01-deploy-text-embedding-model.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3a4bc882-63fb-4049-8551-d0fa3127bd6f",
   "metadata": {},
   "source": [
    "## Deploy Text Embedding Model (GPT-J 6B FP-16)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "259bf0cc-c971-48c7-a537-6cc5958c9267",
   "metadata": {},
   "source": [
    "#### Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fa427a29-aa9d-411c-8ffc-7cada2feb57f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sagemaker.jumpstart.notebook_utils import list_jumpstart_models\n",
    "from sagemaker.predictor import Predictor\n",
    "from sagemaker import get_execution_role\n",
    "from sagemaker.model import Model\n",
    "from sagemaker import image_uris \n",
    "from sagemaker import model_uris\n",
    "import sagemaker\n",
    "import logging\n",
    "import boto3\n",
    "import time"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09080f41-3b2c-464e-9557-a9fae1313b63",
   "metadata": {},
   "source": [
    "##### Setup logging"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "bde2a70f-471b-4eaf-9703-10fdcf67863e",
   "metadata": {},
   "outputs": [],
   "source": [
    "logger = logging.getLogger('sagemaker')\n",
    "logger.setLevel(logging.DEBUG)\n",
    "logger.addHandler(logging.StreamHandler())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5372bb7c-ba1d-46af-ad4c-2e77503f422a",
   "metadata": {},
   "source": [
    "##### Log versions of dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cb81aa05-1479-48e3-97fa-e9fa5a3684a5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using sagemaker==2.140.1\n",
      "Using boto3==1.26.96\n"
     ]
    }
   ],
   "source": [
    "logger.info(f'Using sagemaker=={sagemaker.__version__}')\n",
    "logger.info(f'Using boto3=={boto3.__version__}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df8a48e0-a23f-4fbd-9be2-811ae129622c",
   "metadata": {},
   "source": [
    "#### Setup essentials "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93dc7315-4803-440d-8dfb-e36f51c0a54f",
   "metadata": {},
   "source": [
    "##### List and filter all text embedding models available in JumpStart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9060ff53-7c41-4998-b258-c847a6ee09c0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Total number of models in SageMaker JumpStart hub = 649\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['huggingface-textembedding-bloom-7b1',\n",
       " 'huggingface-textembedding-bloom-7b1-fp16',\n",
       " 'huggingface-textembedding-gpt-j-6b',\n",
       " 'huggingface-textembedding-gpt-j-6b-fp16']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "models = list_jumpstart_models()\n",
    "logger.info(f'Total number of models in SageMaker JumpStart hub = {len(models)}')\n",
    "\n",
    "FILTER = 'task == textembedding'\n",
    "txt2img_models = list_jumpstart_models(filter=FILTER)\n",
    "txt2img_models"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34b6fcc4-a7d0-4f01-b2fa-d01ad3f0e2a5",
   "metadata": {},
   "source": [
    "##### Setup config params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1b77dc13-20d5-4dad-aa8a-45ed2f8e70bf",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Role => arn:aws:iam::119174016168:role/service-role/AmazonSageMaker-ExecutionRole-20211014T093628\n"
     ]
    }
   ],
   "source": [
    "MODEL_ID = 'huggingface-textembedding-gpt-j-6b-fp16'  \n",
    "MODEL_VERSION = '*'\n",
    "INSTANCE_TYPE = 'ml.g5.2xlarge'\n",
    "INSTANCE_COUNT = 1\n",
    "IMAGE_SCOPE = 'inference'\n",
    "MODEL_DATA_DOWNLOAD_TIMEOUT = 3600  # in seconds\n",
    "CONTAINER_STARTUP_HEALTH_CHECK_TIMEOUT = 3600\n",
    "CONTENT_TYPE = 'application/json'\n",
    "\n",
    "# Set up roles and clients \n",
    "client = boto3.client('sagemaker-runtime')\n",
    "ROLE = get_execution_role()\n",
    "logger.info(f'Role => {ROLE}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1526ad5f-9e74-459b-8dbd-1accdd576f12",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Endpoint name: huggingface-textembedding-gpt-j-6b-fp16-1680825746\n"
     ]
    }
   ],
   "source": [
    "unix_time = int(time.time())\n",
    "endpoint_name = f'{MODEL_ID}-{unix_time}'\n",
    "logger.info(f'Endpoint name: {endpoint_name}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "283e1db7-5629-495a-abd1-cf04351d2ad8",
   "metadata": {},
   "source": [
    "#### Retrieve image and model URIs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "187d02d5-93c9-4a87-bdd7-dd7443d7f64c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Deploy image URI => 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:1.12.0-gpu-py38\n"
     ]
    }
   ],
   "source": [
    "deploy_image_uri = image_uris.retrieve(region=None, \n",
    "                                       framework=None, \n",
    "                                       image_scope=IMAGE_SCOPE, \n",
    "                                       model_id=MODEL_ID, \n",
    "                                       model_version=MODEL_VERSION, \n",
    "                                       instance_type=INSTANCE_TYPE)\n",
    "logger.info(f'Deploy image URI => {deploy_image_uri}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "521ba56c-0b53-485c-9c96-b08c5a332a8f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Model URI => s3://jumpstart-cache-prod-us-east-1/huggingface-infer/infer-huggingface-textembedding-gpt-j-6b-fp16.tar.gz\n"
     ]
    }
   ],
   "source": [
    "model_uri = model_uris.retrieve(model_id=MODEL_ID, \n",
    "                                model_version=MODEL_VERSION, \n",
    "                                model_scope=IMAGE_SCOPE)\n",
    "logger.info(f'Model URI => {model_uri}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a32fbce5-500c-4606-8f19-e667e7c6e6a3",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "env = {\n",
    "    'SAGEMAKER_MODEL_SERVER_TIMEOUT': str(3600),\n",
    "    'MODEL_CACHE_ROOT': '/opt/ml/model', \n",
    "    'SAGEMAKER_ENV': '1',\n",
    "    'SAGEMAKER_SUBMIT_DIRECTORY': '/opt/ml/model/code/',\n",
    "    'SAGEMAKER_PROGRAM': 'inference.py',\n",
    "    'SAGEMAKER_MODEL_SERVER_WORKERS': '1', \n",
    "    'TS_DEFAULT_WORKERS_PER_MODEL': '1', \n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2657343-5a65-4c57-b39d-6c93107588c5",
   "metadata": {},
   "source": [
    "#### Create SageMaker Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "60aae2d1-c78a-4a89-890a-d6111ab95c57",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "model = Model(image_uri=deploy_image_uri, \n",
    "              model_data=model_uri, \n",
    "              role=ROLE, \n",
    "              predictor_cls=Predictor, \n",
    "              name=endpoint_name, \n",
    "              env=env)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a6b21c7-ff26-4dc1-89e9-aa5fea339771",
   "metadata": {},
   "source": [
    "#### Deploy text embedding model as SageMaker endpoint for real-time synchronous inference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0ce97c1f-b2e6-42e4-87c4-6fba2a92bed1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Creating model with name: huggingface-textembedding-gpt-j-6b-fp16-1680825746\n",
      "CreateModel request: {\n",
      "    \"ModelName\": \"huggingface-textembedding-gpt-j-6b-fp16-1680825746\",\n",
      "    \"ExecutionRoleArn\": \"arn:aws:iam::119174016168:role/service-role/AmazonSageMaker-ExecutionRole-20211014T093628\",\n",
      "    \"PrimaryContainer\": {\n",
      "        \"Image\": \"763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:1.12.0-gpu-py38\",\n",
      "        \"Environment\": {\n",
      "            \"SAGEMAKER_MODEL_SERVER_TIMEOUT\": \"3600\",\n",
      "            \"MODEL_CACHE_ROOT\": \"/opt/ml/model\",\n",
      "            \"SAGEMAKER_ENV\": \"1\",\n",
      "            \"SAGEMAKER_SUBMIT_DIRECTORY\": \"/opt/ml/model/code/\",\n",
      "            \"SAGEMAKER_PROGRAM\": \"inference.py\",\n",
      "            \"SAGEMAKER_MODEL_SERVER_WORKERS\": \"1\",\n",
      "            \"TS_DEFAULT_WORKERS_PER_MODEL\": \"1\"\n",
      "        },\n",
      "        \"ModelDataUrl\": \"s3://jumpstart-cache-prod-us-east-1/huggingface-infer/infer-huggingface-textembedding-gpt-j-6b-fp16.tar.gz\"\n",
      "    },\n",
      "    \"Tags\": [\n",
      "        {\n",
      "            \"Key\": \"aws-jumpstart-inference-model-uri\",\n",
      "            \"Value\": \"s3://jumpstart-cache-prod-us-east-1/huggingface-infer/infer-huggingface-textembedding-gpt-j-6b-fp16.tar.gz\"\n",
      "        }\n",
      "    ]\n",
      "}\n",
      "Creating endpoint-config with name huggingface-textembedding-gpt-j-6b-fp16-1680825746\n",
      "Creating endpoint with name huggingface-textembedding-gpt-j-6b-fp16-1680825746\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------!CPU times: user 206 ms, sys: 11.7 ms, total: 218 ms\n",
      "Wall time: 6min 3s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "_ = model.deploy(initial_instance_count=INSTANCE_COUNT, \n",
    "                 instance_type=INSTANCE_TYPE, \n",
    "                 endpoint_name=endpoint_name, \n",
    "                 model_data_download_timeout=MODEL_DATA_DOWNLOAD_TIMEOUT, \n",
    "                 container_startup_health_check_timeout=CONTAINER_STARTUP_HEALTH_CHECK_TIMEOUT)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "73161979-39d5-453e-b76f-56e6cee2c586",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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