added logs for loss per iteration and epoch

utils/data_logging_utils.py

@@ -16,6 +16,7 @@ import os
 import matplotlib.pyplot as plt
 import shutil
 import logging
+import numpy as np
 
 # The SummaryWriter class provides a high-level API to create an event file in a given directory and add summaries and events to it.
 # More here: https://tensorboardx.readthedocs.io/en/latest/tensorboard.html
@@ -90,15 +91,68 @@ class LogWriter():
 
         self.logger.info(msg= message)
 
-    def loss_per_iteration(self):
-        pass
+    def loss_per_iteration(self, loss_per_iteration, batch_index, current_iteration):
+        """Log of loss / iteration
 
-    def loss_per_epoch(self):
-        pass
+        This function records the loss for every iteration.
+
+        Args:
+            loss_per_iteration (torch.tensor): Value of loss for every iteration step
+            batch_index (int): Index of current batch
+            current_iteartion (int): Current iteration value
+
+        Returns:
+            None
+
+        Raises:
+            None
+        """
+
+        print("Loss for Iteration {} is: {}".format(batch_index, loss_per_iteration))
+        self.log_writer['train'].add_scalar(tag= 'loss / iteration', loss_per_iteration, current_iteration)
+
+    def loss_per_epoch(self, losses, phase, epoch):
+        """Log function
+
+        This function records the loss for every epoch.
+
+        Args:
+            losses (list): Values of all the losses recorded during the training epoch
+            phase (str): Current run mode or phase
+            epoch (int): Current epoch value
+
+        Returns:
+            None
+
+        Raises:
+            None
+        """
+
+        if phase == 'train':
+            loss = losses[-1]
+        else:
+            loss = np.mean(losses)
+
+        print("Loss for Epoch {} of {} is: {}".format(epoch, phase, loss))
+        self.log_writer[phase].add_scalar(tag= 'loss / iteration', loss, epoch)
 
     def confusion_matrix_per_epoch(self):
-        pass
+        """Log function
+
+        This function logs a message in the logger.
 
+        Args:
+            message (str): Message to be logged
+
+        Returns:
+            None
+
+        Raises:
+            None
+        """
+
+
+        
     def plot_confusion_matrix(self):
         pass