Update modeling_super_linear.py

modeling_super_linear.py

@@ -451,38 +451,38 @@ class superLinear(nn.Module):
         #         print(f"Path {path} does not exist. Skipping loading weights.")
 
 
-    def map_to_cycle(self, freq):
-        if "/" in freq:
-            cycle = int(freq.split("/")[1])
-        elif "h" in freq:
-            cycle = 24
-        elif "2h":
-            cycle = 12
-        elif "3h" in freq:
-            cycle = 8
-        elif "4h" in freq:
-            cycle = 6
-        elif "D" in freq:
-            cycle = 7
-        elif "DM" in freq:
-            cycle = 30
-        elif "W" in freq:
-            cycle = 52
-        elif "M" in freq:
-            cycle = 12
-        elif "min" in freq:
-            cycle = 1440
-        elif "5min" in freq:
-            cycle = 288
-        elif "10min" in freq:
-            cycle = 144
-        elif "15min" in freq:
-            cycle = 96
-        elif "30min" in freq:
-            cycle = 48
-        else:
-            cycle = int(freq)
-        return cycle
+    # def map_to_cycle(self, freq):
+    #     if "/" in freq:
+    #         cycle = int(freq.split("/")[1])
+    #     elif "h" in freq:
+    #         cycle = 24
+    #     elif "2h":
+    #         cycle = 12
+    #     elif "3h" in freq:
+    #         cycle = 8
+    #     elif "4h" in freq:
+    #         cycle = 6
+    #     elif "D" in freq:
+    #         cycle = 7
+    #     elif "DM" in freq:
+    #         cycle = 30
+    #     elif "W" in freq:
+    #         cycle = 52
+    #     elif "M" in freq:
+    #         cycle = 12
+    #     elif "min" in freq:
+    #         cycle = 1440
+    #     elif "5min" in freq:
+    #         cycle = 288
+    #     elif "10min" in freq:
+    #         cycle = 144
+    #     elif "15min" in freq:
+    #         cycle = 96
+    #     elif "30min" in freq:
+    #         cycle = 48
+    #     else:
+    #         cycle = int(freq)
+    #     return cycle
 
 
     def forward(self, x_enc, x_mark_enc=None, x_dec=None, x_mark_dec=None, mask=None, freq=[None], get_prob=False, inf_pred_len=None):