loss per epoch is not the mean, absolute change is printed

utils/data_logging_utils.py

@@ -109,7 +109,7 @@ class LogWriter():
         self.log_writer['train'].add_scalar(
             'loss/iteration', loss_per_iteration, iteration)
 
-    def loss_per_epoch(self, losses, phase, epoch):
+    def loss_per_epoch(self, losses, phase, epoch, previous_loss=None):
         """Log function
 
         This function records the loss for every epoch.
@@ -118,14 +118,21 @@ class LogWriter():
             losses (list): Values of all the losses recorded during the training epoch
             phase (str): Current run mode or phase
             epoch (int): Current epoch value
+            previous_loss(float): Value of the previous epoch's loss
         """
 
+        loss = np.mean(losses)
+
         if phase == 'train':
-            loss = losses[-1]
+            # loss = losses[-1]
+            print("Loss for Epoch {} of {} is: {}".format(epoch, phase, loss))
         else:
-            loss = np.mean(losses)
+            # loss = np.mean(losses)
+            if previous_loss == None:
+                print("Loss for Epoch {} of {} is: {}".format(epoch, phase, loss))
+            else:
+                print("Loss for Epoch {} of {} is {} and Absolute Change is {}".format(epoch, phase, loss, previous_loss - loss))
 
-        print("Loss for Epoch {} of {} is: {}".format(epoch, phase, loss))
         self.log_writer[phase].add_scalar('loss/epoch', loss, epoch)
 
     def close(self):