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[Do not merge] DAI e2e test flow to support migration #22

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387 changes: 387 additions & 0 deletions 6 DAI:Migration Test.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"id": "2d6f9dba",
"metadata": {},
"source": [
"## Create an AI engine\n",
"Create a Driverless AI engine for access to automated machine learning to build models for us on our data. \n",
"\n",
"See the `2 AI Engines` tutorial for more details on how to use and interact with **Steam** for creating and managing your AI Engines.\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "7737ea3f",
"metadata": {},
"outputs": [],
"source": [
"from h2o_ai_cloud import steam_client\n",
"from h2osteam.clients import DriverlessClient"
]
},
{
"cell_type": "markdown",
"id": "9dd339a5",
"metadata": {},
"source": [
"## Securely connect \n",
"We first connect to the H2O AI Cloud using our platform token to create a token provider object. We can then use this object to log into Steam and other APIs."
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "6df7371e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Visit https://cloud-dev.h2o.ai/auth/get-platform-token to get your platform token\n"
]
}
],
"source": [
"steam = steam_client()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "5092a663",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['jg-driverless-kubernetes', 'aaa', 'admin-driverless-kubernetes', 'dai-with-h2o-drive-k8s', 'default-driverless-kubernetes-low-mem', 'gbq-driverless-kubernetes', 'default-driverless-kubernetes', 'visitor-driverless-kubernetes', 'se-driverless-kubernetes', 'dai-multinode-tmpfs', 'dai-multinode-tmpfs-14cores', 'multinode-single-user', 'multinode-single-user-fixed-workers', 'multinode-single-user-no-dask', 'multinode-single-user-no-gpu', 'default-driverless-kubernetes-migration', 'multinode-single-user-cpu', 'default-driverless-kubernetes-max_cores8', 'custom-driverless-cpu-test', 'custom-driverless-cpu-test-4core']\n"
]
}
],
"source": [
"# Profiles determin the resourcs that an AI Engine will have access to - see the Steam tutorial for more information\n",
"dai_profiles = [profile[\"name\"] for profile in steam.get_profiles() if profile[\"profile_type\"] == \"driverless_kubernetes\"]\n",
"\n",
"print(dai_profiles)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "2398dfce",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['default-driverless-kubernetes-migration']\n"
]
}
],
"source": [
"# Get the migration profile\n",
"migration_profile = \"default-driverless-kubernetes-migration\"\n",
"dai_profiles = [profile for profile in dai_profiles if profile == migration_profile]\n",
"print(dai_profiles)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"DAI status is running\n",
"DAI run status is running\n"
]
}
],
"source": [
"# Create DAI instance\n",
"DAI_VERSION = \"1.10.4.99\"\n",
"dai_instance_name = \"joby-dai-e2e-migration\"\n",
"\n",
"try:\n",
" dai_instance = DriverlessClient(steam).get_instance(name=dai_instance_name)\n",
"except Exception as e:\n",
" print(f'Starting new DAI {DAI_VERSION} instance')\n",
" dai_instance = DriverlessClient(steam).launch_instance(\n",
" name = dai_instance_name,\n",
" version = DAI_VERSION,\n",
" profile_name=dai_profiles[0],\n",
" )\n",
"status = dai_instance.status()\n",
"print(f'DAI status is {status}')\n",
"\n",
"if status == \"stopped\":\n",
" dai_instance.start()\n",
"\n",
"print(f'DAI run status is {dai_instance.status()}')"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 28,
"outputs": [],
"source": [
"# Get the DAI python client\n",
"dai_client = dai_instance.connect()"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "markdown",
"source": [
"## Driverless python client APIs\n",
"DAI functionality with python client"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 32,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1.10.4\n",
"['upload', 'file', 'hdfs', 's3', 'recipe_file', 'recipe_url', 'h2o_drive', 'feature_store']\n"
]
}
],
"source": [
"print(dai_client.server.version)\n",
"print(dai_client.connectors.list())"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 39,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1.10.2-walmart-catboost-byor (c74a42bc-aeb1-11ec-8f4b-0242ac120002)\n"
]
}
],
"source": [
"# List of experiments available\n",
"list_of_experiments = dai_client.experiments.list()\n",
"experiment = [exp for exp in list_of_experiments if '1.10.2' in exp.name][0]\n",
"print(experiment)"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "markdown",
"source": [
"### Fetch experiment datasets\n"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 48,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'train_dataset': <class 'Dataset'> ff759814-aeaf-11ec-b224-0242ac120002 walmart_train.csv, 'validation_dataset': None, 'test_dataset': None}\n",
"ff759814-aeaf-11ec-b224-0242ac120002\n"
]
}
],
"source": [
"assert experiment.is_running() is False\n",
"print(experiment.datasets)\n",
"dataset = experiment.datasets.get('train_dataset')\n",
"print(dataset.key)"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 55,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"dai_e2e_test_migration\n"
]
}
],
"source": [
"# Create a test project\n",
"project_name = \"dai_e2e_test_migration\"\n",
"projects = dai_client.projects.list()\n",
"\n",
"list_of_project = [p for p in projects if project_name in p.name]\n",
"if len(list_of_project) == 0 :\n",
" project = dai_client.projects.create(\n",
" name = project_name,\n",
" description = \"Test migration\",\n",
" )\n",
"else:\n",
" project = list_of_project[0]\n",
"print(project.name)"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 56,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" | Type | Key | Name\n",
"----+------------+--------------------------------------+------------------------------\n",
" 0 | Experiment | c74a42bc-aeb1-11ec-8f4b-0242ac120002 | 1.10.2-walmart-catboost-byor\n",
"{'test_datasets': | Type | Key | Name\n",
"----+--------+-------+--------, 'train_datasets': | Type | Key | Name\n",
"----+---------+--------------------------------------+-------------------\n",
" 0 | Dataset | ff759814-aeaf-11ec-b224-0242ac120002 | walmart_train.csv, 'validation_datasets': | Type | Key | Name\n",
"----+--------+-------+--------}\n"
]
}
],
"source": [
"# Attach experiment and dataset to the project\n",
"project.link_experiment(experiment = experiment)\n",
"\n",
"print(project.experiments)\n",
"print(project.datasets)"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "markdown",
"source": [
"### Query for the experiment artifacts in mlops\n"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 58,
"outputs": [],
"source": [
"from h2o_ai_cloud import mlops_client"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 60,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Visit https://cloud-dev.h2o.ai/auth/get-platform-token to get your platform token\n"
]
}
],
"source": [
"mlops = mlops_client()"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": 63,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"27498d52-15c5-4a48-b2fa-f136bc90522c dai_e2e_test_migration\n",
"492b8ec5-5a48-4551-870c-edcc606fc5c3 dai_e2e_migration\n",
"cca74583-bf46-492b-b017-4070197f7ae3 test_project\n"
]
}
],
"source": [
"mlops_projects = mlops.storage.project.list_projects(body={}).project\n",
"for p in mlops_projects:\n",
" print(p.id, p.display_name)"
],
"metadata": {
"collapsed": false
}
},
{
"cell_type": "code",
"execution_count": null,
"outputs": [],
"source": [
"# Stop DAI instance\n",
"dai_instance.stop()"
],
"metadata": {
"collapsed": false
}
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.15"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
4 changes: 2 additions & 2 deletions README.md
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Expand Up @@ -8,8 +8,8 @@ These tutorials were explictly tested last in H2O AI Cloud v22.07.0 and python 3

```bash
pip install h2o_authn==0.1.1
pip install https://enterprise-steam.s3.amazonaws.com/release/1.8.12/python/h2osteam-1.8.12-py2.py3-none-any.whl
pip install https://s3.amazonaws.com/artifacts.h2o.ai/releases/ai/h2o/mlops/rel-0.56.1/2/h2o_mlops_client-0.56.1%2Bdd66f93.rel0.56.1.2-py2.py3-none-any.whl
pip install https://enterprise-steam.s3.amazonaws.com/release/1.8.14/python/h2osteam-1.8.14-py2.py3-none-any.whl
pip install https://s3.amazonaws.com/artifacts.h2o.ai/releases/ai/h2o/mlops/rel-0.57.2/2/h2o_mlops_client-0.57.2%2B7b19723.rel0.57.2.2-py2.py3-none-any.whl
pip install https://h2o-release.s3.amazonaws.com/h2o/rel-zumbo/2/Python/h2o-3.36.1.2-py2.py3-none-any.whl

```
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