




'''simple docstring'''



import fire
from torch.utils.data import DataLoader
from tqdm import tqdm

from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def 			SCREAMING_SNAKE_CASE_			(							__A    :			Union[str, Any]	,					__A    :			Union[str, Any]	,					__A    :			Optional[Any]=10_24	,					__A    :			List[str]=10_24	,					__A    :			Union[str, Any]=False	,					**__A    :			Tuple  )			->			Dict:
   _SCREAMING_SNAKE_CASE	=				AutoTokenizer.from_pretrained(__A  )
   _SCREAMING_SNAKE_CASE	=				SeqaSeqDataset(__A	,					__A	,					__A	,					__A	,					type_path="train"	,					**__A  )
   _SCREAMING_SNAKE_CASE	=				tok.pad_token_id

   def get_lens(__A    :			Tuple  ):
      _SCREAMING_SNAKE_CASE	=				tqdm(
          DataLoader(__A	,					batch_size=5_12	,					num_workers=8	,					shuffle=__A	,					collate_fn=ds.collate_fn  )	,					desc=str(ds.len_file  )	,					)
      _SCREAMING_SNAKE_CASE	=				[]
      for batch in dl:
         _SCREAMING_SNAKE_CASE	=				batch["input_ids"].ne(__A  ).sum(1  ).tolist()
         _SCREAMING_SNAKE_CASE	=				batch["labels"].ne(__A  ).sum(1  ).tolist()
         if consider_target:
            for src, tgt in zip(__A	,					__A  ):
               max_lens.append(max(__A	,					__A  )  )
         else:
            max_lens.extend(__A  )
      return max_lens

   _SCREAMING_SNAKE_CASE	=				get_lens(__A  )
   _SCREAMING_SNAKE_CASE	=				SeqaSeqDataset(__A	,					__A	,					__A	,					__A	,					type_path="val"	,					**__A  )
   _SCREAMING_SNAKE_CASE	=				get_lens(__A  )
   pickle_save(__A	,					train_ds.len_file  )
   pickle_save(__A	,					val_ds.len_file  )


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







'''simple docstring'''



lowerCamelCase_			=						'Tobias Carryer'

from time import time







class 		lowercase_   :


   """simple docstring"""

   def __init__(   self :     Tuple  ,				__lowerCamelCase :     int  ,				__lowerCamelCase :     List[Any]  ,				__lowerCamelCase :     Optional[int]  ,				__lowerCamelCase :     Dict=int(time()   )   ):  # noqa: B008

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				multiplier
      _SCREAMING_SNAKE_CASE	=				increment
      _SCREAMING_SNAKE_CASE	=				modulo
      _SCREAMING_SNAKE_CASE	=				seed



   def 							lowerCAmelCase_      (   self :     List[str]   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				(self.multiplier * self.seed + self.increment) % self.modulo
      return self.seed


if __name__ == "__main__":
 # Show the LCG in action.
 lowerCamelCase_			=						LinearCongruentialGenerator(1_66_45_25, 10_13_90_42_23, 2 << 31)
 while True:
  print(lcg.next_number())

