orch.no_grad():
    image = vae.decode(latents).sample Lastly, convert the image to a PIL.Image to see your generated image!   Copied >>> image = (image / 2 + 0.5).clamp(0, 1).squeeze()
>>> image = (image.permute(1, 2, 0) * 255).to(torch.uint8).cpu().numpy()
>>> images = (image * 255).round().astype("uint8")
>>> image = Image.fromarray(image)
>>> image   Next steps From basic to complex pipelines, you’ve seen that all you really need to write y