




'''simple docstring'''




def 						snake_case__    ( lowerCamelCase__				:   list			)   ->   bool:
					if not isinstance(lowerCamelCase__			,		lowerCamelCase__			):
										raise ValueError('''Input series is not valid, valid series - [2, 4, 8]'''			)
					if len(lowerCamelCase__			) == 0:
										raise ValueError('''Input list must be a non empty list'''			)
					if len(lowerCamelCase__			) == 1:
										return True
					try:
										A_ :     List[Any] =							series[1] / series[0]
										for index in range(len(lowerCamelCase__			) - 1			):
															if series[index + 1] / series[index] != common_ratio:
																				return False
					except ZeroDivisionError:
										return False
					return True




def 						snake_case__    ( lowerCamelCase__				:   list			)   ->   float:
					if not isinstance(lowerCamelCase__			,		lowerCamelCase__			):
										raise ValueError('''Input series is not valid, valid series - [2, 4, 8]'''			)
					if len(lowerCamelCase__			) == 0:
										raise ValueError('''Input list must be a non empty list'''			)
					A_ :     List[Any] =							1
					for value in series:
										answer *= value
					return pow(lowerCamelCase__			,		1 / len(lowerCamelCase__			)			)


if __name__ == "__main__":
							import doctest

							doctest.testmod()









'''simple docstring'''




from ...configuration_utils import PretrainedConfig
from ...utils import logging


snake_case__          =						logging.get_logger(__name__)

snake_case__          =						{
    """bert-base-uncased""": """https://huggingface.co/bert-base-uncased/resolve/main/config.json""",
    # QDQBERT models can be loaded from any BERT checkpoint, available at https://huggingface.co/models?filter=bert
}






class     UpperCamelCase_     (a__     ):







						"""simple docstring"""


						_lowerCAmelCase    						=					'qdqbert'







						def __init__(     self      :       Union[str, Any]							, _lowerCamelCase      :       List[Any]=30522							, _lowerCamelCase      :       str=768							, _lowerCamelCase      :       Optional[Any]=12							, _lowerCamelCase      :       str=12							, _lowerCamelCase      :       List[Any]=3072							, _lowerCamelCase      :       Union[str, Any]="gelu"							, _lowerCamelCase      :       Dict=0.1							, _lowerCamelCase      :       Union[str, Any]=0.1							, _lowerCamelCase      :       Optional[int]=512							, _lowerCamelCase      :       Dict=2							, _lowerCamelCase      :       Optional[Any]=0.02							, _lowerCamelCase      :       List[Any]=1E-12							, _lowerCamelCase      :       Tuple=True							, _lowerCamelCase      :       Tuple=1							, _lowerCamelCase      :       Optional[Any]=0							, _lowerCamelCase      :       Optional[int]=2							, **_lowerCamelCase      :       List[str]							, ):





											"""simple docstring"""







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

											A_ :     Optional[Any] =							vocab_size
											A_ :     str =							max_position_embeddings
											A_ :     List[str] =							hidden_size
											A_ :     str =							num_hidden_layers
											A_ :     List[str] =							num_attention_heads
											A_ :     List[str] =							intermediate_size
											A_ :     int =							hidden_act
											A_ :     Tuple =							hidden_dropout_prob
											A_ :     Optional[Any] =							attention_probs_dropout_prob
											A_ :     Dict =							initializer_range
											A_ :     Optional[int] =							type_vocab_size
											A_ :     Any =							layer_norm_eps
											A_ :     Optional[int] =							use_cache



