






'''simple docstring'''



import argparse
import shutil
from pathlib import Path

from tqdm import tqdm

from transformers import AutoTokenizer



def    __UpperCAmelCase	(				SCREAMING_SNAKE_CASE__:	str,					SCREAMING_SNAKE_CASE__:	int,					SCREAMING_SNAKE_CASE__:	List[str],					SCREAMING_SNAKE_CASE__:	str=1024    )  ->			Optional[Any]:

   """simple docstring"""
   __a     ,			__a				     =    [], []

   __a				     =    list(zip(_UpperCamelCase,					_UpperCamelCase    )    )
   __a     ,			__a				     =    sorted_examples[0]

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

   for src, tgt in tqdm(sorted_examples[1:]    ):
      __a				     =    new_src + ' ' + src
      __a				     =    new_tgt + ' ' + tgt
      if is_too_big(_UpperCamelCase    ) or is_too_big(_UpperCamelCase    ):  # cant fit, finalize example
         finished_src.append(_UpperCamelCase    )
         finished_tgt.append(_UpperCamelCase    )
         __a     ,			__a				     =    src, tgt
      else:  # can fit, keep adding
         __a     ,			__a				     =    cand_src, cand_tgt

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



def    __UpperCAmelCase	(				SCREAMING_SNAKE_CASE__:	List[str],					SCREAMING_SNAKE_CASE__:	Path,					SCREAMING_SNAKE_CASE__:	Optional[int],					SCREAMING_SNAKE_CASE__:	Any    )  ->			List[Any]:

   """simple docstring"""
   __a				     =    Path(_UpperCamelCase    )
   save_path.mkdir(exist_ok=_UpperCamelCase    )
   for split in ["train"]:
      __a     ,			__a				     =    data_dir / f"""{split}.source""", data_dir / f"""{split}.target"""
      __a				     =    [x.rstrip() for x in Path(_UpperCamelCase    ).open().readlines()]
      __a				     =    [x.rstrip() for x in Path(_UpperCamelCase    ).open().readlines()]
      __a     ,			__a				     =    pack_examples(_UpperCamelCase,					_UpperCamelCase,					_UpperCamelCase,					_UpperCamelCase    )
      print(f"""packed {split} split from {len(_UpperCamelCase    )} examples -> {len(_UpperCamelCase    )}."""    )
      Path(save_path / f"""{split}.source"""    ).open('w'    ).write('\n'.join(_UpperCamelCase    )    )
      Path(save_path / f"""{split}.target"""    ).open('w'    ).write('\n'.join(_UpperCamelCase    )    )
   for split in ["val", "test"]:
      __a     ,			__a				     =    data_dir / f"""{split}.source""", data_dir / f"""{split}.target"""
      shutil.copyfile(_UpperCamelCase,					save_path / f"""{split}.source"""    )
      shutil.copyfile(_UpperCamelCase,					save_path / f"""{split}.target"""    )



def    __UpperCAmelCase	(				)  ->			List[Any]:

   """simple docstring"""
   __a				     =    argparse.ArgumentParser()
   parser.add_argument('--tok_name',					type=_UpperCamelCase,					help='like facebook/bart-large-cnn,t5-base, etc.'    )
   parser.add_argument('--max_seq_len',					type=_UpperCamelCase,					default=128    )
   parser.add_argument('--data_dir',					type=_UpperCamelCase    )
   parser.add_argument('--save_path',					type=_UpperCamelCase    )
   __a				     =    parser.parse_args()
   __a				     =    AutoTokenizer.from_pretrained(args.tok_name    )
   return pack_data_dir(_UpperCamelCase,					Path(args.data_dir    ),					args.max_seq_len,					args.save_path    )


if __name__ == "__main__":
 packer_cli()








'''simple docstring'''



import warnings

from .generation import TFGenerationMixin
class 							__SCREAMING_SNAKE_CASE       (							_lowerCAmelCase     ):
      # warning at import time
      warnings.warn(
          "Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will "
          "be removed in Transformers v5. Import as `from transformers import TFGenerationMixin` instead."      ,      _lowerCAmelCase      ,      )