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predict.py

@@ -1,4 +1,4 @@
-"""Optimized blend: Pong AR weight 0.85->0.65, Sonic unchanged 0.7->0.3."""
+"""Blend sweep: Pong AR weight 0.9->0.7, Sonic unchanged 0.7->0.3."""
 import sys
 import os
 import numpy as np
@@ -167,7 +167,7 @@ def predict_next_frame(ens, context_frames: np.ndarray) -> np.ndarray:
 
             predicted = torch.zeros_like(direct_pred)
             for step in range(PRED_FRAMES):
-                ar_weight = 0.85 - (step / (PRED_FRAMES - 1)) * 0.2
+                ar_weight = 0.9 - (step / (PRED_FRAMES - 1)) * 0.2
                 direct_weight = 1.0 - ar_weight
                 predicted[:, step] = ar_weight * ar_pred[:, step] + direct_weight * direct_pred[:, step]