





from __future__ import annotations




def 			lowerCAmelCase_			(				UpperCamelCase_       ,		UpperCamelCase_       ,		UpperCamelCase_       ,		)  ->		list[float | int]:
       if not all((nth_term, start_term_a, common_ratio_r)	):
              return []
       UpperCamelCase_ 							=	[]
       UpperCamelCase_ 							=	1
       UpperCamelCase_ 							=	common_ratio_r
       for _ in range(int(UpperCamelCase_	)	):
              if not series:
                     series.append(UpperCamelCase_	)
              else:
                     power += 1
                     series.append(float(start_term_a * multiple	)	)
                     UpperCamelCase_ 							=	pow(float(UpperCamelCase_	)       ,		UpperCamelCase_	)
       return series


if __name__ == "__main__":
     import doctest

     doctest.testmod()

     _UpperCAmelCase										=					float(input('Enter the last number (n term) of the Geometric Series'))
     _UpperCAmelCase										=					float(input('Enter the starting term (a) of the Geometric Series'))
     _UpperCAmelCase										=					float(
         input('Enter the common ratio between two terms (r) of the Geometric Series')
     )
     print('Formula of Geometric Series => a + ar + ar^2 ... +ar^n')
     print(geometric_series(nth_term, start_term_a, common_ratio_r))








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


_UpperCAmelCase										=					logging.get_logger(__name__)

_UpperCAmelCase										=					{
    '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       (						lowerCAmelCase_  ):
       _UpperCamelCase					:       Union[str, Any]       = '''qdqbert'''

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




              """simple docstring"""


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

              UpperCamelCase_ 							=	vocab_size
              UpperCamelCase_ 							=	max_position_embeddings
              UpperCamelCase_ 							=	hidden_size
              UpperCamelCase_ 							=	num_hidden_layers
              UpperCamelCase_ 							=	num_attention_heads
              UpperCamelCase_ 							=	intermediate_size
              UpperCamelCase_ 							=	hidden_act
              UpperCamelCase_ 							=	hidden_dropout_prob
              UpperCamelCase_ 							=	attention_probs_dropout_prob
              UpperCamelCase_ 							=	initializer_range
              UpperCamelCase_ 							=	type_vocab_size
              UpperCamelCase_ 							=	layer_norm_eps
              UpperCamelCase_ 							=	use_cache

