Fix loss loss logging for multi-gpu compatibility

run_classifier_pytorch.py

@@ -529,10 +529,10 @@ def main():
                 label_ids = label_ids.to(device)
 
                 loss, _ = model(input_ids, segment_ids, input_mask, label_ids)
-                total_tr_loss += loss.item()
+                total_tr_loss += loss.sum().item() # sum() is to account for multi-gpu support.
                 nb_tr_examples += input_ids.size(0)
                 model.zero_grad()
-                loss.backward()
+                loss.sum().backward() # sum() is to account for multi-gpu support.
                 optimizer.step()
                 global_step += 1
 
@@ -573,7 +573,7 @@ def main():
             label_ids = label_ids.to('cpu').numpy()
             tmp_eval_accuracy = accuracy(logits, label_ids)
 
-            eval_loss += tmp_eval_loss.item()
+            eval_loss += tmp_eval_loss.sum().item()
             eval_accuracy += tmp_eval_accuracy
             
             nb_eval_examples += input_ids.size(0)