diff --git a/pytorch_lightning/core/hooks.py b/pytorch_lightning/core/hooks.py
index dc5a502c5f89a..c89b82e00a101 100644
--- a/pytorch_lightning/core/hooks.py
+++ b/pytorch_lightning/core/hooks.py
@@ -124,12 +124,13 @@ def on_after_backward(self):
         """
         pass
 
-    def backward(self, use_amp, loss, optimizer):
+    def backward(self, use_amp, loss, optimizer, optimizer_idx):
         """Override backward with your own implementation if you need to
 
         :param use_amp: Whether amp was requested or not
         :param loss: Loss is already scaled by accumulated grads
         :param optimizer: Current optimizer being used
+        :param optimizer_idx: Index of the current optimizer being used
         :return:
 
         Called to perform backward step.
diff --git a/pytorch_lightning/trainer/training_loop.py b/pytorch_lightning/trainer/training_loop.py
index d5f16c9462bf1..9f07fb523b4e6 100644
--- a/pytorch_lightning/trainer/training_loop.py
+++ b/pytorch_lightning/trainer/training_loop.py
@@ -486,13 +486,14 @@ def optimizer_closure():
 
                     # backward pass
                     model_ref = self.get_model()
-                    model_ref.backward(self.use_amp, closure_loss, optimizer)
+                    model_ref.backward(self.use_amp, closure_loss, optimizer, opt_idx)
 
                     # track metrics for callbacks
                     all_callback_metrics.append(callback_metrics)
 
                     # track progress bar metrics
                     self.add_tqdm_metrics(progress_bar_metrics)
+                    self.add_tqdm_metrics(progress_bar_metrics)
                     all_log_metrics.append(log_metrics)
 
                     # insert after step hook