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app.py

@@ -16,8 +16,6 @@ else: device = 'cpu'
 print('DEVICE:', device)
 if device == 'cuda': print('CUDA DEVICE:', torch.cuda.get_device_name())
 
-torch.backends.cuda.matmul.allow_tf32 = False
-
 model = VGG_19().to(device).eval()
 for param in model.parameters():
     param.requires_grad = False

inference.py

@@ -42,6 +42,7 @@ def inference(
         generated_features = model(generated_image)
         total_loss = _compute_loss(generated_features, content_features, style_features, alpha, beta)
         total_loss.backward()
+        torch.nn.utils.clip_grad_norm_([generated_image], max_norm=1.0) # clip gradients
         return total_loss
     
     for _ in tqdm(range(iterations), desc='The magic is happening ✨'):