Improving the HGT example. (#6069)

examples/pytorch/hgt/train_acm.py

@@ -49,7 +49,6 @@ def get_n_params(model):
 def train(model, G):
     best_val_acc = torch.tensor(0)
     best_test_acc = torch.tensor(0)
-    train_step = torch.tensor(0)
     for epoch in np.arange(args.n_epoch) + 1:
         model.train()
         logits = model(G, "paper")
@@ -59,8 +58,7 @@ def train(model, G):
         loss.backward()
         torch.nn.utils.clip_grad_norm_(model.parameters(), args.clip)
         optimizer.step()
-        train_step += 1
-        scheduler.step(train_step)
+        scheduler.step()
         if epoch % 5 == 0:
             model.eval()
             logits = model(G, "paper")