					=							new_src + " " + src
              a__		:      Dict					=							new_tgt + " " + tgt
              if is_too_big(__snake_case							) or is_too_big(__snake_case							):  # cant fit, finalize example
                     finished_src.append(__snake_case							)
                     finished_tgt.append(__snake_case							)
                     a__		:      str					=							src, tgt
              else:  # can fit, keep adding
                     a__		:      Union[str, Any]					=							cand_src, cand_tgt

    # cleanup
       if new_src:
              assert new_tgt
              finished_src.append(__snake_case							)
              finished_tgt.append(__snake_case							)
       return finished_src, finished_tgt



def A_      (						A__						, A__						, A__						, A__							)    ->						int:
       a__		:      Tuple					=							Path(__snake_case							)
       save_path.mkdir(exist_ok=__snake_case							)
       for split in ["train"]:
              a__		:      Any					=							data_dir / F'{split}.source', data_dir / F'{split}.target'
              a__		:      List[Any]					=							[x.rstrip() for x in Path(__snake_case							).open().readlines()]
              a__		:      int					=							[x.rstrip() for x in Path(__snake_case							).open().readlines()]
              a__		:      List[Any]					=							pack_examples(__snake_case						, __snake_case						, __snake_case						, __snake_case							)
              print(F'packed {split} split from {len(__snake_case							)} examples -> {len(__snake_case							)}.'							)
              Path(save_path / F'{split}.source'							).open('w'							).write('\n'.join(__snake_case							)							)
              Path(save_path / F'{split}.target'							).open('w'							).write('\n'.join(__snake_case							)							)
       for split in ["val", "test"]:
              a__		:      Dict					=							data_dir / F'{split}.source', data_dir / F'{split}.target'
              shutil.copyfile(__snake_case						, save_path / F'{split}.source'							)
              shutil.copyfile(__snake_case						, save_path / F'{split}.target'							)



def A_      (						)    ->						Any:
       a__		:      List[Any]					=							argparse.ArgumentParser()
       parser.add_argument('--tok_name'						, type=__snake_case						, help='like facebook/bart-large-cnn,t5-base, etc.'							)
       parser.add_argument('--max_seq_len'						, type=__snake_case						, default=128							)
       parser.add_argument('--data_dir'						, type=__snake_case							)
       parser.add_argument('--save_path'						, type=__snake_case							)
       a__		:      List[str]					=							parser.parse_args()
       a__		:      Optional[int]					=							AutoTokenizer.from_pretrained(args.tok_name							)
       return pack_data_dir(__snake_case						, Path(args.data_dir							)						, args.max_seq_len						, args.save_path							)


if __name__ == "__main__":
    packer_cli()




"""simple docstring"""




def     __magic_name__      ( __snake_case							:			Any	,					__snake_case							:			Union[str, Any]	,					__snake_case							:			Union[str, Any]=False    )					->							Optional[Any]:

       if isinstance(__snake_case	,					__snake_case    ) and isinstance(__snake_case	,					__snake_case    ):
              lowercase       :							Tuple									=				len(set_a.intersection(__snake_case    )    )

              if alternative_union:
                     lowercase       :							Union[str, Any]									=				len(__snake_case    ) + len(__snake_case    )
              else:
                     lowercase       :							Optional[Any]									=				len(set_a.union(__snake_case    )    )

              return intersection / union

       if isinstance(__snake_case	,					(list, tuple)    ) and isinstance(__snake_case	,					(list, tuple)    ):
              lowercase       :							Tuple									=				[element for element in set_a if element in set_b]

              if alternative_union:
                     lowercase       :							List[str]									=				len(__snake_case    ) + len(__snake_case    )
                     return len(__snake_case    ) / union
              else:
                     lowercase       :							Dict									=				set_a + [element for element in set_b if element not in set_a]
                     return len(__snake_case    ) / len(__snake_case    )

              return len(__snake_case    ) / len(__snake_case    )
       return None


if __name__ == "__main__":
   _A     :			List[str]  						=			{"""a""", """b""", """c""", """d""", """e"""}
   _A     :			Dict  						=			{"""c""", """d""", """e""", """f""", """h""", """i"""}
   print(jaccard_similarity(set_a, set_b))


