

def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  Dict )   ->       list:
				_UpperCAmelCase       :		List[Any] 		=    int(lowerCAmelCase )
				if n_element < 1:
								_UpperCAmelCase       :		Any 		=    ValueError("a should be a positive number" )
								raise my_error

				_UpperCAmelCase       :		Any 		=    [1]
				_UpperCAmelCase       :		Optional[int] 		=    (0, 0, 0)
				_UpperCAmelCase       :		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__":
					SCREAMING_SNAKE_CASE_				    =      input('Enter the last number (nth term) of the Hamming Number Series: ')
					print('Formula of Hamming Number Series => 2^i * 3^j * 5^k')
					SCREAMING_SNAKE_CASE_				    =      hamming(int(n))
					print('-----------------------------------------------------')
					print(F'''The list with nth numbers is: {hamming_numbers}''')
					print('-----------------------------------------------------')





import warnings

from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor


SCREAMING_SNAKE_CASE_        =      logging.get_logger(__name__)

class 				a  (	UpperCAmelCase				):


						def __init__(       self						,					*A_						,					**A_	):







										'''simple docstring'''


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


