--- a
+++ b/trained_model_loader.py
@@ -0,0 +1,43 @@
+import os
+import tensorflow as tf
+
+from utils import store_to_csv
+import config
+
+from model_utils import x, evaluate_test_set, evaluate_solution
+from model_factory import ModelFactory
+
+
+# Construct model
+factory = ModelFactory()
+model = factory.get_network_model()
+
+softmax_prediction = tf.nn.softmax(model.conv_net(x, 1.0), 
+    name='softmax_prediction')
+
+data_loader = factory.get_data_loader()
+test_set = data_loader.get_exact_tests_set()
+out_dir = data_loader.results_out_dir()
+print(out_dir)
+
+
+saver = tf.train.Saver()
+
+with tf.Session() as sess:
+    sess.run(tf.global_variables_initializer())
+    if os.path.exists(os.path.join(out_dir, config.RESTORE_MODEL_CKPT + '.index')):
+        saver.restore(sess, os.path.join(out_dir, config.RESTORE_MODEL_CKPT))
+
+        evaluate_test_set(sess, 
+                          test_set,
+                          softmax_prediction,
+                          x)
+        if os.path.exists(config.SOLUTION_FILE_PATH):
+            print("Evaluate generated solution...")
+            evaluate_solution(config.SOLUTION_FILE_PATH)
+        else:
+          print("Solution file was not generated, check if test data is complete...")
+    else:
+        print("Checkpoint file {} does not exist in the configured directory {}.".format(
+            config.RESTORE_MODEL_CKPT, out_dir))
+