Clean up copypaste in GPT.forward()

nanochat/gpt.py

@@ -260,19 +260,18 @@ class GPT(nn.Module):
         x = norm(x)
 
         # Forward the lm_head (compute logits)
+        logits = self.lm_head(x)
         softcap = 15
+        logits = softcap * torch.tanh(logits / softcap) # logits softcap
+
         if targets is not None:
             # training mode: compute and return the loss
             # TODO: experiment with Liger Kernels / chunked cross-entropy etc.
-            logits = self.lm_head(x)
-            logits = softcap * torch.tanh(logits / softcap) # logits softcap
             logits = logits.float() # use tf32/fp32 for logits
             loss = F.cross_entropy(logits.view(-1, logits.size(-1)), targets.view(-1), ignore_index=-1, reduction=loss_reduction)
             return loss
         else:
-            # inference mode: compute and return the logits
-            logits = self.lm_head(x)
-            logits = softcap * torch.tanh(logits / softcap) # logits softcap
+            # inference mode: only return the logits
             return logits
 
     @torch.inference_mode()