Logs

app.py

@@ -134,6 +134,7 @@ def evaluate_model(model, dataloader, device):
 
             # Get predictions
             preds = torch.argmax(logits, dim=-1).cpu().numpy()
+            
             all_preds.extend(preds)
             all_labels.extend(labels.cpu().numpy())
 
@@ -141,7 +142,10 @@ def evaluate_model(model, dataloader, device):
     print("evaluate_model sizes")
     print(len(all_preds[0]))
     print(len(all_labels[0]))
-    print(all_preds)
+    for p in all_preds:
+        if len(p) != len(all_preds[0]):
+            print(len(p))
+            print(p)
     all_preds = np.asarray(all_preds, dtype=np.float32)
     all_labels = np.asarray(all_labels, dtype=np.float32)
     print("Flattened sizes")