





import tempfile
import unittest

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
    is_torch_available,
    require_optimum,
    require_torch,
    slow,
)


if is_torch_available():
    import torch





@require_torch
@require_optimum
@slow
class  A__    (							unittest.TestCase	):




   """simple docstring"""



   def 							__lowercase		(					self)			->						Any:







          '''simple docstring'''

          a__						:	int =				'hf-internal-testing/tiny-random-t5'
          a__						:	List[str] =				AutoTokenizer.from_pretrained(lowercase)
          a__						:	Union[str, Any] =				AutoModelForSeqaSeqLM.from_pretrained(lowercase)

          a__						:	List[str] =				tokenizer('This is me'					,  return_tensors='pt')

          a__						:	List[Any] =				model.to_bettertransformer()

          self.assertTrue(any('BetterTransformer' in mod.__class__.__name__ for _, mod in model.named_modules()))

          a__						:	List[str] =				model.generate(**lowercase)

          a__						:	Tuple =				model.reverse_bettertransformer()

          self.assertFalse(any('BetterTransformer' in mod.__class__.__name__ for _, mod in model.named_modules()))

          with tempfile.TemporaryDirectory() as tmpdirname:
                 model.save_pretrained(lowercase)

                 a__						:	Tuple =				AutoModelForSeqaSeqLM.from_pretrained(lowercase)

                 self.assertFalse(
                     any('BetterTransformer' in mod.__class__.__name__ for _, mod in model_reloaded.named_modules()))

                 a__						:	Tuple =				model_reloaded.generate(**lowercase)
                 self.assertTrue(torch.allclose(lowercase					,  lowercase))

   def 							__lowercase		(					self)			->						Optional[Any]:







          '''simple docstring'''

          a__						:	Any =				'hf-internal-testing/tiny-random-t5'
          a__						:	str =				AutoModelForSeqaSeqLM.from_pretrained(lowercase)

          a__						:	Optional[Any] =				model.to_bettertransformer()

          with tempfile.TemporaryDirectory() as tmpdirname:
                 with self.assertRaises(lowercase):
                        model.save_pretrained(lowercase)

                 a__						:	str =				model.reverse_bettertransformer()
                 model.save_pretrained(lowercase)






"""simple docstring"""







from bisect import bisect
from itertools import accumulate


def      lowercase			(				A_  ,   A_  ,   A_  ,   A_       )->      Union[str, Any]:
  '''simple docstring'''







  a						:		Any      							=			sorted(zip(A_  ,   A_       )  ,   key=lambda A_       : x[0] / x[1]  ,   reverse=A_       )
  a							,		a						:		int      							=			[i[0] for i in r], [i[1] for i in r]
  a						:		Union[str, Any]      							=			list(accumulate(A_       )       )
  a						:		Optional[Any]      							=			bisect(A_  ,   A_       )
  return (
      0
      if k == 0
      else sum(vl[:k]       ) + (w - acc[k - 1]) * (vl[k]) / (wt[k])
      if k != n
      else sum(vl[:k]       )
  )


if __name__ == "__main__":
 import doctest

 doctest.testmod()






