





import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
    from transformers import AutoModelForSeqaSeqLM, AutoTokenizer





@require_torch
@require_sentencepiece
@require_tokenizers
class 					A__       (				unittest.TestCase      ):




   """simple docstring"""



   @slow
   def 				__lowercase						(   self)     ->		Optional[int]:







          '''simple docstring'''

          a__		:      Tuple					=							AutoModelForSeqaSeqLM.from_pretrained('google/mt5-small'   ,    return_dict=_a).to(_a)
          a__		:      Union[str, Any]					=							AutoTokenizer.from_pretrained('google/mt5-small')

          a__		:      Optional[Any]					=							tokenizer('Hello there'   ,    return_tensors='pt').input_ids
          a__		:      Union[str, Any]					=							tokenizer('Hi I am'   ,    return_tensors='pt').input_ids

          a__		:      int					=							model(input_ids.to(_a)   ,    labels=labels.to(_a)).loss
          a__		:      str					=							-(labels.shape[-1] * loss.item())

          a__		:      List[str]					=							-84.9127
          self.assertTrue(abs(mtf_score - EXPECTED_SCORE) < 1e-4)




"""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))


