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Author SHA1 Message Date
Andrew Ferlitsch 65d019d677 fix: IS_COLAB 2023-06-07 21:06:44 +00:00
Andrew FerlitschandGitHub a37d8c7f7d fix: import os 2023-06-07 13:23:08 -07:00
Andrew Ferlitsch 9fd2f326e1 fix: boilerplate reduction 79 2023-06-07 20:11:42 +00:00
@@ -168,56 +168,37 @@
},
"outputs": [],
"source": [
"import os\n",
"\n",
"# The Vertex AI Workbench Notebook product has specific requirements\n",
"IS_WORKBENCH_NOTEBOOK = os.getenv(\"DL_ANACONDA_HOME\") and not os.getenv(\"VIRTUAL_ENV\")\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",
"! pip3 install {USER_FLAG} --upgrade google-cloud-aiplatform -q"
"! pip3 install --upgrade --quiet google-cloud-aiplatform"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "oQhwq1iozAxh"
"id": "58707a750154"
},
"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."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "zo3YFZXLzCRJ"
"id": "f200f10a1da3"
},
"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)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "84cd83853240"
"id": "BF1j6f9HApxa"
},
"source": [
"## Before you begin\n",
@@ -228,64 +209,39 @@
"\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 $300 free credit towards your compute/storage costs.\n",
"\n",
"1. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
"2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
"\n",
"1. [Enable the Vertex AI, BigQuery, Compute Engine and Cloud Storage APIs](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com,bigquery,compute_component,storage_component).\n",
"3. [Enable the Vertex AI API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com).\n",
"\n",
"1. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk).\n",
"\n",
"1. Enter your project ID in the cell below. Then run the cell to make sure the\n",
"Cloud SDK uses the right project for all the commands in this notebook.\n",
"\n",
"**Note**: Jupyter runs lines prefixed with `!` as shell commands, and it interpolates Python variables prefixed with `$` into these commands."
"4. If you are running this notebook locally, install the [Cloud SDK](https://cloud.google.com/sdk)."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "project_id"
"id": "WReHDGG5g0XY"
},
"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)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "set_project_id"
"id": "oM1iC_MfAts1"
},
"outputs": [],
"source": [
"PROJECT_ID = \"[your-project-id]\" # @param {type:\"string\"}"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "autoset_project_id"
},
"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": "set_gcloud_project_id"
},
"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}"
]
},
{
@@ -294,32 +250,20 @@
"id": "region"
},
"source": [
"#### Region\n",
"#### Set the 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)."
"**Optional**: Update the 'REGION' variable to specify the region that you want to use. Learn more about [Vertex AI regions](https://cloud.google.com/vertex-ai/docs/general/locations)."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "qohAA9fJulvP"
"id": "nsN5NJKSu-GU"
},
"outputs": [],
"source": [
"REGION = \"[your-region]\" # @param {type: \"string\"}\n",
"\n",
"if REGION == \"[your-region]\":\n",
" REGION = \"us-central1\""
"REGION = \"us-central1\" # @param {type: \"string\"}"
]
},
{
@@ -335,7 +279,7 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": null,
"metadata": {
"id": "4e166d927e36"
},
@@ -356,117 +300,84 @@
{
"cell_type": "markdown",
"metadata": {
"id": "poKeKYG8ulvQ"
"id": "sBCra4QMA2wR"
},
"source": [
"### Authenticate your Google Cloud account\n",
"\n",
"**If you are using Vertex AI Workbench Notebooks**, your environment is already\n",
"authenticated. Skip this step."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "MIpJGzF9ulvQ"
},
"source": [
"**If you are using Colab**, run the cell below and follow the instructions\n",
"when prompted to authenticate your account via oAuth.\n",
"To authenticate your Google Cloud account, follow the instructions for your Jupyter environment:\n",
"\n",
"**Otherwise**, follow these steps:\n",
"**1. Vertex AI Workbench**\n",
"<br>You are already authenticated.\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."
"**2. Local JupyterLab instance**\n",
"<br>Uncomment and run the following code:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "Vh6KDXB5ulvQ"
"id": "254614fa0c46"
},
"outputs": [],
"source": [
"# 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",
"import os\n",
"import sys\n",
"\n",
"# If on Vertex AI Workbench, then don't execute this code\n",
"IS_COLAB = False\n",
"if not os.path.exists(\"/opt/deeplearning/metadata/env_version\") and not os.getenv(\n",
" \"DL_ANACONDA_HOME\"\n",
"):\n",
" if \"google.colab\" in sys.modules:\n",
" IS_COLAB = True\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 ''"
"# ! gcloud auth login"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "bucket:mbsdk"
"id": "ef21552ccea8"
},
"source": [
"**3. Colab**\n",
"<br>Uncomment and run the following code:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "603adbbf0532"
},
"outputs": [],
"source": [
"# from google.colab import auth\n",
"\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."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "zgPO1eR3CYjk"
},
"source": [
"### Create a Cloud Storage bucket\n",
"\n",
"**The following steps are required, regardless of your notebook environment.**\n",
"\n",
"When you initialize the Vertex SDK for Python, you specify a Cloud Storage staging bucket. The staging bucket is where all the data associated with your dataset and model resources are retained across sessions.\n",
"\n",
"Set the name of your Cloud Storage bucket below. Bucket names must be globally unique across all Google Cloud projects, including those outside of your organization."
"Create a storage bucket to store intermediate artifacts such as datasets."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "bucket"
"id": "MzGDU7TWdts_"
},
"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": "autoset_bucket"
},
"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 = f\"gs://your-bucket-name-{PROJECT_ID}-unique\" # @param {type:\"string\"}"
]
},
{
@@ -482,31 +393,11 @@
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "Moosy2rOulvR"
"id": "NIq7R4HZCfIc"
},
"outputs": [],
"source": [
"! gsutil mb -l $REGION $BUCKET_URI"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "validate_bucket"
},
"source": [
"Finally, validate access to your Cloud Storage bucket by examining its contents:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "56irx2CvulvS"
},
"outputs": [],
"source": [
"! gsutil ls -al $BUCKET_URI"
"! gsutil mb -l $REGION -p $PROJECT_ID $BUCKET_URI"
]
},
{
@@ -529,6 +420,8 @@
},
"outputs": [],
"source": [
"import os\n",
"\n",
"import google.cloud.aiplatform as aip"
]
},
@@ -1380,6 +1273,9 @@
},
"outputs": [],
"source": [
"import sys\n",
"\n",
"IS_COLAB = \"google.colab\" in sys.modules\n",
"if not IS_COLAB:\n",
" ! docker build custom -t $TRAIN_IMAGE\n",
"else:\n",