Add trained model and print information in eval (Model)

SmartRecruiting_BackEnd/data/models.py

@@ -113,7 +113,7 @@ class Contact(Base):
     role = Column(String(100), unique=False, nullable=True)
     id_field = Column(Integer, ForeignKey('field.id'), unique=False, nullable=False)
 
-    def init__(self, name, surname, email, phone, role, id_field):
+    def __init__(self, name, surname, email, phone, role, id_field):
         self.name = name
         self.surname = surname
         self.email = email

SmartRecruiting_BackEnd/deeplearning/cnn/Model.py

@@ -123,6 +123,7 @@ class Model(object):
         if self.model is None:
             raise ModelInitialisationError("Model not build. Consider using build (and train) or load methods before.")
 
+        print("Eval on " + str(len(features)) + " offers")
         features = self._text_to_word_indexes(features)
         features = tf.keras.preprocessing.sequence.pad_sequences(features, maxlen=400, padding="post")
         loss, acc = self.model.evaluate(features, labels)

SmartRecruiting_BackEnd/deeplearning/cnn/train.py

@@ -34,7 +34,7 @@ def train(db_manager):
     """
     Train a convolutional neuronal network and save it in a file in /runs
 
-    @:param: the database manager
+    :param: the database manager
     :type db_manager: DbManager
     """
     x, y = get_offers(db_manager)