upgrade: replace CURL with GAPIC

notebooks/community/ml_ops/stage5/get_started_with_vertex_endpoint_and_shared_vm.ipynb

@@ -159,9 +159,9 @@
         "\n",
         "# Install the packages\n",
         "\n",
-        "! pip3 install --upgrade google-cloud-aiplatform $USER_FLAG -q\n",
-        "! pip3 install --upgrade tensorflow $USER_FLAG -q\n",
-        "! pip3 install --upgrade tensorflow-hub $USER_FLAG -q"
+        "! pip3 install --upgrade google-cloud-aiplatform \\\n",
+        "                         tensorflow \\\n",
+        "                         tensorflow-hub $USER_FLAG -q"
       ]
     },
     {
@@ -307,22 +307,29 @@
         "id": "timestamp"
       },
       "source": [
-        "#### Timestamp\n",
+        "#### UUID\n",
         "\n",
-        "If you are in a live tutorial session, you might be using a shared test account or project. To avoid name collisions between users on resources created, you create a timestamp for each instance session, and append the timestamp onto the name of resources you create in this tutorial."
+        "If you are in a live tutorial session, you might be using a shared test account or project. To avoid name collisions between users on resources created, you create a uuid for each instance session, and append it onto the name of resources you create in this tutorial."
       ]
     },
     {
       "cell_type": "code",
       "execution_count": null,
       "metadata": {
-        "id": "timestamp"
+        "id": "84Vdv7R-QEH6"
       },
       "outputs": [],
       "source": [
-        "from datetime import datetime\n",
+        "import random\n",
+        "import string\n",
         "\n",
-        "TIMESTAMP = datetime.now().strftime(\"%Y%m%d%H%M%S\")"
+        "\n",
+        "# Generate a uuid of a specifed length(default=8)\n",
+        "def generate_uuid(length: int = 8) -> str:\n",
+        "    return \"\".join(random.choices(string.ascii_lowercase + string.digits, k=length))\n",
+        "\n",
+        "\n",
+        "UUID = generate_uuid()"
       ]
     },
     {
@@ -421,7 +428,7 @@
       "outputs": [],
       "source": [
         "if BUCKET_URI == \"\" or BUCKET_URI is None or BUCKET_URI == \"gs://[your-bucket-name]\":\n",
-        "    BUCKET_NAME = PROJECT_ID + \"aip-\" + TIMESTAMP\n",
+        "    BUCKET_NAME = PROJECT_ID + \"aip-\" + UUID\n",
         "    BUCKET_URI = \"gs://\" + BUCKET_NAME"
       ]
     },
@@ -523,7 +530,7 @@
         "\n",
         "Setup up the following constants for Vertex AI:\n",
         "\n",
-        "- `API_ENDPOINT`: The Vertex AI API service endpoint for `Endpoint` services."
+        "- `API_ENDPOINT`: The Vertex AI API service endpoint."
       ]
     },
     {
@@ -538,46 +545,10 @@
         "API_ENDPOINT = \"{}-aiplatform.googleapis.com\".format(REGION)\n",
         "\n",
         "# Vertex location root path for your dataset, model and endpoint resources\n",
-        "PARENT = \"projects/\" + PROJECT_ID + \"/locations/\" + REGION"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "clients:metadata"
-      },
-      "source": [
-        "## Set up clients\n",
+        "PARENT = \"projects/\" + PROJECT_ID + \"/locations/\" + REGION\n",
         "\n",
-        "The Vertex  works as a client/server model. On your side (the Python script) you will create a client that sends requests and receives responses from the Vertex AI server.\n",
-        "\n",
-        "You will use different clients in this tutorial for different steps in the workflow. So set them all up upfront.\n",
-        "\n",
-        "- Endpoint Service for creating endpoints, and deploying models to endpoints."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "clients:metadata"
-      },
-      "outputs": [],
-      "source": [
         "# client options same for all services\n",
-        "client_options = {\"api_endpoint\": API_ENDPOINT}\n",
-        "\n",
-        "\n",
-        "def create_endpoint_client():\n",
-        "    client = aip_beta.EndpointServiceClient(client_options=client_options)\n",
-        "    return client\n",
-        "\n",
-        "\n",
-        "clients = {}\n",
-        "clients[\"endpoint\"] = create_endpoint_client()\n",
-        "\n",
-        "for client in clients.items():\n",
-        "    print(client)"
+        "client_options = {\"api_endpoint\": API_ENDPOINT}"
       ]
     },
     {
@@ -592,7 +563,7 @@
         "\n",
         "Set the variables `DEPLOY_GPU/DEPLOY_NGPU` to use a container image supporting a GPU and the number of GPUs allocated to the virtual machine (VM) instance. For example, to use a GPU container image with 4 Nvidia Telsa K80 GPUs allocated to each VM, you would specify:\n",
         "\n",
-        "    (aip.AcceleratorType.NVIDIA_TESLA_K80, 4)\n",
+        "    (aip.gapic.AcceleratorType.NVIDIA_TESLA_K80, 4)\n",
         "\n",
         "\n",
         "Otherwise specify `(None, None)` to use a container image to run on a CPU.\n",
@@ -902,7 +873,7 @@
       "outputs": [],
       "source": [
         "model_icn = aiplatform.Model.upload(\n",
-        "    display_name=\"icn_\" + TIMESTAMP,\n",
+        "    display_name=\"icn_\" + UUID,\n",
         "    artifact_uri=MODEL_ICN_DIR,\n",
         "    serving_container_image_uri=DEPLOY_IMAGE,\n",
         ")\n",
@@ -1013,7 +984,7 @@
       "outputs": [],
       "source": [
         "model_use = aiplatform.Model.upload(\n",
-        "    display_name=\"icn_\" + TIMESTAMP,\n",
+        "    display_name=\"icn_\" + UUID,\n",
         "    artifact_uri=MODEL_USE_DIR,\n",
         "    serving_container_image_uri=DEPLOY_IMAGE,\n",
         ")\n",
@@ -1029,64 +1000,52 @@
       "source": [
         "## Creating a deployment resource pool\n",
         "\n",
-        "Currently, creating deploynent resource pools is only supported via the REST-based API (e.g., CURL).\n",
+        "Currently, creating deploynent resource pools is only supported via the REST-based API (e.g., CURL) and GAPIC APIs (Python).\n",
         "\n",
-        "Use `CreateDeploymentResourcePool` API to create a resource pool, with the following configuration:\n",
+        "Use `create_deployment_resource_pool` API to create a resource pool, with the following configuration:\n",
         "\n",
         "- `dedicated_resources`: Compute (HW) resources to allocate for the shared vm.\n",
         "- `min_replica_count`: Auto-scaling, the minimum number of compute nodes.\n",
         "- `max_replica_count`: Auto-scaling, the maximum number of compute nodes.\n",
         "\n",
-        "Learn more about [Deployment Resource Pools]()."
+        "Learn more about [Deployment Resource Pools](https://googleapis.dev/python/aiplatform/latest/aiplatform_v1beta1/deployment_resource_pool_service.html)."
       ]
     },
     {
       "cell_type": "code",
       "execution_count": null,
       "metadata": {
-        "id": "YiBmoiWYcMQt"
+        "id": "90c51b6cf34a"
       },
       "outputs": [],
       "source": [
-        "DEPLOYMENT_RESOURCE_POOL_ID = \"shared-vm\"  # @param {type: \"string\"}"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "0CHPJ4h-Slgs"
-      },
-      "outputs": [],
-      "source": [
-        "import json\n",
-        "import pprint\n",
-        "pp = pprint.PrettyPrinter(indent=4)\n",
-        "\n",
+        "DEPLOYMENT_RESOURCE_POOL_ID = f\"shared-vm-{UUID}\"  # @param {type: \"string\"}\n",
         "MIN_NODES = 1\n",
         "MAX_NODES = 2\n",
         "\n",
-        "CREATE_RP_PAYLOAD = {\n",
-        "  \"deployment_resource_pool\":{\n",
-        "    \"dedicated_resources\":{\n",
-        "      \"machine_spec\":{\n",
-        "        \"machine_type\": DEPLOY_COMPUTE\n",
-        "      },\n",
-        "      \"min_replica_count\": MIN_NODES, \n",
-        "      \"max_replica_count\": MAX_NODES\n",
-        "    }\n",
-        "  },\n",
-        "  \"deployment_resource_pool_id\":DEPLOYMENT_RESOURCE_POOL_ID\n",
-        "}\n",
-        "CREATE_RP_REQUEST=json.dumps(CREATE_RP_PAYLOAD)\n",
-        "pp.pprint(\"CREATE_RP_REQUEST: \" + CREATE_RP_REQUEST)\n",
+        "# Initialize request argument(s)\n",
+        "deployment_resource_pool = aip_beta.DeploymentResourcePool()\n",
+        "deployment_resource_pool.dedicated_resources.min_replica_count = MIN_NODES\n",
+        "deployment_resource_pool.dedicated_resources.max_replica_count = MAX_NODES\n",
+        "deployment_resource_pool.dedicated_resources.machine_spec.machine_type = DEPLOY_COMPUTE\n",
         "\n",
-        "! curl \\\n",
-        "-X POST \\\n",
-        "-H \"Authorization: Bearer $(gcloud auth print-access-token)\" \\\n",
-        "-H \"Content-Type: application/json\" \\\n",
-        "https://{REGION}-aiplatform.googleapis.com/v1beta1/projects/{PROJECT_ID}/locations/{REGION}/deploymentResourcePools \\\n",
-        "-d '{CREATE_RP_REQUEST}'"
+        "request = aip_beta.CreateDeploymentResourcePoolRequest(\n",
+        "    parent=f\"projects/{PROJECT_ID}/locations/{REGION}\",\n",
+        "    deployment_resource_pool=deployment_resource_pool,\n",
+        "    deployment_resource_pool_id=DEPLOYMENT_RESOURCE_POOL_ID,\n",
+        ")\n",
+        "\n",
+        "pool_client = aip_beta.services.deployment_resource_pool_service.DeploymentResourcePoolServiceClient(\n",
+        "    client_options=client_options\n",
+        ")\n",
+        "\n",
+        "op = pool_client.create_deployment_resource_pool(request=request)\n",
+        "print(op)\n",
+        "\n",
+        "result = op.result()\n",
+        "print(result)\n",
+        "\n",
+        "deployment_pool_id = result.name"
       ]
     },
     {
@@ -1099,21 +1058,19 @@
         "\n",
         "Use `GetDeploymentResourcePool` API to check out the deploynent resource pool that you created. \n",
         "\n",
-        "Learn more about [Get Deployment Resource Pool](https://source.corp.google.com/piper///depot/google3/google/cloud/aiplatform/master/deployment_resource_pool_service.proto;l=75?q=deployment_resource_pool&sq=package:piper%20file:%2F%2Fdepot%2Fgoogle3%20-file:google3%2Fexperimental)."
+        "Learn more about [Get Deployment Resource Pool](https://googleapis.dev/python/aiplatform/latest/aiplatform_v1beta1/deployment_resource_pool_service.html)."
       ]
     },
     {
       "cell_type": "code",
       "execution_count": null,
       "metadata": {
-        "id": "6wTLyhPraFah"
+        "id": "b740253903c0"
       },
       "outputs": [],
       "source": [
-        "! curl -X GET \\\n",
-        "-H \"Authorization: Bearer $(gcloud auth print-access-token)\" \\\n",
-        "-H \"Content-Type: application/json\" \\\n",
-        "https://{REGION}-aiplatform.googleapis.com/v1beta1/projects/{PROJECT_ID}/locations/{REGION}/deploymentResourcePools/{DEPLOYMENT_RESOURCE_POOL_ID}"
+        "response = pool_client.get_deployment_resource_pool(name=deployment_pool_id)\n",
+        "print(response)"
       ]
     },
     {
@@ -1126,21 +1083,22 @@
         "\n",
         "Use `ListDeploymentResourcePools` API to list all the deployment resource pools. \n",
         "\n",
-        "Learn more about [Listing Deployment Resource Pools](https://source.corp.google.com/piper///depot/google3/google/cloud/aiplatform/master/deployment_resource_pool_service.proto;l=101?q=deployment_resource_pool&sq=package:piper%20file:%2F%2Fdepot%2Fgoogle3%20-file:google3%2Fexperimental)."
+        "Learn more about [Listing Deployment Resource Pools](https://googleapis.dev/python/aiplatform/latest/aiplatform_v1beta1/deployment_resource_pool_service.html)."
       ]
     },
     {
       "cell_type": "code",
       "execution_count": null,
       "metadata": {
-        "id": "Pxls4sNnaltU"
+        "id": "3ebfd007bff2"
       },
       "outputs": [],
       "source": [
-        "! curl -X GET \\\n",
-        "-H \"Authorization: Bearer $(gcloud auth print-access-token)\" \\\n",
-        "-H \"Content-Type: application/json\" \\\n",
-        "https://{REGION}-aiplatform.googleapis.com/v1beta1/projects/{PROJECT_ID}/locations/{REGION}/deploymentResourcePools"
+        "pools = pool_client.list_deployment_resource_pools(\n",
+        "    parent=f\"projects/{PROJECT_ID}/locations/{REGION}\"\n",
+        ")\n",
+        "for pool in pools:\n",
+        "    print(pool)"
       ]
     },
     {
@@ -1170,11 +1128,11 @@
       },
       "outputs": [],
       "source": [
-        "endpoint_icn = aiplatform.Endpoint.create(display_name=\"icn_\" + TIMESTAMP)\n",
+        "endpoint_icn = aiplatform.Endpoint.create(display_name=\"icn_\" + UUID)\n",
         "\n",
         "print(endpoint_icn)\n",
         "\n",
-        "endpoint_use = aiplatform.Endpoint.create(display_name=\"use_\" + TIMESTAMP)\n",
+        "endpoint_use = aiplatform.Endpoint.create(display_name=\"use_\" + UUID)\n",
         "\n",
         "print(endpoint_use)"
       ]
@@ -1204,6 +1162,12 @@
       },
       "outputs": [],
       "source": [
+        "import json\n",
+        "import pprint\n",
+        "\n",
+        "pp = pprint.PrettyPrinter(indent=4)\n",
+        "\n",
+        "\n",
         "SHARED_RESOURCE = \"projects/{project_id}/locations/{region}/deploymentResourcePools/{deployment_resource_pool_id}\".format(\n",
         "    project_id=PROJECT_ID,\n",
         "    region=REGION,\n",
@@ -1363,18 +1327,27 @@
         "    time.sleep(30)"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "52248c450776"
+      },
+      "source": [
+        "### Get deployment details for the endpoint\n",
+        "\n",
+        "List the deployed models on the endpoint."
+      ]
+    },
     {
       "cell_type": "code",
       "execution_count": null,
       "metadata": {
-        "id": "86a659bf60f0"
+        "id": "3b768614e7c6"
       },
       "outputs": [],
       "source": [
-        "! curl -X GET \\\n",
-        " -H \"Authorization: Bearer $(gcloud auth print-access-token)\" \\\n",
-        " -H \"Content-Type: application/json\" \\\n",
-        "https://{REGION}-aiplatform.googleapis.com/v1/projects/759209241365/locations/us-central1/endpoints/2259566763823857664"
+        "print(endpoint_icn.list_models())\n",
+        "print(endpoint_use.list_models())"
       ]
     },
     {
@@ -1557,21 +1530,19 @@
       "source": [
         "#### Delete the `DeploymentResourcePool`\n",
         "\n",
-        "The method 'delete()' will delete your deployment resource pool."
+        "The method 'delete_deployment_resource_pool()' will delete your deployment resource pool."
       ]
     },
     {
       "cell_type": "code",
       "execution_count": null,
       "metadata": {
-        "id": "ac40cc1d594a"
+        "id": "b76a4de1e57e"
       },
       "outputs": [],
       "source": [
-        "! curl -X DELETE \\\n",
-        "-H \"Authorization: Bearer $(gcloud auth print-access-token)\" \\\n",
-        "-H \"Content-Type: application/json\" \\\n",
-        "https://{REGION}-aiplatform.googleapis.com/v1beta1/projects/{PROJECT_ID}/locations/{REGION}/deploymentResourcePools/{DEPLOYMENT_RESOURCE_POOL_ID}"
+        "response = pool_client.delete_deployment_resource_pool(name=deployment_pool_id)\n",
+        "print(response)"
       ]
     },
     {