Update modeling_super_linear.py

modeling_super_linear.py

@@ -457,9 +457,6 @@ class superLinear(nn.Module):
             V    = 1
             
         x = x.reshape(B * V, L)
-        print("RAZ")
-        print(x.shape)
-        
         expert_probs = None
         
         if get_prob:
@@ -468,6 +465,7 @@ class superLinear(nn.Module):
             out, self.moe_loss = self.moe(x)
 
         if self.auto_regressive and self.max_horizon < self.inf_pred_len:
+            print("bitch")
             outputs = [out]
             ar_x = torch.cat([x, out], dim=1)[:, -self.seq_len:]
             for i in range(0, self.inf_pred_len, self.max_horizon):
@@ -478,13 +476,10 @@ class superLinear(nn.Module):
             
         if len(x_enc.shape) > 2:
             out = out.reshape(B, V, out.shape[-1])
-            print(F"out2 :{out.shape}")
             result = out.permute(0, 2, 1)
         else:
-            print(F"out1 :{out.shape}")
             result =  out
 
-        
         if get_prob:
             expert_probs = expert_probs.reshape(B, V, expert_probs.shape[-1])
             return result, expert_probs