

from __future__ import annotations


def  __a    (				SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				) ->       Dict:






    '''simple docstring'''




    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()

   A_						:     Optional[Any]			  =				float(input('Enter the last number (n term) of the Geometric Series'))
   A_						:     str			  =				float(input('Enter the starting term (a) of the Geometric Series'))
   A_						:     str			  =				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))







import warnings

from ...utils import logging
from .image_processing_convnext import ConvNextImageProcessor


A_						:     int			  =				logging.get_logger(__name__)
class    A_				( _a  ):


    '''simple docstring'''






    def __init__(self       , *lowercase__       , **lowercase__					)       -> None:
        warnings.warn(
            '''The class ConvNextFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
            ''' Please use ConvNextImageProcessor instead.'''       , lowercase__       , )
        super().__init__(*lowercase__       , **lowercase__					)




