Fix backpropagation steps order in basics/quickstart_tutorial.py

beginner_source/basics/quickstart_tutorial.py

@@ -140,15 +140,16 @@ def train(dataloader, model, loss_fn, optimizer):
     model.train()
     for batch, (X, y) in enumerate(dataloader):
         X, y = X.to(device), y.to(device)
-
+
+        # Zero the gradients for batch
+        optimizer.zero_grad()
         # Compute prediction error
         pred = model(X)
         loss = loss_fn(pred, y)
-
         # Backpropagation
         loss.backward()
+        # Optimizer step
         optimizer.step()
-        optimizer.zero_grad()
 
         if batch % 100 == 0:
             loss, current = loss.item(), (batch + 1) * len(X)