put model checkpoint/reload weights into separate function

toolkit.py

@@ -842,6 +842,11 @@ class ClassificationProject(object):
             except KeyboardInterrupt:
                 logger.info("Interrupt training - continue with rest")
 
+        self.checkpoint_model(epochs)
+
+
+    def checkpoint_model(self, epochs):
+
         logger.info("Save history")
         self._dump_history()
 
@@ -1455,6 +1460,8 @@ class ClassificationProjectRNN(ClassificationProject):
         for branch_index, branch in enumerate(self.fields):
             self.plot_input(branch_index)
 
+        self.total_epochs = self._read_info("epochs", 0)
+
         try:
             self.shuffle_training_data() # needed here too, in order to get correct validation data
             self.is_training = True
@@ -1468,8 +1475,8 @@ class ClassificationProjectRNN(ClassificationProject):
             self.is_training = False
         except KeyboardInterrupt:
             logger.info("Interrupt training - continue with rest")
-        logger.info("Save history")
-        self._dump_history()
+
+        self.checkpoint_model(epochs)
 
 
     def get_input_list(self, x):