=True)
ddim.to("cuda")

# create a generator for reproducibility
generator = torch.Generator(device="cuda").manual_seed(0)

# run pipeline for just two steps and return numpy tensor
image = ddim(num_inference_steps=2, output_type="np", generator=generator).images
print(np.abs(image).sum()) The result is not the same even though you’re using an identical seed because the GPU uses a different random number generator than the CPU. To circumvent th