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sdk-metric-parameter-tracking-for-custom-jobs (#1242)

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**REQUIRED:** Add a summary of your PR here, typically including why the change is needed and what was changed. Include any design alternatives for discussion purposes.

<br>

1. Boilerplate changes.
2. Added code for deleting experiment otherwise its throwing experiment name already exist.
<br><br><br>

**REQUIRED:** Fill out the below checklists or remove if irrelevant
1. If you are opening a PR for `Official Notebooks` under the [notebooks/official](https://togithub.com/GoogleCloudPlatform/vertex-ai-samples/tree/main/notebooks/official) folder, follow this mandatory checklist:
- [X] Use the [notebook template](https://togithub.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/notebook_template.ipynb) as a starting point.
- [X] Follow the style and grammar rules outlined in the above notebook template.
- [X] Verify the notebook runs successfully in Colab since the automated tests cannot guarantee this even when it passes.
- [X] Passes all the required automated checks. You can locally test for formatting and linting with these [instructions](https://togithub.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/CONTRIBUTING.md#code-quality-checks).
- [ ] You have consulted with a tech writer to see if tech writer review is necessary. If so, the notebook has been reviewed by a tech writer, and they have approved it.
- [X] This notebook has been added to the [CODEOWNERS](https://togithub.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/CODEOWNERS) file under the `Official Notebooks` section, pointing to the author or the author's team.
- [X] The Jupyter notebook cleans up any artifacts it has created (datasets, ML models, endpoints, etc) so as not to eat up unnecessary resources.

<br>
This commit is contained in:
uday kumar
2022-11-18 17:04:13 +00:00
committed by GitHub
parent 18440f5c0c
commit db96de8266
1 changed files with 81 additions and 297 deletions
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notebooks/official/ml_metadata/sdk-metric-parameter-tracking-for-custom-jobs.ipynb
+81 -297
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@@ -117,64 +117,15 @@
"to generate a cost estimate based on your projected usage."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ze4-nDLfK4pw"
},
"source": [
"### Set up your local development environment\n",
"\n",
"**If you are using Colab or Vertex AI Workbench**, your environment already meets\n",
"all the requirements to run this notebook. You can skip this step."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "gCuSR8GkAgzl"
},
"source": [
"**Otherwise**, make sure your environment meets this notebook's requirements.\n",
"You need the following:\n",
"\n",
"* The Google Cloud SDK\n",
"* Git\n",
"* Python 3\n",
"* virtualenv\n",
"* Jupyter notebook running in a virtual environment with Python 3\n",
"\n",
"The Google Cloud guide to [Setting up a Python development\n",
"environment](https://cloud.google.com/python/setup) and the [Jupyter\n",
"installation guide](https://jupyter.org/install) provide detailed instructions\n",
"for meeting these requirements. The following steps provide a condensed set of\n",
"instructions:\n",
"\n",
"1. [Install and initialize the Cloud SDK.](https://cloud.google.com/sdk/docs/)\n",
"\n",
"1. [Install Python 3.](https://cloud.google.com/python/setup#installing_python)\n",
"\n",
"1. [Install\n",
" virtualenv](https://cloud.google.com/python/setup#installing_and_using_virtualenv)\n",
" and create a virtual environment that uses Python 3. Activate the virtual environment.\n",
"\n",
"1. To install Jupyter, run `pip install jupyter` on the\n",
"command-line in a terminal shell.\n",
"\n",
"1. To launch Jupyter, run `jupyter notebook` on the command-line in a terminal shell.\n",
"\n",
"1. Open this notebook in the Jupyter Notebook Dashboard."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "i7EUnXsZhAGF"
},
"source": [
"### Install additional packages\n",
"### Installation\n",
"\n",
"Install additional package dependencies not installed in your notebook environment."
"Install the packages required for executing this notebook."
]
},
{
@@ -185,23 +136,9 @@
},
"outputs": [],
"source": [
"import os\n",
"\n",
"# The Vertex AI Workbench Notebook product has specific requirements\n",
"IS_WORKBENCH_NOTEBOOK = os.getenv(\"DL_ANACONDA_HOME\")\n",
"IS_USER_MANAGED_WORKBENCH_NOTEBOOK = os.path.exists(\n",
" \"/opt/deeplearning/metadata/env_version\"\n",
")\n",
"\n",
"# Vertex AI Notebook requires dependencies to be installed with '--user'\n",
"USER_FLAG = \"\"\n",
"if IS_WORKBENCH_NOTEBOOK:\n",
" USER_FLAG = \"--user\"\n",
"\n",
"\n",
"! pip3 install -U tensorflow $USER_FLAG\n",
"! python3 -m pip3 install {USER_FLAG} google-cloud-aiplatform --upgrade\n",
"! pip3 install scikit-learn {USER_FLAG}"
"! pip3 install --upgrade tensorflow \\\n",
" google-cloud-aiplatform \\\n",
" scikit-learn -q"
]
},
{
@@ -210,9 +147,7 @@
"id": "hhq5zEbGg0XX"
},
"source": [
"### Restart the kernel\n",
"\n",
"After you install the additional packages, you need to restart the notebook kernel so it can find the packages."
"### Colab only: Uncomment the following cell to restart the kernel."
]
},
{
@@ -223,15 +158,11 @@
},
"outputs": [],
"source": [
"# Automatically restart kernel after installs\n",
"import os\n",
"# Automatically restart kernel after installs so that your environment can access the new packages\n",
"# import IPython\n",
"\n",
"if not os.getenv(\"IS_TESTING\"):\n",
" # Automatically restart kernel after installs\n",
" import IPython\n",
"\n",
" app = IPython.Application.instance()\n",
" app.kernel.do_shutdown(True)"
"# app = IPython.Application.instance()\n",
"# app.kernel.do_shutdown(True)"
]
},
{
@@ -240,46 +171,21 @@
"id": "lWEdiXsJg0XY"
},
"source": [
"## Before you begin\n",
"\n",
"### Select a GPU runtime\n",
"\n",
"**Make sure you're running this notebook in a GPU runtime if you have that option. In Colab, select \"Runtime --> Change runtime type > GPU\"**"
"## Before you begin"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "BF1j6f9HApxa"
},
"source": [
"### Set up your Google Cloud project\n",
"\n",
"**The following steps are required, regardless of your notebook environment.**\n",
"\n",
"1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
"\n",
"1. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
"\n",
"1. [Enable the Vertex AI API and Compute Engine API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com,compute_component).\n",
"\n",
"1. If you are running this notebook locally, you will need to install the [Cloud SDK](https://cloud.google.com/sdk).\n",
"\n",
"1. Enter your project ID in the cell below. Then run the cell to make sure the\n",
"Cloud SDK uses the right project for all the commands in this notebook.\n",
"\n",
"**Note**: Jupyter runs lines prefixed with `!` as shell commands, and it interpolates Python variables prefixed with `$` into these commands."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "WReHDGG5g0XY"
"id": "8bc8a29f9001"
},
"source": [
"#### Set your project ID\n",
"\n",
"**If you don't know your project ID**, you may be able to get your project ID using `gcloud`."
"**If you don't know your project ID**, try the following:\n",
"* Run `gcloud config list`.\n",
"* Run `gcloud projects list`.\n",
"* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
]
},
{
@@ -290,33 +196,10 @@
},
"outputs": [],
"source": [
"PROJECT_ID = \"[your-project-id]\" # @param {type:\"string\"}"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "oM1iC_MfAts1"
},
"outputs": [],
"source": [
"if PROJECT_ID == \"\" or PROJECT_ID is None or PROJECT_ID == \"[your-project-id]\":\n",
" # Get your GCP project id from gcloud\n",
" shell_output = ! gcloud config list --format 'value(core.project)' 2>/dev/null\n",
" PROJECT_ID = shell_output[0]\n",
" print(\"Project ID:\", PROJECT_ID)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "TL9QIaVd9hvm"
},
"outputs": [],
"source": [
"!gcloud config set project $PROJECT_ID"
"PROJECT_ID = \"[your-project-id]\" # @param {type:\"string\"}\n",
"\n",
"# Set the project id\n",
"! gcloud config set project {PROJECT_ID}"
]
},
{
@@ -327,16 +210,7 @@
"source": [
"#### Region\n",
"\n",
"You can also change the `REGION` variable, which is used for operations\n",
"throughout the rest of this notebook. Below are regions supported for Vertex AI. We recommend that you choose the region closest to you.\n",
"\n",
"- Americas: `us-central1`\n",
"- Europe: `europe-west4`\n",
"- Asia Pacific: `asia-east1`\n",
"\n",
"You may not use a multi-regional bucket for training with Vertex AI. Not all regions provide support for all Vertex AI services.\n",
"\n",
"Learn more about [Vertex AI regions](https://cloud.google.com/vertex-ai/docs/general/locations)."
"You can also change the `REGION` variable used by Vertex AI. Learn more about [Vertex AI regions](https://cloud.google.com/vertex-ai/docs/general/locations)."
]
},
{
@@ -347,41 +221,7 @@
},
"outputs": [],
"source": [
"REGION = \"[your-region]\" # @param {type: \"string\"}\n",
"\n",
"if REGION == \"[your-region]\":\n",
" REGION = \"us-central1\""
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "06571eb4063b"
},
"source": [
"#### 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 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": "697568e92bd6"
},
"outputs": [],
"source": [
"import random\n",
"import string\n",
"\n",
"\n",
"# Generate a uuid of length 8\n",
"def generate_uuid():\n",
" return \"\".join(random.choices(string.ascii_lowercase + string.digits, k=8))\n",
"\n",
"\n",
"UUID = generate_uuid()"
"REGION = \"us-central1\" # @param {type: \"string\"}"
]
},
{
@@ -392,8 +232,7 @@
"source": [
"### Authenticate your Google Cloud account\n",
"\n",
"**If you are using Vertex AI Workbench**, your environment is already\n",
"authenticated. Skip this step."
"Depending on your Jupyter environment, you may have to manually authenticate. Follow the relevant instructions below."
]
},
{
@@ -402,28 +241,37 @@
"id": "sBCra4QMA2wR"
},
"source": [
"**If you are using Colab**, run the cell below and follow the instructions\n",
"when prompted to authenticate your account via oAuth.\n",
"\n",
"**Otherwise**, follow these steps:\n",
"\n",
"1. In the Cloud Console, go to the [**Create service account key**\n",
" page](https://console.cloud.google.com/apis/credentials/serviceaccountkey).\n",
"\n",
"2. Click **Create service account**.\n",
"\n",
"3. In the **Service account name** field, enter a name, and\n",
" click **Create**.\n",
"\n",
"4. In the **Grant this service account access to project** section, click the **Role** drop-down list. Type \"Vertex AI\"\n",
"into the filter box, and select\n",
" **Vertex AI Administrator**. Type \"Storage Object Admin\" into the filter box, and select **Storage Object Admin**.\n",
"\n",
"5. Click *Create*. A JSON file that contains your key downloads to your\n",
"local environment.\n",
"\n",
"6. Enter the path to your service account key as the\n",
"`GOOGLE_APPLICATION_CREDENTIALS` variable in the cell below and run the cell."
"**1. Vertex AI Workbench**\n",
"* Do nothing as you are already authenticated."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ad1138a125ea"
},
"source": [
"**2. Local JupyterLab instance, uncomment and run:**"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "ce6043da7b33"
},
"outputs": [],
"source": [
"# ! gcloud auth login"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "0367eac06a10"
},
"source": [
"**3. Colab, uncomment and run:**"
]
},
{
@@ -434,26 +282,18 @@
},
"outputs": [],
"source": [
"import os\n",
"import sys\n",
"\n",
"# If you are running this notebook in Colab, run this cell and follow the\n",
"# instructions to authenticate your GCP account. This provides access to your\n",
"# Cloud Storage bucket and lets you submit training jobs and prediction\n",
"# requests.\n",
"\n",
"# If on Google Cloud Notebooks, then don't execute this code\n",
"if not os.path.exists(\"/opt/deeplearning/metadata/env_version\"):\n",
" if \"google.colab\" in sys.modules:\n",
" from google.colab import auth as google_auth\n",
"\n",
" google_auth.authenticate_user()\n",
"\n",
" # If you are running this notebook locally, replace the string below with the\n",
" # path to your service account key and run this cell to authenticate your GCP\n",
" # account.\n",
" elif not os.getenv(\"IS_TESTING\"):\n",
" %env GOOGLE_APPLICATION_CREDENTIALS ''"
"# from google.colab import auth\n",
"# auth.authenticate_user()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "c13224697bfb"
},
"source": [
"**4. Service account or other**\n",
"* See how to grant Cloud Storage permissions to your service account at https://cloud.google.com/storage/docs/gsutil/commands/iam#ch-examples."
]
},
{
@@ -464,18 +304,7 @@
"source": [
"### Create a Cloud Storage bucket\n",
"\n",
"**The following steps are required, regardless of your notebook environment.**\n",
"\n",
"\n",
"When you submit a training job using the Vertex AI SDK, you upload a Python package\n",
"containing your training code to a Cloud Storage bucket. Vertex AI runs\n",
"the code from this package. In this tutorial, Vertex AI also saves the\n",
"trained model that results from your job in the same bucket. Using this model artifact, you can then\n",
"create Vertex AI model and endpoint resources in order to serve\n",
"online predictions.\n",
"\n",
"Set the name of your Cloud Storage bucket below. It must be unique across all\n",
"Cloud Storage buckets."
"Create a storage bucket to store intermediate artifacts such as datasets."
]
},
{
@@ -486,21 +315,7 @@
},
"outputs": [],
"source": [
"BUCKET_NAME = \"[your-bucket-name]\" # @param {type:\"string\"}\n",
"BUCKET_URI = f\"gs://{BUCKET_NAME}\""
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "cf221059d072"
},
"outputs": [],
"source": [
"if BUCKET_NAME == \"\" or BUCKET_NAME is None or BUCKET_NAME == \"[your-bucket-name]\":\n",
" BUCKET_NAME = PROJECT_ID + \"aip-\" + UUID\n",
" BUCKET_URI = f\"gs://{BUCKET_NAME}\""
"BUCKET_URI = \"gs://your-bucket-name-unique\" # @param {type:\"string\"}"
]
},
{
@@ -520,27 +335,7 @@
},
"outputs": [],
"source": [
"! gsutil mb -l $REGION $BUCKET_URI"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ucvCsknMCims"
},
"source": [
"Finally, validate access to your Cloud Storage bucket by examining its contents:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "vhOb7YnwClBb"
},
"outputs": [],
"source": [
"! gsutil ls -al $BUCKET_URI"
"! gsutil mb -l $REGION -p $PROJECT_ID $BUCKET_URI"
]
},
{
@@ -569,6 +364,8 @@
},
"outputs": [],
"source": [
"import os\n",
"\n",
"import pandas as pd\n",
"from google.cloud import aiplatform\n",
"from sklearn.metrics import mean_absolute_error, mean_squared_error\n",
@@ -601,28 +398,7 @@
},
"outputs": [],
"source": [
"EXPERIMENT_NAME = \"\" # @param {type:\"string\"}"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "jWQLXXNVN4Lv"
},
"source": [
"If EXEPERIMENT_NAME is not set, set a default one below:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "Q1QInYWOKsmo"
},
"outputs": [],
"source": [
"if EXPERIMENT_NAME == \"\" or EXPERIMENT_NAME is None:\n",
" EXPERIMENT_NAME = \"my-experiment-\" + UUID"
"EXPERIMENT_NAME = \"my-experiment-unique\""
]
},
{
@@ -812,7 +588,9 @@
},
"outputs": [],
"source": [
"aiplatform.start_run(\"custom-training-run-1\") # Change this to your desired run name\n",
"aiplatform.start_run(\n",
" \"custom-training-run-unique\"\n",
") # Change this to your desired run name\n",
"parameters = {\"epochs\": 10, \"num_units\": 64}\n",
"aiplatform.log_params(parameters)\n",
"\n",
@@ -1049,6 +827,12 @@
"# Delete dataset\n",
"ds.delete()\n",
"\n",
"# Delete experiment\n",
"experiment = aiplatform.Experiment(\n",
" experiment_name=EXPERIMENT_NAME, project=PROJECT_ID, location=REGION\n",
")\n",
"experiment.delete()\n",
"\n",
"# Delete the training job\n",
"job.delete()\n",
"\n",