diff --git a/Untitled.ipynb b/Untitled.ipynb
index 1c17091..a0093d1 100644
--- a/Untitled.ipynb
+++ b/Untitled.ipynb
@@ -3,7 +3,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "820b3659",
+   "id": "2b480856",
    "metadata": {},
    "outputs": [
     {
@@ -40,7 +40,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "778a8669",
+   "id": "ba1925fa",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -49,38 +49,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "id": "2873f942",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import time\n",
-    "def run_time(func):\n",
-    "    def inner(model, image, question):\n",
-    "        back = func(model, image, question)\n",
-    "        print(\"Runned time: {} s\".format(round((time.time() - t)/10, 3)))\n",
-    "        return back\n",
-    "    t = time.time()\n",
-    "    return inner"
-   ]
-  },
-  {
-   "cell_type": "code",
    "execution_count": 8,
-   "id": "40f61f2c",
+   "id": "20c88989",
    "metadata": {},
    "outputs": [],
    "source": [
     "def load_demo_image(in_PATH):\n",
     "    img = np.array(Image.open(in_PATH).convert('RGB'))[np.newaxis] / 255.0\n",
-    "    img_p = util.preprocess_images_outpainting(img)\n",
+    "    img_p = src.util.preprocess_images_outpainting(img)\n",
     "    return img_p"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "d4861188",
+   "id": "5d117d25",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -94,14 +77,13 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "92005cf0",
+   "id": "de6b79ae",
    "metadata": {},
    "outputs": [],
    "source": [
-    "@run_time\n",
     "def inference(model_PATH, img_p):\n",
     "    G_Z = tf.placeholder(tf.float32, shape=[None, IMAGE_SZ, IMAGE_SZ, 4], name='G_Z')\n",
-    "    G_sample = model.generator(G_Z)\n",
+    "    G_sample = src.model.generator(G_Z)\n",
     "    \n",
     "    saver = tf.train.Saver()\n",
     "    with tf.Session() as sess:\n",
@@ -116,7 +98,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "5863f30d",
+   "id": "35c27191",
    "metadata": {},
    "outputs": [],
    "source": [
diff --git a/handler.py b/handler.py
index 229249c..3548bf8 100644
--- a/handler.py
+++ b/handler.py
@@ -10,18 +10,9 @@
 
 model_PATH='/home/jovyan/work/src/output/models/model2000.ckpt'
 
-import time
-def run_time(func):
-    def inner(model, image, question):
-        back = func(model, image, question)
-        print("Runned time: {} s".format(round((time.time() - t)/10, 3)))
-        return back
-    t = time.time()
-    return inner
-
 def load_demo_image(in_PATH):
     img = np.array(Image.open(in_PATH).convert('RGB'))[np.newaxis] / 255.0
-    img_p = util.preprocess_images_outpainting(img)
+    img_p = src.util.preprocess_images_outpainting(img)
     return img_p
 
 def image_to_path(img):
@@ -30,10 +21,9 @@
     resize_img.save(path)
     return path
 
-@run_time
 def inference(model_PATH, img_p):
     G_Z = tf.placeholder(tf.float32, shape=[None, IMAGE_SZ, IMAGE_SZ, 4], name='G_Z')
-    G_sample = model.generator(G_Z)
+    G_sample = src.model.generator(G_Z)
     
     saver = tf.train.Saver()
     with tf.Session() as sess: