Enable the use of dedicated Endpoints in instructpix2pix notebook

PiperOrigin-RevId: 751641417

Author: vertex-mg-bot

notebooks/community/model_garden/model_garden_pytorch_instructpix2pix.ipynb

@@ -178,7 +178,10 @@
         "# The machine and accelerator specs for model deployment.\n",
         "accelerator_type = \"NVIDIA_L4\"\n",
         "machine_type = \"g2-standard-12\"\n",
-        "accelerator_count = 1"
+        "accelerator_count = 1\n",
+        "\n",
+        "# @markdown Set use_dedicated_endpoint to False if you don't want to use [dedicated endpoint](https://cloud.google.com/vertex-ai/docs/general/deployment#create-dedicated-endpoint). Note that [dedicated endpoint does not support VPC Service Controls](https://cloud.google.com/vertex-ai/docs/predictions/choose-endpoint-type), uncheck the box if you are using VPC-SC.\n",
+        "use_dedicated_endpoint = True  # @param {type:\"boolean\"}"
       ]
     },
     {
@@ -200,6 +203,7 @@
         "    machine_type=machine_type,\n",
         "    accelerator_type=accelerator_type,\n",
         "    accelerator_count=accelerator_count,\n",
+        "    use_dedicated_endpoint=use_dedicated_endpoint,\n",
         "    accept_eula=True,  # Accept the End User License Agreement (EULA) on the model card before deploy. Otherwise, the deployment will be forbidden.\n",
         ")"
       ]
@@ -226,9 +230,13 @@
         "    machine_type: str,\n",
         "    accelerator_type: str,\n",
         "    accelerator_count: int,\n",
+        "    use_dedicated_endpoint: bool = False,\n",
         "):\n",
         "    model_name = \"instruct-pix2pix\"\n",
-        "    endpoint = aiplatform.Endpoint.create(display_name=f\"{model_name}-endpoint\")\n",
+        "    endpoint = aiplatform.Endpoint.create(\n",
+        "        display_name=f\"{model_name}-endpoint\",\n",
+        "        dedicated_endpoint_enabled=use_dedicated_endpoint,\n",
+        "    )\n",
         "    serving_env = {\n",
         "        \"MODEL_ID\": model_id,\n",
         "        \"TASK\": task,\n",
@@ -272,6 +280,7 @@
         "    machine_type=machine_type,\n",
         "    accelerator_type=accelerator_type,\n",
         "    accelerator_count=accelerator_count,\n",
+        "    use_dedicated_endpoint=use_dedicated_endpoint,\n",
         ")"
       ]
     },
@@ -302,7 +311,9 @@
         "        \"num_inference_steps\": num_inference_steps,\n",
         "    },\n",
         "]\n",
-        "response = endpoints[LABEL].predict(instances=instances)\n",
+        "response = endpoints[LABEL].predict(\n",
+        "    instances=instances, use_dedicated_endpoint=use_dedicated_endpoint\n",
+        ")\n",
         "images = [common_util.base64_to_image(image) for image in response.predictions]\n",
         "common_util.image_grid([init_image, images[0]], rows=1, cols=2)"
       ]