


"""simple docstring"""




def        lowercase							(		lowerCAmelCase__ :     list			) ->      bool:
		if not isinstance(lowerCAmelCase__    ,					lowerCAmelCase__			):
				raise ValueError('''Input series is not valid, valid series - [2, 4, 6]'''			)
		if len(lowerCAmelCase__			) == 0:
				raise ValueError('''Input list must be a non empty list'''			)
		if len(lowerCAmelCase__			) == 1:
				return True
		__a           =			series[1] - series[0]
		for index in range(len(lowerCAmelCase__			) - 1			):
				if series[index + 1] - series[index] != common_diff:
						return False
		return True

def        lowercase							(		lowerCAmelCase__ :     list			) ->      float:
		if not isinstance(lowerCAmelCase__    ,					lowerCAmelCase__			):
				raise ValueError('''Input series is not valid, valid series - [2, 4, 6]'''			)
		if len(lowerCAmelCase__			) == 0:
				raise ValueError('''Input list must be a non empty list'''			)
		__a           =			0
		for val in series:
				answer += val
		return answer / len(lowerCAmelCase__			)


if __name__ == "__main__":
				import doctest

				doctest.testmod()









from ... import PretrainedConfig


_lowerCAmelCase					:			Any  				=			{
    "sijunhe/nezha-cn-base": "https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json",
}






class 	__magic_name__    (			lowerCAmelCase_      ):
			SCREAMING_SNAKE_CASE							   =						NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
			SCREAMING_SNAKE_CASE							   =						'nezha'





			def __init__(		self					,  __snake_case=2_1128					,  __snake_case=768					,  __snake_case=12					,  __snake_case=12					,  __snake_case=3072					,  __snake_case="gelu"					,  __snake_case=0.1					,  __snake_case=0.1					,  __snake_case=512					,  __snake_case=64					,  __snake_case=2					,  __snake_case=0.02					,  __snake_case=1e-12					,  __snake_case=0.1					,  __snake_case=0					,  __snake_case=2					,  __snake_case=3					,  __snake_case=True					,  **__snake_case					,  )   -> str:




						'''simple docstring'''
						super().__init__(pad_token_id=__snake_case					,  bos_token_id=__snake_case					,  eos_token_id=__snake_case					,  **__snake_case					)

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






