

def      snake_case_				(__A					:						int					)      ->     list:
   __lowerCAmelCase  :      Any    =						int(__A					)
   if n_element < 1:
      __lowerCAmelCase  :      Optional[int]    =						ValueError("""a should be a positive number"""					)
      raise my_error

   __lowerCAmelCase  :      Tuple    =						[1]
   __lowerCAmelCase   ,__lowerCAmelCase   ,__lowerCAmelCase  :      List[str]    =						(0, 0, 0)
   __lowerCAmelCase  :      List[Any]    =						1
   while index < n_element:
      while hamming_list[i] * 2 <= hamming_list[-1]:
         i += 1
      while hamming_list[j] * 3 <= hamming_list[-1]:
         j += 1
      while hamming_list[k] * 5 <= hamming_list[-1]:
         k += 1
      hamming_list.append(
          min(hamming_list[i] * 2 ,       hamming_list[j] * 3 ,       hamming_list[k] * 5					)					)
      index += 1
   return hamming_list


if __name__ == "__main__":
   __UpperCAmelCase								=			input("""Enter the last number (nth term) of the Hamming Number Series: """)
   print("""Formula of Hamming Number Series => 2^i * 3^j * 5^k""")
   __UpperCAmelCase								=			hamming(int(n))
   print("""-----------------------------------------------------""")
   print(F'The list with nth numbers is: {hamming_numbers}')
   print("""-----------------------------------------------------""")





import warnings

from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor


__UpperCAmelCase								=			logging.get_logger(__name__)



class SCREAMING_SNAKE_CASE     (  a_			):
  """simple docstring"""






  def __init__(      self			:   Optional[Any]	,							*lowerCAmelCase			:   int	,							**lowerCAmelCase			:   Optional[int]   )							->     None:






     """simple docstring"""







     warnings.warn(
         """The class GLPNFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
         """ use GLPNImageProcessor instead."""	,							lowerCAmelCase	,							)
     super().__init__(*lowerCAmelCase	,							**lowerCAmelCase   )


