Fixed tests and trainer class.

resources/src/ai/trainer.py

@@ -29,7 +29,7 @@
 import configparser
 from datetime import datetime
 from src.ai.outliers import Autoencoder
-
+from tensorflow import keras
 sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
 
 class Trainer(Autoencoder):
@@ -67,7 +67,6 @@ def save_model(self, save_model_file, save_config_file):
         if os.path.exists(save_config_file):
             if not os.access(save_config_file, os.W_OK):
                 raise PermissionError(f"Permission denied: Cannot overwrite '{save_config_file}'")
-
         self.model.save(save_model_file)
         new_model_config = configparser.ConfigParser()
         new_model_config.add_section('Columns')
@@ -131,7 +130,7 @@ def train(self, raw_data, epochs=20, batch_size=32, backup_path=None):
         """
         if backup_path is None:
             backup_path = "./backups/"
-        date = datetime.now().strftime("%y-%m-%dT%H%M")
+        date = datetime.now().strftime("%y-%m-%dT%H:%M")
         self.save_model(f"{backup_path}{date}.keras",f"{backup_path}{date}.ini")
         data = self.input_json(raw_data)[0]
         prep_data = self.prepare_data_for_training(data)

resources/tests/test_trainer.py

@@ -20,46 +20,60 @@
 import unittest
 import os
 import sys
-import logging
 import json
 import numpy as np
+import configparser
 
 sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
 from src.ai.trainer import Trainer
 
 class TestTrainer(unittest.TestCase):
 
     def setUp(self):
-        self.test_backup_path = "./test_backups/"
+        self.test_backup_path = "./resources/tests/test_backups/"
         os.makedirs(self.test_backup_path, exist_ok=True)
-        self.trainer = Trainer("test_traffic.keras", "test_traffic.ini")
-        self.trainer.model_config_file = "dummy_config.ini"
-        self.trainer.model_file = "dummy.keras"
+        self.trainer = Trainer("./resources/tests/test_model.keras", "./resources/tests/test_model_config.ini")
+        self.trainer.model_config_file = "./resources/tests/dummy_config.ini"
+        self.trainer.model_file = "./resources/tests/dummy.keras"
 
     def tearDown(self):
-        os.rmdir(self.test_backup_path)
-        os.remove("dummy_config.ini")
-        os.remove("dummy.keras")
+        if os.path.exists(self.test_backup_path):
+            for filename in os.listdir(self.test_backup_path):
+                if os.path.isfile(os.path.join(self.test_backup_path, filename)):
+                    os.remove(os.path.join(self.test_backup_path, filename))
+            os.rmdir(self.test_backup_path)
+        if os.path.isfile(os.path.join(self.trainer.model_config_file)):
+            os.remove(self.trainer.model_config_file)
+        if os.path.isfile(self.trainer.model_file):
+            os.remove(self.trainer.model_file)
 
     def test_save_model(self):
-        save_model_file = os.path.join(self.test_backup_path, "test_model.keras")
-        save_config_file = os.path.join(self.test_backup_path, "test_config.ini")
-        self.trainer.model = "dummy_model"
+        dummy_model = os.path.join(self.test_backup_path, "dummy.keras")
+        dummy_config = os.path.join(self.test_backup_path, "dummy_config.ini")
         self.trainer.METRICS = ["metric1", "metric2"]
         self.trainer.AVG_LOSS = 0.5
         self.trainer.STD_LOSS = 0.2
-        self.trainer.save_model(save_model_file, save_config_file)
-        self.assertTrue(os.path.exists(save_model_file))
-        self.assertTrue(os.path.exists(save_config_file))
+        self.trainer.save_model(dummy_model, dummy_config)
+        self.assertTrue(os.path.exists(dummy_model))
+        self.assertTrue(os.path.exists(dummy_config))
+        model_config = configparser.ConfigParser()
+        model_config.read(dummy_config)
+        columns_section = model_config['Columns']
+        self.assertEqual(["metric1", "metric2"], columns_section.get('METRICS', '').split(', '))
+        general_section = model_config['General']
+        self.assertEqual('0.5', general_section.get('AVG_LOSS'))
+        self.assertEqual('0.2', general_section.get('STD_LOSS'))
 
     def test_prepare_data_for_training(self):
-        data = np.array([1, 2, 3, 4, 5])
+        data = np.zeros((100,100))
         prep_data = self.trainer.prepare_data_for_training(data)
+        self.assertEqual(prep_data.shape[1], self.trainer.NUM_WINDOWS*self.trainer.WINDOW_SIZE)
+        self.assertEqual(prep_data.shape[2], 100)
 
     def test_train(self):
-        with open("outliers_test_data.json", "r") as file:
+        with open("./resources/tests/outliers_test_data.json", "r") as file:
             raw_data = json.load(file)
         self.trainer.train(raw_data, epochs=10, batch_size=32, backup_path=self.test_backup_path)
 
 if __name__ == "__main__":
-    unittest.main()
+    unittest.main()