in-built preprocessing layer

trash_classification_using_ResNet.ipynb

@@ -673,12 +673,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "preprocess_layer = tf.keras.layers.Lambda(preprocess_input)\n",
-    "\n",
     "def build_model():\n",
     "    pretrained_model = ResNet50(\n",
     "    input_shape=(224, 224, 3),\n",
@@ -690,8 +688,9 @@
     "    pretrained_model.trainable = False  # Phase 1: freeze backbone\n",
     "\n",
     "    inputs = Input(shape=(*IMAGE_SIZE, 3))\n",
-    "    x = tf.keras.layers.Resizing(*IMAGE_SIZE)(inputs)\n",
-    "    x = preprocess_layer(x)  # standardized input pipeline\n",
+    "    x = Resizing(*IMAGE_SIZE)(inputs)\n",
+    "    x = Rescaling(1./255)(x)  # Rescale to [-1, 1]\n",
+    "    x = preprocess_input(x)  # standardized input pipeline\n",
     "\n",
     "    x = pretrained_model(x, training=False)\n",
     "\n",