another approach for final decoder

main.py

@@ -72,8 +72,8 @@ for epoch in range(100):
             ):
                 batch = test_dataset[i : i + batch_size]
                 images = rf.sample(batch["x0"].to(device))
-                image = denormalize(images[-1]).clamp(0, 1) * 255
-                original = denormalize(batch["x1"]).clamp(0, 1) * 255
+                image = denormalize(images[-1]).clamp(0, 1)
+                original = denormalize(batch["x1"]).clamp(0, 1)
 
                 psnr, ssim, lpips = benchmark(image.cpu(), original.cpu())
                 psnr_sum += psnr.sum().item()
@@ -92,7 +92,6 @@ for epoch in range(100):
                 "epoch": epoch + 1,
             }
         )
-
         rf.model.train()
 
         torch.save(