Update modeling_super_linear.py

modeling_super_linear.py

@@ -635,20 +635,15 @@ class SuperLinearForCausalLM(PreTrainedModel, GenerationMixin):
 
         
         if x_enc.shape[1] < 512:
-            #x_enc = self.revin_layer(x_enc, 'norm')
-            scale_factor = int(np.ceil(512/x_enc.shape[-1]))
+            '''scale_factor = int(np.ceil(512/x_enc.shape[-1]))
             x_enc = self.upsample_interpolate(x_enc,scale_factor,512)
-            pass
-
-        
-        # backbone returns (B, pred_len, C)
-        self.backbone.inf_pred_len = 96*scale_factor
-        
-        preds = self.backbone(x_enc)
-        preds = self.upsample_interpolate(preds,1/scale_factor,96)
-        #preds = self.fourier_downsample_dim1(preds,96)
-        #preds = self.revin_layer(preds, 'denorm')
-                
+            self.backbone.inf_pred_len = 96*scale_factor
+            preds = self.backbone(x_enc)
+            preds = self.upsample_interpolate(preds,1/scale_factor,96)'''
+            preds = self.backbone(x_enc)
+        else:
+            preds = self.backbone(x_enc)
+            
         return CausalLMOutputWithCrossAttentions(loss=None,logits=preds,past_key_values=None,hidden_states=None,attentions=None,)