






from typing import List

from tokenizers import NormalizedString, PreTokenizedString, normalizers
class 							__snake_case:



 def __init__(						self : Tuple			,		UpperCAmelCase__ : List[str]						):

    """simple docstring"""






    lowercase__    :						Dict       =			vocab
    lowercase__    :						Dict       =			normalizers.BertNormalizer(
        clean_text=lowercase__			,		handle_chinese_chars=lowercase__			,		strip_accents=lowercase__			,		lowercase=lowercase__			,		)
    try:
       import rjieba
    except ImportError:
       raise ImportError(
           """You need to install rjieba to use RoFormerTokenizer. """
           """See https://pypi.org/project/rjieba/ for installation."""						)
    lowercase__    :						Any       =			rjieba



 def     UpperCAmelCase     (						self : Optional[int]			,		UpperCAmelCase__ : int			,		UpperCAmelCase__ : NormalizedString						):

    """simple docstring"""






    lowercase__    :						List[Any]       =			[]

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

    """simple docstring"""






    pretok.split(self.jieba_split						)







def 		__snake_case						(    _UpperCAmelCase       ,			_UpperCAmelCase				):
					"""simple docstring"""






					for index, item in enumerate(_UpperCAmelCase				):
										if item == target:
															return index
					return -1





def 		__snake_case						(    _UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase				):
					"""simple docstring"""






					if not (0 <= high < len(_UpperCAmelCase				) and 0 <= low < len(_UpperCAmelCase				)):
										raise Exception('Invalid upper or lower bound!'				)
					if high < low:
										return -1
					if sequence[low] == target:
										return low
					if sequence[high] == target:
										return high
					return rec_linear_search(_UpperCAmelCase       ,			low + 1       ,			high - 1       ,			_UpperCAmelCase				)


if __name__ == "__main__":
		__magic_name__       =     input('''Enter numbers separated by comma:\n''').strip()
		__magic_name__       =     [int(item.strip()) for item in user_input.split(''',''')]

		__magic_name__       =     int(input('''Enter a single number to be found in the list:\n''').strip())
		__magic_name__       =     linear_search(sequence, target)
		if result != -1:
				print(F"""linear_search({sequence}, {target}) = {result}""")
		else:
				print(F"""{target} was not found in {sequence}""")






