






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  _lowercase   (   unittest.TestCase						):
      def 						lowercase__					(     self   ):
       snake_case__  :    List[str]							       ="""hf-internal-testing/tiny-random-t5"""
       snake_case__  :    Optional[int]							       =AutoTokenizer.from_pretrained(a   )
       snake_case__  :    Dict							       =AutoModelForSeqaSeqLM.from_pretrained(a   )

       snake_case__  :    Tuple							       =tokenizer("""This is me"""				,			return_tensors="""pt"""   )

       snake_case__  :    int							       =model.to_bettertransformer()

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

       snake_case__  :    Optional[int]							       =model.generate(**a   )

       snake_case__  :    List[Any]							       =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(a   )

        snake_case__  :    Any							       =AutoModelForSeqaSeqLM.from_pretrained(a   )

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

        snake_case__  :    Optional[int]							       =model_reloaded.generate(**a   )
        self.assertTrue(torch.allclose(a				,			a   )   )



      def 						lowercase__					(     self   ):
       snake_case__  :    Tuple							       ="""hf-internal-testing/tiny-random-t5"""
       snake_case__  :    Any							       =AutoModelForSeqaSeqLM.from_pretrained(a   )

       snake_case__  :    Dict							       =model.to_bettertransformer()

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

        snake_case__  :    Optional[int]							       =model.reverse_bettertransformer()
        model.save_pretrained(a   )













def 			A__							(      _a  :					Optional[Any]		,  _a  :					Tuple		,  _a  :					List[str]=False	):





 '''simple docstring'''







 if isinstance(_a		,  _a	) and isinstance(_a		,  _a	):
  snake_case__  :    int							       =len(set_a.intersection(_a	)	)

  if alternative_union:
   snake_case__  :    int							       =len(_a	) + len(_a	)
  else:
   snake_case__  :    Tuple							       =len(set_a.union(_a	)	)

  return intersection / union

 if isinstance(_a		,  (list, tuple)	) and isinstance(_a		,  (list, tuple)	):
  snake_case__  :    Optional[int]							       =[element for element in set_a if element in set_b]

  if alternative_union:
   snake_case__  :    Optional[Any]							       =len(_a	) + len(_a	)
   return len(_a	) / union
  else:
   snake_case__  :    Dict							       =set_a + [element for element in set_b if element not in set_a]
   return len(_a	) / len(_a	)

  return len(_a	) / len(_a	)
 return None


if __name__ == "__main__":
       __lowerCamelCase	:		List[Any]										=   {"""a""", """b""", """c""", """d""", """e"""}
       __lowerCamelCase	:		Optional[int]										=   {"""c""", """d""", """e""", """f""", """h""", """i"""}
       print(jaccard_similarity(set_a, set_b))





