 steps and return numpy tensor
image = ddim(num_inference_steps=2, output_type="np", generator=generator).images
print(np.abs(image).sum()) Now when you run the code above, it always prints a value of 1491.1711 no matter what because the Generator object with the seed is passed to all the random functions of the pipeline. If you run this code example on your specific hardware and PyTorch version, you should get a similar, if not the same, resul