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predict.py

@@ -164,11 +164,9 @@ def predict_next_frame(ens, context_frames: np.ndarray) -> np.ndarray:
 
             ar_pred = torch.stack(ar_preds, dim=1)
 
-            # Custom per-step AR weights (nonlinear schedule)
-            pong_ar_weights = [0.90, 0.90, 0.90, 0.90, 0.70, 0.70, 0.45, 0.45]
             predicted = torch.zeros_like(direct_pred)
             for step in range(PRED_FRAMES):
-                ar_weight = pong_ar_weights[step]
+                ar_weight = 0.80
                 direct_weight = 1.0 - ar_weight
                 predicted[:, step] = ar_weight * ar_pred[:, step] + direct_weight * direct_pred[:, step]