Implemented shuffle parameter in preprocessing; shuffled validation data in model_training.py

source/model_utils.py

@@ -171,6 +171,7 @@ class Latent_space_control(Layer):
         # Adds Silhouette score controling overlap between clusters
         hard_labels = tf.math.argmax(z_cat, axis=1)
         silhouette = tf.numpy_function(silhouette_score, [z, hard_labels], tf.float32)
+        self.add_loss(- K.mean(silhouette), inputs=[z, hard_labels])
         self.add_metric(silhouette, aggregation="mean", name="silhouette")
 
         return z