


from ... import PretrainedConfig


lowerCAmelCase	=							{
    'sijunhe/nezha-cn-base': 'https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json',
}


class 	_a							(      UpperCamelCase__      ):






							"""simple docstring"""




							_lowercase     :      List[str]  				=			NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
							_lowercase     :      Union[str, Any]  				=			'''nezha'''

							def __init__(							self:     Optional[int]   ,						UpperCamelCase_:     Tuple=21_128   ,						UpperCamelCase_:     Optional[Any]=768   ,						UpperCamelCase_:     Optional[Any]=12   ,						UpperCamelCase_:     List[Any]=12   ,						UpperCamelCase_:     List[str]=3_072   ,						UpperCamelCase_:     List[Any]="gelu"   ,						UpperCamelCase_:     int=0.1   ,						UpperCamelCase_:     List[Any]=0.1   ,						UpperCamelCase_:     int=512   ,						UpperCamelCase_:     Any=64   ,						UpperCamelCase_:     Optional[int]=2   ,						UpperCamelCase_:     str=0.02   ,						UpperCamelCase_:     Any=1E-1_2   ,						UpperCamelCase_:     str=0.1   ,						UpperCamelCase_:     Optional[Any]=0   ,						UpperCamelCase_:     Dict=2   ,						UpperCamelCase_:     List[Any]=3   ,						UpperCamelCase_:     Any=True   ,						**UpperCamelCase_:     Union[str, Any]   ,						)      ->       List[str]:





									"""simple docstring"""







									super().__init__(pad_token_id=__lowerCamelCase   ,						bos_token_id=__lowerCamelCase   ,						eos_token_id=__lowerCamelCase   ,						**__lowerCamelCase							)

									lowercase__						=				vocab_size
									lowercase__						=				hidden_size
									lowercase__						=				num_hidden_layers
									lowercase__						=				num_attention_heads
									lowercase__						=				hidden_act
									lowercase__						=				intermediate_size
									lowercase__						=				hidden_dropout_prob
									lowercase__						=				attention_probs_dropout_prob
									lowercase__						=				max_position_embeddings
									lowercase__						=				max_relative_position
									lowercase__						=				type_vocab_size
									lowercase__						=				initializer_range
									lowercase__						=				layer_norm_eps
									lowercase__						=				classifier_dropout
									lowercase__						=				use_cache






def       _a			(				SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE					):


		"""simple docstring"""




		lowercase__						=				len(SCREAMING_SNAKE_CASE					)
		lowercase__						=				[]
		for i in range(len(SCREAMING_SNAKE_CASE					) - pat_len + 1					):
				lowercase__						=				True
				for j in range(SCREAMING_SNAKE_CASE					):
						if s[i + j] != pattern[j]:
								lowercase__						=				False
								break
				if match_found:
						position.append(SCREAMING_SNAKE_CASE					)
		return position


if __name__ == "__main__":
			assert naive_pattern_search('ABCDEFG', 'DE') == [3]
			print(naive_pattern_search('ABAAABCDBBABCDDEBCABC', 'ABC'))


