diff --git a/notebooks/community/model_garden/model_garden_mediapipe_object_detection.ipynb b/notebooks/community/model_garden/model_garden_mediapipe_object_detection.ipynb index ac85d0d9b..0ec1befc4 100644 --- a/notebooks/community/model_garden/model_garden_mediapipe_object_detection.ipynb +++ b/notebooks/community/model_garden/model_garden_mediapipe_object_detection.ipynb @@ -4,11 +4,12 @@ "cell_type": "code", "execution_count": null, "metadata": { + "cellView": "form", "id": "ur8xi4C7S06n" }, "outputs": [], "source": [ - "# Copyright 2023 Google LLC\n", + "# Copyright 2024 Google LLC\n", "#\n", "# Licensed under the Apache License, Version 2.0 (the \"License\");\n", "# you may not use this file except in compliance with the License.\n", @@ -31,39 +32,18 @@ "source": [ "# Vertex AI Model Garden MediaPipe with object detection\n", "\n", - "\n", - "
\n", - " \n", - " \"Colab Run in Colab\n", + "\n", + " \n", - "\n", - " \n", - " \n", - "
\n", + " \n", + " \"Google
Run in Colab Enterprise\n", " \n", " 		\n", + " \n", " \n", - " \"GitHub\n", - " View on GitHub\n", - " \n", - " \n", - " \n", - " \"Vertex\n", - "Open in Vertex AI Workbench\n", + " \"GitHub
View on GitHub\n", " \n", "
" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "dwGLvtIeECLK" - }, - "source": [ - "**_NOTE_**: This notebook has been tested in the following environment:\n", - "\n", - "* Python version = 3.9\n", - "\n", - "**NOTE**: The checkpoint and the dataset linked in this Colab are not owned or distributed by Google, and are made available by third parties. Please review the terms and conditions made available by the third parties before using the checkpoint and data." + "
" ] }, { @@ -92,11 +72,7 @@ "* Vertex AI\n", "* Cloud Storage\n", "\n", - "Learn about [Vertex AI\n", - "pricing](https://cloud.google.com/vertex-ai/pricing) and [Cloud Storage\n", - "pricing](https://cloud.google.com/storage/pricing), and use the [Pricing\n", - "Calculator](https://cloud.google.com/products/calculator/)\n", - "to generate a cost estimate based on your projected usage." + "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing), [Cloud Storage pricing](https://cloud.google.com/storage/pricing), and use the [Pricing Calculator](https://cloud.google.com/products/calculator/) to generate a cost estimate based on your projected usage." ] }, { @@ -108,87 +84,109 @@ "## Before you begin" ] }, - { - "cell_type": "markdown", - "metadata": { - "id": "z__i0w0lCAsW" - }, - "source": [ - "### Colab only\n", - "Run the following commands to install dependencies and to authenticate with Google Cloud if running on Colab." - ] - }, { "cell_type": "code", "execution_count": null, "metadata": { + "cellView": "form", "id": "Jvqs-ehKlaYh" }, "outputs": [], "source": [ + "# @markdown 1. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n", + "\n", + "# @markdown 2. For finetuning, **[click here](https://console.cloud.google.com/iam-admin/quotas?location=us-central1&metric=aiplatform.googleapis.com%2Frestricted_image_training_nvidia_a100_80gb_gpus)** to check if your project already has the required 8 Nvidia A100 80 GB GPUs in the us-central1 region. If yes, then run this notebook in the us-central1 region. If you do not have 8 Nvidia A100 80 GPUs or have more GPU requirements than this, then schedule your job with Nvidia H100 GPUs via Dynamic Workload Scheduler using [these instructions](https://cloud.google.com/vertex-ai/docs/training/schedule-jobs-dws). For Dynamic Workload Scheduler, check the [us-central1](https://console.cloud.google.com/iam-admin/quotas?location=us-central1&metric=aiplatform.googleapis.com%2Fcustom_model_training_preemptible_nvidia_h100_gpus) or [europe-west4](https://console.cloud.google.com/iam-admin/quotas?location=europe-west4&metric=aiplatform.googleapis.com%2Fcustom_model_training_preemptible_nvidia_h100_gpus) quota for Nvidia H100 GPUs. If you do not have enough GPUs, then you can follow [these instructions](https://cloud.google.com/docs/quotas/view-manage#viewing_your_quota_console) to request quota.\n", + "\n", + "# @markdown 3. For serving, **[click here](https://console.cloud.google.com/iam-admin/quotas?location=us-central1&metric=aiplatform.googleapis.com%2Fcustom_model_serving_nvidia_l4_gpus)** to check if your project already has the required 1 L4 GPU in the us-central1 region. If yes, then run this notebook in the us-central1 region. If you need more L4 GPUs for your project, then you can follow [these instructions](https://cloud.google.com/docs/quotas/view-manage#viewing_your_quota_console) to request more. Alternatively, if you want to run predictions with A100 80GB or H100 GPUs, we recommend using the regions listed below. **NOTE:** Make sure you have associated quota in selected regions. Click the links to see your current quota for each GPU type: [Nvidia A100 80GB](https://console.cloud.google.com/iam-admin/quotas?metric=aiplatform.googleapis.com%2Fcustom_model_serving_nvidia_a100_80gb_gpus), [Nvidia H100 80GB](https://console.cloud.google.com/iam-admin/quotas?metric=aiplatform.googleapis.com%2Fcustom_model_serving_nvidia_h100_gpus).\n", + "\n", + "# @markdown > | Machine Type | Accelerator Type | Recommended Regions |\n", + "# @markdown | ----------- | ----------- | ----------- |\n", + "# @markdown | a2-ultragpu-1g | 1 NVIDIA_A100_80GB | us-central1, us-east4, europe-west4, asia-southeast1, us-east4 |\n", + "# @markdown | a3-highgpu-2g | 2 NVIDIA_H100_80GB | us-west1, asia-southeast1, europe-west4 |\n", + "# @markdown | a3-highgpu-4g | 4 NVIDIA_H100_80GB | us-west1, asia-southeast1, europe-west4 |\n", + "# @markdown | a3-highgpu-8g | 8 NVIDIA_H100_80GB | us-central1, us-east5, europe-west4, us-west1, asia-southeast1 |\n", + "\n", + "# @markdown 4. **[Optional]** [Create a Cloud Storage bucket](https://cloud.google.com/storage/docs/creating-buckets) for storing experiment outputs. Set the BUCKET_URI for the experiment environment. The specified Cloud Storage bucket (`BUCKET_URI`) should be located in the same region as where the notebook was launched. Note that a multi-region bucket (eg. \"us\") is not considered a match for a single region covered by the multi-region range (eg. \"us-central1\"). If not set, a unique GCS bucket will be created instead.\n", + "\n", + "BUCKET_URI = \"gs://\" # @param {type:\"string\"}\n", + "\n", + "# @markdown 5. **[Optional]** Set region. If not set, the region will be set automatically according to Colab Enterprise environment.\n", + "\n", + "REGION = \"\" # @param {type:\"string\"}\n", + "\n", "! pip3 install --upgrade pip\n", + "! git clone https://github.com/GoogleCloudPlatform/vertex-ai-samples.git\n", "\n", - "import sys\n", + "import datetime\n", + "import importlib\n", + "import json\n", + "import os\n", + "import uuid\n", "\n", - "if \"google.colab\" in sys.modules:\n", - " ! pip3 install --upgrade google-cloud-aiplatform\n", + "import tensorflow\n", + "from google.cloud import aiplatform\n", "\n", - " # Automatically restart kernel after installs\n", - " import IPython\n", + "common_util = importlib.import_module(\n", + " \"vertex-ai-samples.community-content.vertex_model_garden.model_oss.notebook_util.common_util\"\n", + ")\n", "\n", - " app = IPython.Application.instance()\n", - " app.kernel.do_shutdown(True)\n", + "models, endpoints = {}, {}\n", "\n", - " from google.colab import auth as google_auth\n", + "# Get the default cloud project id.\n", + "PROJECT_ID = os.environ[\"GOOGLE_CLOUD_PROJECT\"]\n", "\n", - " google_auth.authenticate_user()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "WReHDGG5g0XY" - }, - "source": [ - "#### Set your project ID\n", + "# Get the default region for launching jobs.\n", + "if not REGION:\n", + " REGION = os.environ[\"GOOGLE_CLOUD_REGION\"]\n", "\n", - "**If you don't know your project ID**, see the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "oM1iC_MfAts1" - }, - "outputs": [], - "source": [ - "PROJECT_ID = \"[your-project-id]\" # @param {type:\"string\"}\n", + "# Enable the Vertex AI API and Compute Engine API, if not already.\n", + "print(\"Enabling Vertex AI API and Compute Engine API.\")\n", + "! gcloud services enable aiplatform.googleapis.com compute.googleapis.com\n", + "\n", + "# Cloud Storage bucket for storing the experiment artifacts.\n", + "# A unique GCS bucket will be created for the purpose of this notebook. If you\n", + "# prefer using your own GCS bucket, change the value yourself below.\n", + "now = datetime.datetime.now().strftime(\"%Y%m%d%H%M%S\")\n", + "BUCKET_NAME = \"/\".join(BUCKET_URI.split(\"/\")[:3])\n", + "\n", + "if BUCKET_URI is None or BUCKET_URI.strip() == \"\" or BUCKET_URI == \"gs://\":\n", + " BUCKET_URI = f\"gs://{PROJECT_ID}-tmp-{now}-{str(uuid.uuid4())[:4]}\"\n", + " BUCKET_NAME = \"/\".join(BUCKET_URI.split(\"/\")[:3])\n", + " ! gsutil mb -l {REGION} {BUCKET_URI}\n", + "else:\n", + " assert BUCKET_URI.startswith(\"gs://\"), \"BUCKET_URI must start with `gs://`.\"\n", + " shell_output = ! gsutil ls -Lb {BUCKET_NAME} | grep \"Location constraint:\" | sed \"s/Location constraint://\"\n", + " bucket_region = shell_output[0].strip().lower()\n", + " if bucket_region != REGION:\n", + " raise ValueError(\n", + " \"Bucket region %s is different from notebook region %s\"\n", + " % (bucket_region, REGION)\n", + " )\n", + "print(f\"Using this GCS Bucket: {BUCKET_URI}\")\n", + "\n", + "STAGING_BUCKET = os.path.join(BUCKET_URI, \"temporal\")\n", + "MODEL_BUCKET = os.path.join(BUCKET_URI, \"mediapipe_object_detection\")\n", + "\n", + "\n", + "# Initialize Vertex AI API.\n", + "print(\"Initializing Vertex AI API.\")\n", + "aiplatform.init(project=PROJECT_ID, location=REGION, staging_bucket=STAGING_BUCKET)\n", + "\n", + "# Gets the default SERVICE_ACCOUNT.\n", + "shell_output = ! gcloud projects describe $PROJECT_ID\n", + "project_number = shell_output[-1].split(\":\")[1].strip().replace(\"'\", \"\")\n", + "SERVICE_ACCOUNT = f\"{project_number}-compute@developer.gserviceaccount.com\"\n", + "print(\"Using this default Service Account:\", SERVICE_ACCOUNT)\n", + "\n", + "\n", + "# Provision permissions to the SERVICE_ACCOUNT with the GCS bucket\n", + "! gsutil iam ch serviceAccount:{SERVICE_ACCOUNT}:roles/storage.admin $BUCKET_NAME\n", + "\n", + "! gcloud config set project $PROJECT_ID\n", + "! gcloud projects add-iam-policy-binding --no-user-output-enabled {PROJECT_ID} --member=serviceAccount:{SERVICE_ACCOUNT} --role=\"roles/storage.admin\"\n", + "! gcloud projects add-iam-policy-binding --no-user-output-enabled {PROJECT_ID} --member=serviceAccount:{SERVICE_ACCOUNT} --role=\"roles/aiplatform.user\"\n", "\n", - "# Set the project id\n", - "! gcloud config set project {PROJECT_ID}" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "region" - }, - "source": [ - "#### Region\n", "\n", - "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)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "tTy1gX11kCJY" - }, - "outputs": [], - "source": [ - "REGION = \"us-central1\" # @param {type: \"string\"}\n", "REGION_PREFIX = REGION.split(\"-\")[0]\n", "assert REGION_PREFIX in (\n", " \"us\",\n", @@ -197,73 +195,6 @@ "), f'{REGION} is not supported. It must be prefixed by \"us\", \"asia\", or \"europe\".'" ] }, - { - "cell_type": "markdown", - "metadata": { - "id": "zgPO1eR3CYjk" - }, - "source": [ - "### Create a Cloud Storage bucket\n", - "\n", - "Create a storage bucket to store intermediate artifacts such as datasets." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "MzGDU7TWdts_" - }, - "outputs": [], - "source": [ - "BUCKET_URI = f\"gs://your-bucket-name-{PROJECT_ID}-unique\" # @param {type:\"string\"}" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "-EcIXiGsCePi" - }, - "source": [ - "**Only if your bucket doesn't already exist**: Run the following cell to create your Cloud Storage bucket." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "NIq7R4HZCfIc" - }, - "outputs": [], - "source": [ - "! gsutil mb -l {REGION} -p {PROJECT_ID} {BUCKET_URI}" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "960505627ddf" - }, - "source": [ - "### Import libraries" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "PyQmSRbKA8r-" - }, - "outputs": [], - "source": [ - "import json\n", - "import os\n", - "from datetime import datetime\n", - "\n", - "import tensorflow\n", - "from google.cloud import aiplatform" - ] - }, { "cell_type": "markdown", "metadata": { @@ -279,14 +210,11 @@ "cell_type": "code", "execution_count": null, "metadata": { + "cellView": "form", "id": "9wExiMUxFk91" }, "outputs": [], "source": [ - "now = datetime.now().strftime(\"%Y%m%d-%H%M%S\")\n", - "\n", - "STAGING_BUCKET = os.path.join(BUCKET_URI, \"temp/%s\" % now)\n", - "\n", "EVALUATION_RESULT_OUTPUT_DIRECTORY = os.path.join(STAGING_BUCKET, \"evaluation\")\n", "EVALUATION_RESULT_OUTPUT_FILE = os.path.join(\n", " EVALUATION_RESULT_OUTPUT_DIRECTORY, \"evaluation.json\"\n", @@ -295,9 +223,7 @@ "EXPORTED_MODEL_OUTPUT_DIRECTORY = os.path.join(STAGING_BUCKET, \"model\")\n", "EXPORTED_MODEL_OUTPUT_FILE = os.path.join(\n", " EXPORTED_MODEL_OUTPUT_DIRECTORY, \"model.tflite\"\n", - ")\n", - "\n", - "aiplatform.init(project=PROJECT_ID, location=REGION, staging_bucket=STAGING_BUCKET)" + ")" ] }, { @@ -313,6 +239,7 @@ "cell_type": "code", "execution_count": null, "metadata": { + "cellView": "form", "id": "riG_qUokg0XZ" }, "outputs": [], @@ -336,7 +263,7 @@ { "cell_type": "markdown", "metadata": { - "id": "zgPO1eR3CYjk" + "id": "HxFxTzLCh7Y_" }, "source": [ "### Prepare input data for training\n", @@ -427,6 +354,7 @@ "cell_type": "code", "execution_count": null, "metadata": { + "cellView": "form", "id": "IndQ_m6ddUEM" }, "outputs": [], @@ -457,6 +385,7 @@ "cell_type": "code", "execution_count": null, "metadata": { + "cellView": "form", "id": "um_XKbmpTaHx" }, "outputs": [], @@ -508,6 +437,7 @@ "cell_type": "code", "execution_count": null, "metadata": { + "cellView": "form", "id": "aec22792ee84" }, "outputs": [], @@ -556,6 +486,15 @@ " }\n", "]\n", "\n", + "# Check quota.\n", + "common_util.check_quota(\n", + " project_id=PROJECT_ID,\n", + " region=REGION,\n", + " accelerator_type=TRAIN_ACCELERATOR_TYPE,\n", + " accelerator_count=1,\n", + " is_for_training=True,\n", + ")\n", + "\n", "training_job = aiplatform.CustomJob(\n", " display_name=TRAINING_JOB_DISPLAY_NAME,\n", " project=PROJECT_ID,\n", @@ -590,6 +529,7 @@ "cell_type": "code", "execution_count": null, "metadata": { + "cellView": "form", "id": "09Rz1AYspK19" }, "outputs": [], @@ -625,6 +565,7 @@ "cell_type": "code", "execution_count": null, "metadata": { + "cellView": "form", "id": "NYuQowyZEtxK" }, "outputs": [], @@ -635,6 +576,7 @@ "def copy_model(model_source, model_dest):\n", " ! gsutil cp {model_source} {model_dest}\n", "\n", + "\n", "copy_model(EXPORTED_MODEL_OUTPUT_FILE, \"object_detection_model.tflite\")\n", "\n", "if \"google.colab\" in sys.modules:\n", @@ -656,15 +598,31 @@ "cell_type": "code", "execution_count": null, "metadata": { + "cellView": "form", "id": "Ax6vQVZhp9pR" }, "outputs": [], "source": [ + "# @title Delete the model and endpoint\n", + "\n", "# Delete training data and jobs.\n", "if training_job.list(filter=f'display_name=\"{TRAINING_JOB_DISPLAY_NAME}\"'):\n", " training_job.delete()\n", "\n", - "!gsutil rm -r {STAGING_BUCKET}" + "# @markdown Delete the experiment models and endpoints to recycle the resources\n", + "# @markdown and avoid unnecessary continuous charges that may incur.\n", + "\n", + "# Undeploy model and delete endpoint.\n", + "for endpoint in endpoints.values():\n", + " endpoint.delete(force=True)\n", + "\n", + "# Delete models.\n", + "for model in models.values():\n", + " model.delete()\n", + "\n", + "delete_bucket = False # @param {type:\"boolean\"}\n", + "if delete_bucket:\n", + " ! gsutil -m rm -r $BUCKET_NAME" ] } ],