{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"tags": []
},
"source": [
"# Deploy the Model\n",
"\n",
"The pipeline that was executed created a Model Package version within the specified Model Package Group. Of particular note, the registration of the model/creation of the Model Package was done so with approval status as `PendingManualApproval`.\n",
"\n",
"As part of SageMaker Pipelines, data scientists can register the model with approved/pending manual approval as part of the CI/CD workflow.\n",
"\n",
"We can also approve the model using the SageMaker Studio UI or programmatically as shown below.\n",
"\n",
""
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": []
},
"source": [
"\n",
"## Set up Kernel and Required Dependencies"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": []
},
"source": [
"First, check that the correct kernel is chosen.\n",
"\n",
"
\n",
"\n",
"You can click on that to see and check the details of the image, kernel, and instance type.\n",
"\n",
"
"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import psutil\n",
"\n",
"notebook_memory = psutil.virtual_memory()\n",
"print(notebook_memory)\n",
"\n",
"if notebook_memory.total < 32 * 1000 * 1000 * 1000:\n",
" print('*******************************************') \n",
" print('YOU ARE NOT USING THE CORRECT INSTANCE TYPE')\n",
" print('PLEASE CHANGE INSTANCE TYPE TO m5.2xlarge ')\n",
" print('*******************************************')\n",
"else:\n",
" correct_instance_type=True"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from botocore.exceptions import ClientError\n",
"\n",
"import os\n",
"import sagemaker\n",
"import logging\n",
"import boto3\n",
"import sagemaker\n",
"\n",
"sess = sagemaker.Session()\n",
"bucket = sess.default_bucket()\n",
"region = boto3.Session().region_name\n",
"\n",
"import botocore.config\n",
"\n",
"config = botocore.config.Config(\n",
" user_agent_extra='dsoaws/2.0'\n",
")\n",
"\n",
"sm = boto3.Session().client(service_name=\"sagemaker\", \n",
" region_name=region,\n",
" config=config)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Retrieve model endpoint\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%store -r pipeline_endpoint_name"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"try:\n",
" pipeline_endpoint_name\n",
"except NameError:\n",
" print(\"++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\")\n",
" print(\"[ERROR] Please run previous notebooks before you continue.\")\n",
" print(\"++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(pipeline_endpoint_name)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from IPython.core.display import display, HTML\n",
"\n",
"display(\n",
" HTML(\n",
" 'Review SageMaker HTTPS Endpoint'.format(\n",
" region, pipeline_endpoint_name\n",
" )\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": []
},
"source": [
"# _Wait Until the Endpoint is Deployed_\n",
"_Note: This will take a few minutes. Please be patient._"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%%time\n",
"\n",
"waiter = sm.get_waiter(\"endpoint_in_service\")\n",
"waiter.wait(EndpointName=pipeline_endpoint_name)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# _Wait Until the Endpoint ^^ Above ^^ is Deployed_"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Zero Shot Inference"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"import json\n",
"from sagemaker import Predictor\n",
"\n",
"zero_shot_prompt = \"\"\"Summarize the following conversation.\n",
"\n",
"#Person1#: Tom, I've got good news for you.\n",
"#Person2#: What is it?\n",
"#Person1#: Haven't you heard that your novel has won The Nobel Prize?\n",
"#Person2#: Really? I can't believe it. It's like a dream come true. I never expected that I would win The Nobel Prize!\n",
"#Person1#: You did a good job. I'm extremely proud of you.\n",
"#Person2#: Thanks for the compliment.\n",
"#Person1#: You certainly deserve it. Let's celebrate!\n",
"\n",
"Summary:\"\"\"\n",
"predictor = Predictor(\n",
" endpoint_name=pipeline_endpoint_name,\n",
" sagemaker_session=sess,\n",
")\n",
"response = predictor.predict(zero_shot_prompt,\n",
" {\n",
" \"ContentType\": \"application/x-text\",\n",
" \"Accept\": \"application/json\",\n",
" },\n",
")\n",
"response_json = json.loads(response.decode('utf-8'))\n",
"print(response_json)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Clean Up: Tear Down Endpoint"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# sm.delete_endpoint(\n",
"# EndpointName=pipeline_endpoint_name\n",
"# )"
]
}
],
"metadata": {
"availableInstances": [
{
"_defaultOrder": 0,
"_isFastLaunch": true,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 4,
"name": "ml.t3.medium",
"vcpuNum": 2
},
{
"_defaultOrder": 1,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 8,
"name": "ml.t3.large",
"vcpuNum": 2
},
{
"_defaultOrder": 2,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 16,
"name": "ml.t3.xlarge",
"vcpuNum": 4
},
{
"_defaultOrder": 3,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 32,
"name": "ml.t3.2xlarge",
"vcpuNum": 8
},
{
"_defaultOrder": 4,
"_isFastLaunch": true,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 8,
"name": "ml.m5.large",
"vcpuNum": 2
},
{
"_defaultOrder": 5,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 16,
"name": "ml.m5.xlarge",
"vcpuNum": 4
},
{
"_defaultOrder": 6,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 32,
"name": "ml.m5.2xlarge",
"vcpuNum": 8
},
{
"_defaultOrder": 7,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 64,
"name": "ml.m5.4xlarge",
"vcpuNum": 16
},
{
"_defaultOrder": 8,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 128,
"name": "ml.m5.8xlarge",
"vcpuNum": 32
},
{
"_defaultOrder": 9,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 192,
"name": "ml.m5.12xlarge",
"vcpuNum": 48
},
{
"_defaultOrder": 10,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 256,
"name": "ml.m5.16xlarge",
"vcpuNum": 64
},
{
"_defaultOrder": 11,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 384,
"name": "ml.m5.24xlarge",
"vcpuNum": 96
},
{
"_defaultOrder": 12,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 8,
"name": "ml.m5d.large",
"vcpuNum": 2
},
{
"_defaultOrder": 13,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 16,
"name": "ml.m5d.xlarge",
"vcpuNum": 4
},
{
"_defaultOrder": 14,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 32,
"name": "ml.m5d.2xlarge",
"vcpuNum": 8
},
{
"_defaultOrder": 15,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 64,
"name": "ml.m5d.4xlarge",
"vcpuNum": 16
},
{
"_defaultOrder": 16,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 128,
"name": "ml.m5d.8xlarge",
"vcpuNum": 32
},
{
"_defaultOrder": 17,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 192,
"name": "ml.m5d.12xlarge",
"vcpuNum": 48
},
{
"_defaultOrder": 18,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 256,
"name": "ml.m5d.16xlarge",
"vcpuNum": 64
},
{
"_defaultOrder": 19,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 384,
"name": "ml.m5d.24xlarge",
"vcpuNum": 96
},
{
"_defaultOrder": 20,
"_isFastLaunch": false,
"category": "General purpose",
"gpuNum": 0,
"hideHardwareSpecs": true,
"memoryGiB": 0,
"name": "ml.geospatial.interactive",
"supportedImageNames": [
"sagemaker-geospatial-v1-0"
],
"vcpuNum": 0
},
{
"_defaultOrder": 21,
"_isFastLaunch": true,
"category": "Compute optimized",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 4,
"name": "ml.c5.large",
"vcpuNum": 2
},
{
"_defaultOrder": 22,
"_isFastLaunch": false,
"category": "Compute optimized",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 8,
"name": "ml.c5.xlarge",
"vcpuNum": 4
},
{
"_defaultOrder": 23,
"_isFastLaunch": false,
"category": "Compute optimized",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 16,
"name": "ml.c5.2xlarge",
"vcpuNum": 8
},
{
"_defaultOrder": 24,
"_isFastLaunch": false,
"category": "Compute optimized",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 32,
"name": "ml.c5.4xlarge",
"vcpuNum": 16
},
{
"_defaultOrder": 25,
"_isFastLaunch": false,
"category": "Compute optimized",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 72,
"name": "ml.c5.9xlarge",
"vcpuNum": 36
},
{
"_defaultOrder": 26,
"_isFastLaunch": false,
"category": "Compute optimized",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 96,
"name": "ml.c5.12xlarge",
"vcpuNum": 48
},
{
"_defaultOrder": 27,
"_isFastLaunch": false,
"category": "Compute optimized",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 144,
"name": "ml.c5.18xlarge",
"vcpuNum": 72
},
{
"_defaultOrder": 28,
"_isFastLaunch": false,
"category": "Compute optimized",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 192,
"name": "ml.c5.24xlarge",
"vcpuNum": 96
},
{
"_defaultOrder": 29,
"_isFastLaunch": true,
"category": "Accelerated computing",
"gpuNum": 1,
"hideHardwareSpecs": false,
"memoryGiB": 16,
"name": "ml.g4dn.xlarge",
"vcpuNum": 4
},
{
"_defaultOrder": 30,
"_isFastLaunch": false,
"category": "Accelerated computing",
"gpuNum": 1,
"hideHardwareSpecs": false,
"memoryGiB": 32,
"name": "ml.g4dn.2xlarge",
"vcpuNum": 8
},
{
"_defaultOrder": 31,
"_isFastLaunch": false,
"category": "Accelerated computing",
"gpuNum": 1,
"hideHardwareSpecs": false,
"memoryGiB": 64,
"name": "ml.g4dn.4xlarge",
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},
{
"_defaultOrder": 32,
"_isFastLaunch": false,
"category": "Accelerated computing",
"gpuNum": 1,
"hideHardwareSpecs": false,
"memoryGiB": 128,
"name": "ml.g4dn.8xlarge",
"vcpuNum": 32
},
{
"_defaultOrder": 33,
"_isFastLaunch": false,
"category": "Accelerated computing",
"gpuNum": 4,
"hideHardwareSpecs": false,
"memoryGiB": 192,
"name": "ml.g4dn.12xlarge",
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},
{
"_defaultOrder": 34,
"_isFastLaunch": false,
"category": "Accelerated computing",
"gpuNum": 1,
"hideHardwareSpecs": false,
"memoryGiB": 256,
"name": "ml.g4dn.16xlarge",
"vcpuNum": 64
},
{
"_defaultOrder": 35,
"_isFastLaunch": false,
"category": "Accelerated computing",
"gpuNum": 1,
"hideHardwareSpecs": false,
"memoryGiB": 61,
"name": "ml.p3.2xlarge",
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},
{
"_defaultOrder": 36,
"_isFastLaunch": false,
"category": "Accelerated computing",
"gpuNum": 4,
"hideHardwareSpecs": false,
"memoryGiB": 244,
"name": "ml.p3.8xlarge",
"vcpuNum": 32
},
{
"_defaultOrder": 37,
"_isFastLaunch": false,
"category": "Accelerated computing",
"gpuNum": 8,
"hideHardwareSpecs": false,
"memoryGiB": 488,
"name": "ml.p3.16xlarge",
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},
{
"_defaultOrder": 38,
"_isFastLaunch": false,
"category": "Accelerated computing",
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"hideHardwareSpecs": false,
"memoryGiB": 768,
"name": "ml.p3dn.24xlarge",
"vcpuNum": 96
},
{
"_defaultOrder": 39,
"_isFastLaunch": false,
"category": "Memory Optimized",
"gpuNum": 0,
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"name": "ml.r5.large",
"vcpuNum": 2
},
{
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"_isFastLaunch": false,
"category": "Memory Optimized",
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"name": "ml.r5.xlarge",
"vcpuNum": 4
},
{
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"_isFastLaunch": false,
"category": "Memory Optimized",
"gpuNum": 0,
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"name": "ml.r5.2xlarge",
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},
{
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"category": "Memory Optimized",
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"name": "ml.r5.4xlarge",
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},
{
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"_isFastLaunch": false,
"category": "Memory Optimized",
"gpuNum": 0,
"hideHardwareSpecs": false,
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"name": "ml.r5.8xlarge",
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},
{
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"category": "Memory Optimized",
"gpuNum": 0,
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"name": "ml.r5.12xlarge",
"vcpuNum": 48
},
{
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"_isFastLaunch": false,
"category": "Memory Optimized",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 512,
"name": "ml.r5.16xlarge",
"vcpuNum": 64
},
{
"_defaultOrder": 46,
"_isFastLaunch": false,
"category": "Memory Optimized",
"gpuNum": 0,
"hideHardwareSpecs": false,
"memoryGiB": 768,
"name": "ml.r5.24xlarge",
"vcpuNum": 96
},
{
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"category": "Accelerated computing",
"gpuNum": 1,
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"name": "ml.g5.xlarge",
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},
{
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"category": "Accelerated computing",
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"name": "ml.g5.2xlarge",
"vcpuNum": 8
},
{
"_defaultOrder": 49,
"_isFastLaunch": false,
"category": "Accelerated computing",
"gpuNum": 1,
"hideHardwareSpecs": false,
"memoryGiB": 64,
"name": "ml.g5.4xlarge",
"vcpuNum": 16
},
{
"_defaultOrder": 50,
"_isFastLaunch": false,
"category": "Accelerated computing",
"gpuNum": 1,
"hideHardwareSpecs": false,
"memoryGiB": 128,
"name": "ml.g5.8xlarge",
"vcpuNum": 32
},
{
"_defaultOrder": 51,
"_isFastLaunch": false,
"category": "Accelerated computing",
"gpuNum": 1,
"hideHardwareSpecs": false,
"memoryGiB": 256,
"name": "ml.g5.16xlarge",
"vcpuNum": 64
},
{
"_defaultOrder": 52,
"_isFastLaunch": false,
"category": "Accelerated computing",
"gpuNum": 4,
"hideHardwareSpecs": false,
"memoryGiB": 192,
"name": "ml.g5.12xlarge",
"vcpuNum": 48
},
{
"_defaultOrder": 53,
"_isFastLaunch": false,
"category": "Accelerated computing",
"gpuNum": 4,
"hideHardwareSpecs": false,
"memoryGiB": 384,
"name": "ml.g5.24xlarge",
"vcpuNum": 96
},
{
"_defaultOrder": 54,
"_isFastLaunch": false,
"category": "Accelerated computing",
"gpuNum": 8,
"hideHardwareSpecs": false,
"memoryGiB": 768,
"name": "ml.g5.48xlarge",
"vcpuNum": 192
},
{
"_defaultOrder": 55,
"_isFastLaunch": false,
"category": "Accelerated computing",
"gpuNum": 8,
"hideHardwareSpecs": false,
"memoryGiB": 1152,
"name": "ml.p4d.24xlarge",
"vcpuNum": 96
},
{
"_defaultOrder": 56,
"_isFastLaunch": false,
"category": "Accelerated computing",
"gpuNum": 8,
"hideHardwareSpecs": false,
"memoryGiB": 1152,
"name": "ml.p4de.24xlarge",
"vcpuNum": 96
}
],
"instance_type": "ml.m5.2xlarge",
"kernelspec": {
"display_name": "Python 3 (Data Science)",
"language": "python",
"name": "python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:us-east-1:081325390199:image/datascience-1.0"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.10"
}
},
"nbformat": 4,
"nbformat_minor": 4
}