add history loss

pts/trainer.py

@@ -41,6 +41,9 @@ def __call__(
         train_iter: DataLoader,
         validation_iter: Optional[DataLoader] = None,
     ) -> None:
+
+        self.training_loss = []
+        self.validation_loss = []
         optimizer = Adam(
             net.parameters(), lr=self.learning_rate, weight_decay=self.weight_decay
         )
@@ -80,7 +83,6 @@ def __call__(
                         },
                         refresh=False,
                     )
-
                     loss.backward()
                     if self.clip_gradient is not None:
                         nn.utils.clip_grad_norm_(net.parameters(), self.clip_gradient)
@@ -92,6 +94,9 @@ def __call__(
                         break
                 it.close()
 
+            # Append the average loss for the epoch to the list of loss values
+            self.training_loss.append(avg_epoch_loss)
+
             # validation loop
             if validation_iter is not None:
                 cumm_epoch_loss_val = 0.0
@@ -121,6 +126,8 @@ def __call__(
                             break
 
                 it.close()
+                self.validation_loss.append(avg_epoch_loss_val)
 
             # mark epoch end time and log time cost of current epoch
             toc = time.time()
+