


'''simple docstring'''



def   lowerCamelCase							(_SCREAMING_SNAKE_CASE				:       Optional[Any]       ):

					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      :	Any    =  series[1] - series[0]
					for index in range(len(__lowerCAmelCase       ) - 1       ):
										if series[index + 1] - series[index] != common_diff:
															return False
					return True






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE				:       Dict       ):

					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      :	Any    =  0
					for val in series:
										answer += val
					return answer / len(__lowerCAmelCase       )


if __name__ == "__main__":
			import doctest

			doctest.testmod()







'''simple docstring'''



from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


__lowercase     :						List[Any]	=     {
    'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
    'susnato/ernie-m-large_pytorch': 'https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json',
}





class 							__UpperCamelCase    (		lowerCAmelCase_ ):
	A_           =   "ernie_m"
	A_           =   {"dropout": "classifier_dropout", "num_classes": "num_labels"}




	def __init__(       self						,    __a = 25_0002						,    __a = 768						,    __a = 12						,    __a = 12						,    __a = 3072						,    __a = "gelu"						,    __a = 0.1						,    __a = 0.1						,    __a = 514						,    __a = 0.02						,    __a = 1						,    __a = 1E-0_5						,    __a=None						,    __a=False						,    __a=0.0						,    **__a						,    ):

						'''simple docstring'''





						super().__init__(pad_token_id=__a						,    **__a							)
						__a      :	int    =  vocab_size
						__a      :	Dict    =  hidden_size
						__a      :	str    =  num_hidden_layers
						__a      :	Dict    =  num_attention_heads
						__a      :	List[str]    =  intermediate_size
						__a      :	Union[str, Any]    =  hidden_act
						__a      :	List[Any]    =  hidden_dropout_prob
						__a      :	str    =  attention_probs_dropout_prob
						__a      :	Any    =  max_position_embeddings
						__a      :	int    =  initializer_range
						__a      :	Dict    =  layer_norm_eps
						__a      :	int    =  classifier_dropout
						__a      :	Dict    =  is_decoder
						__a      :	int    =  act_dropout



