

from __future__ import annotations

def 			__snake_case	(   __UpperCamelCase  :   Tuple							,__UpperCamelCase  :   Dict							,__UpperCamelCase  :   Optional[Any]							,):



      """simple docstring"""

      if not all((nth_term, start_term_a, common_ratio_r)						):
            return []
      A_	     =							[]
      A_	     =							1
      A_	     =							common_ratio_r
      for _ in range(int(__UpperCamelCase						)						):
            if not series:
                  series.append(__UpperCamelCase						)
            else:
                  power += 1
                  series.append(float(start_term_a * multiple						)						)
                  A_	     =							pow(float(__UpperCamelCase						)							,__UpperCamelCase						)
      return series


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      __a						:str            = float(input('Enter the last number (n term) of the Geometric Series'))
      __a						:Dict            = float(input('Enter the starting term (a) of the Geometric Series'))
      __a						:int            = 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_mobilenet_va import MobileNetVaImageProcessor


__a						:Optional[int]            = logging.get_logger(__name__)

class      _a				( snake_case_							):




      """simple docstring"""

      def __init__(      self       :							List[Any]	, *UpperCAmelCase       :							Any	, **UpperCAmelCase       :							int  ):
            warnings.warn(
                "The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."
                " Please use MobileNetV2ImageProcessor instead."	, UpperCAmelCase	, )
            super().__init__(*UpperCAmelCase	, **UpperCAmelCase  )