
'''simple docstring'''







from typing import List

from tokenizers import NormalizedString, PreTokenizedString, normalizers






class 				lowerCAmelCase__     :






					def __init__(     self       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





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






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											lowercase_			:  str									= []

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


											"""simple docstring"""





											pretok.split(self.jieba_split	)





'''simple docstring'''







from itertools import combinations, product
def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				int   ,   __SCREAMING_SNAKE_CASE      :				int   ,   __SCREAMING_SNAKE_CASE      :				int   ,   __SCREAMING_SNAKE_CASE      :				int							):



						"""simple docstring"""





						if xa == ya == 0 or xa == ya == 0:
												return False
						lowercase_			:  Optional[Any]									= xa * xa + ya * ya
						lowercase_			:  List[str]									= xa * xa + ya * ya
						lowercase_			:  Any									= (xa - xa) * (xa - xa) + (ya - ya) * (ya - ya)
						return (
						    a_square + b_square == c_square
						    or a_square + c_square == b_square
						    or b_square + c_square == a_square
						)
def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				int = 50							):



						"""simple docstring"""





						return sum(
						    1
						    for pta, pta in combinations(product(range(limit + 1							)   ,   repeat=2							)   ,   2							)
						    if is_right(*__SCREAMING_SNAKE_CASE   ,   *__SCREAMING_SNAKE_CASE							)							)


if __name__ == "__main__":
							print(f"""{solution() = }""")



