




from typing import List

from tokenizers import NormalizedString, PreTokenizedString, normalizers





class 		A__				:






	def __init__(	self				,     lowerCamelCase						)      ->   None:




						"""simple docstring"""






						__magic_name__					:							Any		   =							vocab
						__magic_name__					:							Union[str, Any]		   =							normalizers.BertNormalizer(
						    clean_text=lowerCamelCase				,     handle_chinese_chars=lowerCamelCase				,     strip_accents=lowerCamelCase				,     lowercase=lowerCamelCase				,     )
						try:
											import rjieba
						except ImportError:
											raise ImportError(
											    '''You need to install rjieba to use RoFormerTokenizer. '''
											    '''See https://pypi.org/project/rjieba/ for installation.'''						)
						__magic_name__					:							Any		   =							rjieba






	def  lowercase      (	self				,     lowerCamelCase				,     lowerCamelCase						)      ->   List[NormalizedString]:




						"""simple docstring"""






						__magic_name__					:							int		   =							[]

						# this code slice normalized_string is too slow (6s) but test_alignement_methods can pass
						for token, start, end in self.jieba.tokenize(str(lowerCamelCase						)				,     hmm=lowerCamelCase						):
											if token in self.vocab:
																splits.append(normalized_string[start:end]						)
											else:
																__magic_name__					:							Optional[Any]		   =							self.normalizers.normalize_str(lowerCamelCase						).split()
																for token in token_list:
																					if token:
																										__magic_name__					:							Optional[Any]		   =							start + len(lowerCamelCase						)
																										splits.append(normalized_string[start:end]						)
																										__magic_name__					:							int		   =							end

        # this code test_alignement_methods can't pass but fast (300ms)
        # for token in self.jieba.cut(str(normalized_string), False):
        #     if token in self.vocab:
        #         splits.append(NormalizedString(token))
        #     else:
        #         token_list = self.normalizers.normalize_str(token).split()
        #         for token in token_list:
        #             if token:
        #                 splits.append(NormalizedString(token))

						return splits






	def  lowercase      (	self				,     lowerCamelCase						)      ->   List[Any]:




						"""simple docstring"""






						pretok.split(self.jieba_split						)










"""simple docstring"""




from functools import lru_cache





@lru_cache
def        a_				(							_lowercase   ):
						if not isinstance(_lowercase       ,						_lowercase   ):
												raise TypeError('''k must be an integer.'''   )
						if k < 0:
												raise ValueError('''k integer must be greater or equal to zero.'''   )
						if k == 0:
												return 0
						elif k == 1:
												return 1
						else:
												return fibonacci(k - 1   ) + fibonacci(k - 2   )





def        a_				(							_lowercase       ,						_lowercase   ):
						_UpperCamelCase			:					Any     =    len(_lowercase   )
						# Find m such that F_m >= n where F_i is the i_th fibonacci number.
						_UpperCamelCase			:					Optional[int]     =    0
						while True:
												if fibonacci(_lowercase   ) >= len_list:
																		_UpperCamelCase			:					List[Any]     =    i
																		break
												i += 1
						_UpperCamelCase			:					Tuple     =    0
						while fibb_k > 0:
												_UpperCamelCase			:					Union[str, Any]     =    min(
												    offset + fibonacci(fibb_k - 1   )       ,						len_list - 1   )  # Prevent out of range
												_UpperCamelCase			:					Any     =    arr[index_k]
												if item_k_1 == val:
																		return index_k
												elif val < item_k_1:
																		fibb_k -= 1
												elif val > item_k_1:
																		offset += fibonacci(fibb_k - 1   )
																		fibb_k -= 2
						else:
												return -1


if __name__ == "__main__":
						import doctest

						doctest.testmod()



