fixed checkpoint loader

solver.py

@@ -376,14 +376,14 @@ class Solver():
         self.start_epoch = checkpoint['epoch']
         self.start_iteration = checkpoint['start_iteration']
         # We are not loading the model_name as we might want to pre-train a model and then use it.
-        self.model.load_state_dict = checkpoint['state_dict']
-        self.optimizer.load_state_dict = checkpoint['optimizer']
+        self.model.load_state_dict(checkpoint['state_dict'])
+        self.optimizer.load_state_dict(checkpoint['optimizer'])
 
-        for state in self.optimizer.state.values():
+        for state in self.optimizer.state. ():
             for key, value in state.items():
                 if torch.is_tensor(value):
                     state[key] = value.to(self.device)
 
-        self.learning_rate_scheduler.load_state_dict = checkpoint['scheduler']
+        self.learning_rate_scheduler.load_state_dict(checkpoint['scheduler'])
         self.LogWriter.log(
             "Checkpoint Loaded {} - epoch {}".format(checkpoint_file_path, checkpoint['epoch']))