Update modeling_super_linear.py

modeling_super_linear.py

@@ -224,21 +224,27 @@ class RLinear(nn.Module):
 
             self.zero_shot_Linear = new_W                  # shape (self.horizon, new_lookback)
         else:
-            W   = self.Linear.weight.detach()
-            W   = W[:, -new_lookback:] 
-            W4d = W.unsqueeze(0).unsqueeze(0)            # (1, 1, out, in)
-
-            # resize   H → self.horizon   and   W → new_lookback
+            W = self.Linear.weight.detach()              # (out_features, seq_len)
+            
+            # 1️⃣ keep the last `new_lookback` columns
+            W_tail = W[:, -new_lookback:]                # (out_features, new_lookback)
+            
+            # 2️⃣ resize those columns back to `seq_len`
+            #     ─ use 4-D shape (N=1, C=1, H=out, W=new_lookback)
+            W4d = W_tail.unsqueeze(0).unsqueeze(0)        
+            
             new_W = F.interpolate(
                         W4d,
-                        size=( new_lookback,self.seq_len),   # (H_out, W_out)
+                        size=(out_features, self.seq_len),  # keep rows = out_features,
+                                                            #      stretch cols to seq_len
                         mode='bilinear',
                         align_corners=False
-                    )[0, 0]                                 # drop the two singleton dims
-
-            W_now = torch.cat((W, new_W), dim=1)  
-            self.zero_shot_Linear = new_W                  
+                    )[0, 0]                                # → (out_features, seq_len)
+            
+            # 3️⃣ concatenate on the column axis
+            W_now = torch.cat((W_tail, new_W), dim=1)      # (out_features, new_lookback + seq_len)
             
+            self.zero_shot_Linear = W_now