


import unicodedata
from dataclasses import dataclass
from typing import Optional, Union

import numpy as np

from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase



def 	_lowerCAmelCase  (							lowerCAmelCase_							:Dict						,  lowerCAmelCase_							:Optional[Any]						,  lowerCAmelCase_							:int						,  lowerCAmelCase_							:Any							)->List[str]:
   '''simple docstring'''






   if isinstance(lowercase__						,  lowercase__							):
      snake_case_    			=    np.full((len(lowercase__							), sequence_length, 2)						,  lowercase__							)
   else:
      snake_case_    			=    np.full((len(lowercase__							), sequence_length)						,  lowercase__							)

   for i, tensor in enumerate(lowercase__							):
      if padding_side == "right":
         if isinstance(lowercase__						,  lowercase__							):
            snake_case_    			=    tensor[:sequence_length]
         else:
            snake_case_    			=    tensor[:sequence_length]
      else:
         if isinstance(lowercase__						,  lowercase__							):
            snake_case_    			=    tensor[:sequence_length]
         else:
            snake_case_    			=    tensor[:sequence_length]

   return out_tensor.tolist()



def 	_lowerCAmelCase  (							lowerCAmelCase_							:Any							)->Optional[int]:
   '''simple docstring'''






   snake_case_    			=    ord(lowercase__							)
   if (cp >= 33 and cp <= 47) or (cp >= 58 and cp <= 64) or (cp >= 91 and cp <= 96) or (cp >= 123 and cp <= 126):
      return True
   snake_case_    			=    unicodedata.category(lowercase__							)
   if cat.startswith("P"							):
      return True
   return False



@dataclass
class 			__lowerCAmelCase   (       A__    ):






  """simple docstring"""





  _SCREAMING_SNAKE_CASE									=				42
  _SCREAMING_SNAKE_CASE									=				True
  _SCREAMING_SNAKE_CASE									=				None
  _SCREAMING_SNAKE_CASE									=				None
  _SCREAMING_SNAKE_CASE									=				-100
  _SCREAMING_SNAKE_CASE									=				"pt"



  def     lowerCAmelCase__     (   self				:				Tuple			, _lowerCAmelCase				:				Any     )      ->       List[Any]:




     """simple docstring"""
     import torch

     snake_case_    			=    '''label''' if '''label''' in features[0].keys() else '''labels'''
     snake_case_    			=    [feature[label_name] for feature in features] if label_name in features[0].keys() else None
     snake_case_    			=    self.tokenizer.pad(
         lowerCAmelCase__			, padding=self.padding			, max_length=self.max_length			, pad_to_multiple_of=self.pad_to_multiple_of			, return_tensors="pt" if labels is None else None			, )

     if labels is None:
        return batch

     snake_case_    			=    torch.tensor(batch["entity_ids"]     ).shape[1]
     snake_case_    			=    self.tokenizer.padding_side
     if padding_side == "right":
        snake_case_    			=    [
            list(lowerCAmelCase__     ) + [self.label_pad_token_id] * (sequence_length - len(lowerCAmelCase__     )) for label in labels
        ]
     else:
        snake_case_    			=    [
            [self.label_pad_token_id] * (sequence_length - len(lowerCAmelCase__     )) + list(lowerCAmelCase__     ) for label in labels
        ]

     snake_case_    			=    [feature['''ner_tags'''] for feature in features]
     snake_case_    			=    padding_tensor(lowerCAmelCase__			, -1			, lowerCAmelCase__			, lowerCAmelCase__     )
     snake_case_    			=    [feature['''original_entity_spans'''] for feature in features]
     snake_case_    			=    padding_tensor(lowerCAmelCase__			, (-1, -1)			, lowerCAmelCase__			, lowerCAmelCase__     )
     snake_case_    			=    {k: torch.tensor(lowerCAmelCase__			, dtype=torch.intaa     ) for k, v in batch.items()}

     return batch








def        _UpperCamelCase							(      lowercase__    ,       lowercase__    ,       lowercase__=False      ):

						if isinstance(lowercase__    ,       lowercase__      ) and isinstance(lowercase__    ,       lowercase__      ):
												__SCREAMING_SNAKE_CASE						:     List[str]					=		len(set_a.intersection(lowercase__      )      )

												if alternative_union:
																		__SCREAMING_SNAKE_CASE						:     int					=		len(lowercase__      ) + len(lowercase__      )
												else:
																		__SCREAMING_SNAKE_CASE						:     int					=		len(set_a.union(lowercase__      )      )

												return intersection / union

						if isinstance(lowercase__    ,       (list, tuple)      ) and isinstance(lowercase__    ,       (list, tuple)      ):
												__SCREAMING_SNAKE_CASE						:     Dict					=		[element for element in set_a if element in set_b]

												if alternative_union:
																		__SCREAMING_SNAKE_CASE						:     Optional[int]					=		len(lowercase__      ) + len(lowercase__      )
																		return len(lowercase__      ) / union
												else:
																		__SCREAMING_SNAKE_CASE						:     Tuple					=		set_a + [element for element in set_b if element not in set_a]
																		return len(lowercase__      ) / len(lowercase__      )

												return len(lowercase__      ) / len(lowercase__      )
						return None


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