{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "32d1de35-e1c3-437c-87f4-8b5c9a30b305",
   "metadata": {},
   "source": [
    "# Alpaca-LoRA SageMaker Inference\n",
    "\n",
    "This is a sample code to deploy Alpaca-LoRA to SageMaker Endpoint."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "35d41704-9ec7-4225-9fd6-d1a39d7edfd4",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install \"sagemaker>=2.143.0\" -U"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aa63ba70-5255-461f-8b65-abd58b69759e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import sagemaker, boto3, json\n",
    "from sagemaker import get_execution_role\n",
    "from sagemaker.pytorch.model import PyTorchModel\n",
    "from sagemaker.huggingface import HuggingFaceModel\n",
    "\n",
    "role = get_execution_role()\n",
    "region = boto3.Session().region_name\n",
    "sess = sagemaker.Session()\n",
    "bucket = sess.default_bucket()\n",
    "\n",
    "sagemaker.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7158f6d6-7415-438a-a1ad-17f22bde4fd5",
   "metadata": {},
   "source": [
    "## Package and Upload Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7fa5ac97-eac7-483e-8bc1-aa8695026b96",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [],
   "source": [
    "%cd scripts\n",
    "!tar -czvf ../package.tar.gz *\n",
    "%cd -"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f5324744-0f23-45f2-9c96-e1c95f2b86d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "model_path = sess.upload_data('package.tar.gz', bucket=bucket, key_prefix=f\"Alpaca\")\n",
    "model_path"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb7bf0c7-bf47-4fbd-b287-c14453c4257c",
   "metadata": {},
   "source": [
    "## Deploy Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3b8df839-c601-4a17-8bd2-b4f8401129c0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from sagemaker.async_inference import AsyncInferenceConfig\n",
    "from sagemaker.serializers import JSONSerializer\n",
    "\n",
    "endpoint_name = \"Alpaca-Inference-ja2\"\n",
    "\n",
    "huggingface_model = PyTorchModel(\n",
    "    model_data=model_path,\n",
    "    framework_version=\"1.13\",\n",
    "    py_version='py39',\n",
    "    role=role,\n",
    "    name=endpoint_name,\n",
    "    env={\n",
    "        \"model_params\": json.dumps({\n",
    "            \"base_model\": \"huggyllama/llama-7b\",\n",
    "            \"lora_weights\": \"kunishou/Japanese-Alpaca-LoRA-7b-v0\",\n",
    "            \"peft\": True,\n",
    "            \"load_8bit\": True,\n",
    "            \"prompt_template\": \"alpaca\",\n",
    "        }),\n",
    "        \"SAGEMAKER_MODEL_SERVER_TIMEOUT\": \"3600\"\n",
    "    }\n",
    ")\n",
    "\n",
    "# deploy model to SageMaker Inference\n",
    "predictor = huggingface_model.deploy(\n",
    "    initial_instance_count=1,\n",
    "    instance_type='ml.g5.xlarge',\n",
    "    endpoint_name=endpoint_name,\n",
    "    serializer=JSONSerializer(),\n",
    "    # async_inference_config=AsyncInferenceConfig()\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "840e9ea2-ba94-4641-be47-3ab69a712a3d",
   "metadata": {},
   "source": [
    "## Run Inference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ca0248d3-c99c-42bc-bf2a-ad988ab747da",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# With SageMaker SDK\n",
    "\n",
    "from sagemaker.predictor import Predictor\n",
    "from sagemaker.predictor_async import AsyncPredictor\n",
    "from sagemaker.serializers import JSONSerializer\n",
    "from sagemaker.deserializers import JSONDeserializer\n",
    "\n",
    "predictor_client = Predictor(\n",
    "    endpoint_name=endpoint_name,\n",
    "    sagemaker_session=sess,\n",
    "    serializer=JSONSerializer(),\n",
    "    deserializer=JSONDeserializer()\n",
    ")\n",
    "# predictor_client = AsyncPredictor(\n",
    "#     predictor=predictor_client,\n",
    "#     name=endpoint_name\n",
    "# )\n",
    "data = {\n",
    "    \"instruction\": \"以下の質問に答えてください\",\n",
    "    \"input\": \"AWS とはなんですか？\",\n",
    "    \"max_new_tokens\": 128\n",
    "}\n",
    "response = predictor_client.predict(\n",
    "    data=data\n",
    ")\n",
    "print(response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef667148-8c98-481a-a1c5-6815b903e727",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# With Boto3\n",
    "\n",
    "import boto3\n",
    "import json\n",
    "\n",
    "endpoint_name = \"Alpaca-Inference-ja\"\n",
    "sagemaker_client = boto3.client('sagemaker-runtime')\n",
    "\n",
    "data = {\n",
    "    \"instruction\": \"以下の質問に答えてください\",\n",
    "    \"input\": \"AWS とはなんですか？\",\n",
    "    \"max_new_tokens\": 128,\n",
    "}\n",
    "\n",
    "response = sagemaker_client.invoke_endpoint(\n",
    "    EndpointName=endpoint_name,\n",
    "    ContentType='application/json',\n",
    "    Accept='application/json',\n",
    "    Body=json.dumps(data)\n",
    ")\n",
    "\n",
    "result = json.loads(response['Body'].read())\n",
    "print(result)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8d5dc4d-51b2-4a7f-84b6-75a7fc79f6e3",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Benchmark Speed\n",
    "\n",
    "16.1 s ± 23.2 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "976f8438-8cff-4f52-b95a-d96b61ddc07f",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "%timeit response = predictor_client.predict(data=data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80445a88-1cbf-4ed0-b90b-fc6a5ae69baa",
   "metadata": {},
   "source": [
    "## Delete Endpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "824e9700-ceb5-459c-b289-89bbb9d2e064",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "predictor.delete_model()\n",
    "predictor.delete_endpoint()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1f2e8890-c595-4b08-b12a-f03fceef50a8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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