Removes the tf.train.Saver().save(), causes to save the wrong checkpoint

Author: AFAgarap

models/gru_softmax/gru_softmax.py

@@ -271,8 +271,6 @@ def train(self, checkpoint_path, log_path, model_name, epochs, train_data, train
 
                 print('EOF -- Testing done at step {}'.format(step))
 
-            saver.save(sess=sess, save_path=os.path.join(checkpoint_path, model_name), global_step=step)
-
     @staticmethod
     def predict(batch_size, cell_size, dropout_rate, num_classes, test_data, test_size, checkpoint_path, result_path):
         """Classifies the data whether there is an intrusion or none

models/gru_svm/gru_svm.py

@@ -276,8 +276,6 @@ def train(self, checkpoint_path, log_path, model_name, epochs, train_data, train
 
                 print('EOF -- Testing done at step {}'.format(step))
 
-            saver.save(sess=sess, save_path=os.path.join(checkpoint_path, model_name), global_step=step)
-
     @staticmethod
     def predict(batch_size, cell_size, dropout_rate, num_classes, test_data, test_size, checkpoint_path, result_path):
         """Classifies the data whether there is an intrusion or none

models/svm/svm.py

@@ -242,8 +242,6 @@ def train(self, checkpoint_path, log_path, model_name, epochs, result_path, trai
 
                 print('EOF -- Testing done at step {}'.format(step))
 
-            saver.save(sess, checkpoint_path + model_name, global_step=step)
-
     @staticmethod
     def predict(batch_size, num_classes, test_data, test_size, checkpoint_path, result_path):
         """Classifies the data whether there is an intrusion or none