from ...utils import is_torch_available, is_transformers_available


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







def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							return int((input_a, input_a).count(0				) != 0				)





def  __lowerCamelCase     (			):







							'''simple docstring'''






							assert nand_gate(0       ,							0				) == 1
							assert nand_gate(0       ,							1				) == 1
							assert nand_gate(1       ,							0				) == 1
							assert nand_gate(1       ,							1				) == 0


if __name__ == "__main__":
					print(nand_gate(0, 0))
					print(nand_gate(0, 1))
					print(nand_gate(1, 0))
					print(nand_gate(1, 1))




