
'''simple docstring'''







def 				_snake_case (		lowercase			,    lowercase			,    lowercase			,    lowercase						)       ->       Optional[int]:
				if start == end:
								return start if lst[start] > item else start + 1
				if start > end:
								return start

				__a       :     List[str]								=	(start + end) // 2
				if lst[mid] < item:
								return binary_search(lowercase			,    lowercase			,    mid + 1			,    lowercase						)
				elif lst[mid] > item:
								return binary_search(lowercase			,    lowercase			,    lowercase			,    mid - 1						)
				else:
								return mid

def 				_snake_case (		lowercase						)       ->       Tuple:
				__a       :     Union[str, Any]								=	len(lowercase						)

				for index in range(1			,    lowercase						):
								__a       :     int								=	lst[index]
								__a       :     Union[str, Any]								=	binary_search(lowercase			,    lowercase			,    0			,    index - 1						)
								__a       :     Dict								=	lst[:pos] + [value] + lst[pos:index] + lst[index + 1 :]

				return lst

def 				_snake_case (		lowercase			,    lowercase						)       ->       str:
				if not left:
								return right

				if not right:
								return left

				if left[0] < right[0]:
								return [left[0], *merge(left[1:]			,    lowercase						)]

				return [right[0], *merge(lowercase			,    right[1:]						)]

def 				_snake_case (		lowercase						)       ->       Dict:
				__a       :     Dict								=	len(lowercase						)
				__a							,	__a       :     Optional[Any]								=	[], []
				__a       :     str								=	[lst[0]]
				__a       :     List[Any]								=	[]
				__a       :     Tuple								=	1
				while i < length:
								if lst[i] < lst[i - 1]:
												runs.append(lowercase						)
												__a       :     Union[str, Any]								=	[lst[i]]
								else:
												new_run.append(lst[i]						)
								i += 1
				runs.append(lowercase						)

				for run in runs:
								sorted_runs.append(insertion_sort(lowercase						)						)
				for run in sorted_runs:
								__a       :     str								=	merge(lowercase			,    lowercase						)

				return sorted_array

def 				_snake_case (		)       ->       Dict:
				__a       :     Optional[Any]								=	[5, 9, 1_0, 3, -4, 5, 1_7_8, 9_2, 4_6, -1_8, 0, 7]
				__a       :     List[str]								=	tim_sort(lowercase						)
				print(lowercase						)


if __name__ == "__main__":
					main()

'''simple docstring'''







from typing import List

from tokenizers import NormalizedString, PreTokenizedString, normalizers
class  SCREAMING_SNAKE_CASE__       :
	def __init__(				self  ,    __UpperCamelCase			):



					'''simple docstring'''






					__a       :     Union[str, Any]								=	vocab
					__a       :     int								=	normalizers.BertNormalizer(
					    clean_text=__UpperCamelCase  ,    handle_chinese_chars=__UpperCamelCase  ,    strip_accents=__UpperCamelCase  ,    lowercase=__UpperCamelCase  ,    )
					try:
									import rjieba
					except ImportError:
									raise ImportError(
									    """You need to install rjieba to use RoFormerTokenizer. """
									    """See https://pypi.org/project/rjieba/ for installation."""			)
					__a       :     Optional[Any]								=	rjieba
	def __lowerCamelCase    (				self  ,    __UpperCamelCase  ,    __UpperCamelCase			):



					'''simple docstring'''






					__a       :     Union[str, 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(__UpperCamelCase			)  ,    hmm=__UpperCamelCase			):
									if token in self.vocab:
													splits.append(normalized_string[start:end]			)
									else:
													__a       :     str								=	self.normalizers.normalize_str(__UpperCamelCase			).split()
													for token in token_list:
																	if token:
																					__a       :     str								=	start + len(__UpperCamelCase			)
																					splits.append(normalized_string[start:end]			)
																					__a       :     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 __lowerCamelCase    (				self  ,    __UpperCamelCase			):



					'''simple docstring'''






					pretok.split(self.jieba_split			)