





def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:str   ,   SCREAMING_SNAKE_CASE		:str   )      ->   float:

 def get_matched_characters(SCREAMING_SNAKE_CASE		:str   ,   SCREAMING_SNAKE_CASE		:str   ) -> str:
  __lowerCAmelCase					:	Any      =     []
  __lowerCAmelCase					:	Tuple      =     min(len(_stra   )   ,   len(_stra   )   ) // 2
  for i, l in enumerate(_stra   ):
   __lowerCAmelCase					:	Optional[Any]      =     int(max(0   ,   i - limit   )   )
   __lowerCAmelCase					:	Union[str, Any]      =     int(min(i + limit + 1   ,   len(_stra   )   )   )
   if l in _stra[left:right]:
    matched.append(SCREAMING_SNAKE_CASE   )
    __lowerCAmelCase					:	str      =     F'''{_stra[0:_stra.index(SCREAMING_SNAKE_CASE   )]} {_stra[_stra.index(SCREAMING_SNAKE_CASE   ) + 1:]}'''

  return "".join(SCREAMING_SNAKE_CASE   )

 # matching characters
 __lowerCAmelCase					:	Union[str, Any]      =     get_matched_characters(SCREAMING_SNAKE_CASE   ,   SCREAMING_SNAKE_CASE   )
 __lowerCAmelCase					:	Optional[Any]      =     get_matched_characters(SCREAMING_SNAKE_CASE   ,   SCREAMING_SNAKE_CASE   )
 __lowerCAmelCase					:	int      =     len(SCREAMING_SNAKE_CASE   )

 # transposition
 __lowerCAmelCase					:	Optional[Any]      =     (
     len([(ca, ca) for ca, ca in zip(SCREAMING_SNAKE_CASE   ,   SCREAMING_SNAKE_CASE   ) if ca != ca]   ) // 2
 )

 if not match_count:
  __lowerCAmelCase					:	int      =     0.0
 else:
  __lowerCAmelCase					:	List[str]      =     (
      1
      / 3
      * (
          match_count / len(SCREAMING_SNAKE_CASE   )
          + match_count / len(SCREAMING_SNAKE_CASE   )
          + (match_count - transpositions) / match_count
      )
  )

 # common prefix up to 4 characters
 __lowerCAmelCase					:	Union[str, Any]      =     0
 for ca, ca in zip(stra[:4]   ,   stra[:4]   ):
  if ca == ca:
   prefix_len += 1
  else:
   break

 return jaro + 0.1 * prefix_len * (1 - jaro)


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      print(jaro_winkler('hello', 'world'))






import unittest

from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


_UpperCAmelCase             =							get_tests_dir('fixtures/test_sentencepiece_no_bos.model')






@require_sentencepiece
@require_tokenizers
class        snake_case_    (		__lowercase					,unittest.TestCase						):
  A_      							=   PegasusTokenizer
  A_      							=   PegasusTokenizerFast
  A_      							=   True
  A_      							=   True






  def 				UpperCAmelCase__						(							self			:					List[str]      )->Dict:






   '''simple docstring'''

   super().setUp()

   # We have a SentencePiece fixture for testing
   __lowerCAmelCase					:	Optional[int]      =       PegasusTokenizer(_snake_case      )
   tokenizer.save_pretrained(self.tmpdirname      )






  @cached_property
  def 				UpperCAmelCase__						(							self			:					str      )->Dict:






   '''simple docstring'''

   return PegasusTokenizer.from_pretrained("""google/pegasus-large"""      )






  def 				UpperCAmelCase__						(							self			:					Optional[Any]       ,  **_snake_case			:					Tuple      )->PegasusTokenizer:






   '''simple docstring'''

   return PegasusTokenizer.from_pretrained(self.tmpdirname       ,  **_snake_case      )






  def 				UpperCAmelCase__						(							self			:					Dict       ,  _snake_case			:					List[Any]      )->Tuple:






   '''simple docstring'''

   return ("This is a test", "This is a test")






  def 				UpperCAmelCase__						(							self			:					Union[str, Any]      )->Dict:






   '''simple docstring'''

   __lowerCAmelCase					:	Dict      =       """</s>"""
   __lowerCAmelCase					:	int      =       1

   self.assertEqual(self.get_tokenizer()._convert_token_to_id(_snake_case      )       ,  _snake_case      )
   self.assertEqual(self.get_tokenizer()._convert_id_to_token(_snake_case      )       ,  _snake_case      )






  def 				UpperCAmelCase__						(							self			:					int      )->Tuple:






   '''simple docstring'''

   __lowerCAmelCase					:	List[Any]      =       list(self.get_tokenizer().get_vocab().keys()      )

   self.assertEqual(vocab_keys[0]       ,  """<pad>"""      )
   self.assertEqual(vocab_keys[1]       ,  """</s>"""      )
   self.assertEqual(vocab_keys[-1]       ,  """v"""      )
   self.assertEqual(len(_snake_case      )       ,  1103      )






  def 				UpperCAmelCase__						(							self			:					Optional[int]      )->Optional[int]:






   '''simple docstring'''

   self.assertEqual(self.get_tokenizer().vocab_size       ,  1103      )






  def 				UpperCAmelCase__						(							self			:					Dict      )->str:






   '''simple docstring'''

   __lowerCAmelCase					:	Any      =       self.rust_tokenizer_class.from_pretrained(self.tmpdirname      )
   __lowerCAmelCase					:	Dict      =       self.tokenizer_class.from_pretrained(self.tmpdirname      )
   __lowerCAmelCase					:	str      =       (
       """Let's see which <unk> is the better <unk_token_11> one <mask_1> It seems like this <mask_2> was important"""
       """ </s> <pad> <pad> <pad>"""
   )
   __lowerCAmelCase					:	str      =       rust_tokenizer([raw_input_str]       ,  return_tensors=_snake_case       ,  add_special_tokens=_snake_case      ).input_ids[0]
   __lowerCAmelCase					:	Tuple      =       py_tokenizer([raw_input_str]       ,  return_tensors=_snake_case       ,  add_special_tokens=_snake_case      ).input_ids[0]
   self.assertListEqual(_snake_case       ,  _snake_case      )






  def 				UpperCAmelCase__						(							self			:					Optional[int]      )->Union[str, Any]:






   '''simple docstring'''

   __lowerCAmelCase					:	List[str]      =       self._large_tokenizer
   # <mask_1> masks whole sentence while <mask_2> masks single word
   __lowerCAmelCase					:	Tuple      =       """<mask_1> To ensure a <mask_2> flow of bank resolutions."""
   __lowerCAmelCase					:	List[str]      =       [2, 413, 615, 114, 3, 1971, 113, 1679, 10710, 107, 1]
   __lowerCAmelCase					:	str      =       tokenizer([raw_input_str]       ,  return_tensors=_snake_case      ).input_ids[0]
   self.assertListEqual(_snake_case       ,  _snake_case      )






  def 				UpperCAmelCase__						(							self			:					List[str]      )->List[str]:






   '''simple docstring'''

   __lowerCAmelCase					:	Optional[Any]      =       self._large_tokenizer
   # The tracebacks for the following asserts are **better** without messages or self.assertEqual
   assert tokenizer.vocab_size == 96103
   assert tokenizer.pad_token_id == 0
   assert tokenizer.eos_token_id == 1
   assert tokenizer.offset == 103
   assert tokenizer.unk_token_id == tokenizer.offset + 2 == 105
   assert tokenizer.unk_token == "<unk>"
   assert tokenizer.model_max_length == 1024
   __lowerCAmelCase					:	Tuple      =       """To ensure a smooth flow of bank resolutions."""
   __lowerCAmelCase					:	Optional[Any]      =       [413, 615, 114, 2291, 1971, 113, 1679, 10710, 107, 1]
   __lowerCAmelCase					:	int      =       tokenizer([raw_input_str]       ,  return_tensors=_snake_case      ).input_ids[0]
   self.assertListEqual(_snake_case       ,  _snake_case      )
   assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]      ) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]






  @require_torch
  def 				UpperCAmelCase__						(							self			:					Any      )->Any:






   '''simple docstring'''

   __lowerCAmelCase					:	List[Any]      =       ["""This is going to be way too long.""" * 150, """short example"""]
   __lowerCAmelCase					:	Union[str, Any]      =       ["""not super long but more than 5 tokens""", """tiny"""]
   __lowerCAmelCase					:	Dict      =       self._large_tokenizer(_snake_case       ,  padding=_snake_case       ,  truncation=_snake_case       ,  return_tensors="""pt"""      )
   __lowerCAmelCase					:	Tuple      =       self._large_tokenizer(
       text_target=_snake_case       ,  max_length=5       ,  padding=_snake_case       ,  truncation=_snake_case       ,  return_tensors="""pt"""      )

   assert batch.input_ids.shape == (2, 1024)
   assert batch.attention_mask.shape == (2, 1024)
   assert targets["input_ids"].shape == (2, 5)
   assert len(_snake_case      ) == 2  # input_ids, attention_mask.






  @slow
  def 				UpperCAmelCase__						(							self			:					Optional[Any]      )->Any:






   '''simple docstring'''

   __lowerCAmelCase					:	Optional[Any]      =       {"""input_ids""": [[38979, 143, 18485, 606, 130, 26669, 87686, 121, 54189, 1129, 111, 26669, 87686, 121, 9114, 14787, 121, 13249, 158, 592, 956, 121, 14621, 31576, 143, 62613, 108, 9688, 930, 43430, 11562, 62613, 304, 108, 11443, 897, 108, 9314, 17415, 63399, 108, 11443, 7614, 18316, 118, 4284, 7148, 12430, 143, 1400, 25703, 158, 111, 4284, 7148, 11772, 143, 21297, 1064, 158, 122, 204, 3506, 1754, 1133, 14787, 1581, 115, 33224, 4482, 111, 1355, 110, 29173, 317, 50833, 108, 20147, 94665, 111, 77198, 107, 1], [110, 62613, 117, 638, 112, 1133, 121, 20098, 1355, 79050, 13872, 135, 1596, 53541, 1352, 141, 13039, 5542, 124, 302, 518, 111, 268, 2956, 115, 149, 4427, 107, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [139, 1235, 2799, 18289, 17780, 204, 109, 9474, 1296, 107, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
   # fmt: on

   self.tokenizer_integration_test_util(
       expected_encoding=_snake_case       ,  model_name="""google/bigbird-pegasus-large-arxiv"""       ,  revision="""ba85d0851d708441f91440d509690f1ab6353415"""       ,  )






@require_sentencepiece
@require_tokenizers
class        snake_case_    (		__lowercase					,unittest.TestCase						):
  A_      							=   PegasusTokenizer
  A_      							=   PegasusTokenizerFast
  A_      							=   True
  A_      							=   True






  def 				UpperCAmelCase__						(							self			:					Tuple      )->Tuple:






   '''simple docstring'''

   super().setUp()

   # We have a SentencePiece fixture for testing
   __lowerCAmelCase					:	Any      =       PegasusTokenizer(_snake_case       ,  offset=0       ,  mask_token_sent=_snake_case       ,  mask_token="""[MASK]"""      )
   tokenizer.save_pretrained(self.tmpdirname      )






  @cached_property
  def 				UpperCAmelCase__						(							self			:					Any      )->str:






   '''simple docstring'''

   return PegasusTokenizer.from_pretrained("""google/bigbird-pegasus-large-arxiv"""      )






  def 				UpperCAmelCase__						(							self			:					Union[str, Any]       ,  **_snake_case			:					Optional[Any]      )->PegasusTokenizer:






   '''simple docstring'''

   return PegasusTokenizer.from_pretrained(self.tmpdirname       ,  **_snake_case      )






  def 				UpperCAmelCase__						(							self			:					List[str]       ,  _snake_case			:					Optional[int]      )->Union[str, Any]:






   '''simple docstring'''

   return ("This is a test", "This is a test")






  def 				UpperCAmelCase__						(							self			:					List[Any]      )->str:






   '''simple docstring'''

   __lowerCAmelCase					:	Tuple      =       self.rust_tokenizer_class.from_pretrained(self.tmpdirname      )
   __lowerCAmelCase					:	List[str]      =       self.tokenizer_class.from_pretrained(self.tmpdirname      )
   __lowerCAmelCase					:	int      =       (
       """Let's see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>"""
       """ <pad> <pad> <pad>"""
   )
   __lowerCAmelCase					:	str      =       rust_tokenizer([raw_input_str]       ,  return_tensors=_snake_case       ,  add_special_tokens=_snake_case      ).input_ids[0]
   __lowerCAmelCase					:	Tuple      =       py_tokenizer([raw_input_str]       ,  return_tensors=_snake_case       ,  add_special_tokens=_snake_case      ).input_ids[0]
   self.assertListEqual(_snake_case       ,  _snake_case      )






  @require_torch
  def 				UpperCAmelCase__						(							self			:					str      )->Optional[Any]:






   '''simple docstring'''

   __lowerCAmelCase					:	int      =       ["""This is going to be way too long.""" * 1000, """short example"""]
   __lowerCAmelCase					:	Optional[int]      =       ["""not super long but more than 5 tokens""", """tiny"""]
   __lowerCAmelCase					:	str      =       self._large_tokenizer(_snake_case       ,  padding=_snake_case       ,  truncation=_snake_case       ,  return_tensors="""pt"""      )
   __lowerCAmelCase					:	List[Any]      =       self._large_tokenizer(
       text_target=_snake_case       ,  max_length=5       ,  padding=_snake_case       ,  truncation=_snake_case       ,  return_tensors="""pt"""      )

   assert batch.input_ids.shape == (2, 4096)
   assert batch.attention_mask.shape == (2, 4096)
   assert targets["input_ids"].shape == (2, 5)
   assert len(_snake_case      ) == 2  # input_ids, attention_mask.






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






   '''simple docstring'''

   __lowerCAmelCase					:	Tuple      =       (
       """This is an example string that is used to test the original TF implementation against the HF"""
       """ implementation"""
   )

   __lowerCAmelCase					:	Optional[Any]      =       self._large_tokenizer(_snake_case      ).input_ids

   self.assertListEqual(
       _snake_case       ,  [182, 117, 142, 587, 4211, 120, 117, 263, 112, 804, 109, 856, 25016, 3137, 464, 109, 26955, 3137, 1]       ,  )