t, num_inference_steps=30).images[0] torch.compile offers different backends and modes. As we’re aiming for maximum inference speed, we opt for the inductor backend using the “max-autotune”. “max-autotune” uses CUDA graphs and optimizes the compilation graph specifically for latency. Specifying fullgraph to be True ensures that there are no graph breaks in the underlying model, ensuring the fullest potential of torch.compile. Using SDPA attenti