






'''simple docstring'''







def 				SCREAMING_SNAKE_CASE_ (UpperCamelCase   )   -> list:
							lowerCamelCase__      :			str 						= int(UpperCamelCase   )
							if n_element < 1:
														lowerCamelCase__      :			int 						= ValueError("""a should be a positive number"""   )
														raise my_error

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







'''simple docstring'''







from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
			from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline

