fix: rename UJ10

pin kfp in google_cloud_pipeline_components_automl_text (#1748 )
pin kfp in google_cloud_pipeline_components_automl_images (#1746 )
2026-09-26 22:51:56 +00:00 · 2023-04-19 23:51:55 +00:00 · 2023-04-19 23:01:21 +00:00 · 2023-04-19 19:29:50 +00:00 · 2023-04-19 18:37:16 +00:00 · 2023-04-19 18:14:04 +00:00
25 changed files with 2779 additions and 77 deletions
@@ -55,3 +55,4 @@
 /notebooks/community/model_garden/model_garden_pytorch_clip.ipynb @xiangxu-google
 /notebooks/community/model_garden/model_garden_pytorch_owlvit.ipynb @xiangxu-google
 /notebooks/community/model_garden/model_garden_pytorch_layoutml_document_qa.ipynb @xiangxu-google
+/notebooks/community/model_garden/model_garden_pytorch_blip2.ipynb @xiangxu-google
@@ -0,0 +1,468 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "7d9bbf86da5e"
+      },
+      "outputs": [],
+      "source": [
+        "# Copyright 2023 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",
+        "# You may obtain a copy of the License at\n",
+        "#\n",
+        "#     https://www.apache.org/licenses/LICENSE-2.0\n",
+        "#\n",
+        "# Unless required by applicable law or agreed to in writing, software\n",
+        "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+        "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+        "# See the License for the specific language governing permissions and\n",
+        "# limitations under the License."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "2bd716bf3e39"
+      },
+      "source": [
+        "# Vertex AI Model Garden - BLIP2\n",
+        "\n",
+        "<table align=\"left\">\n",
+        "  <td>\n",
+        "    <a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/community/model_garden/model_garden_pytorch_blip2.ipynb\">\n",
+        "      <img src=\"https://cloud.google.com/ml-engine/images/colab-logo-32px.png\" alt=\"Colab logo\"> Run in Colab\n",
+        "    </a>\n",
+        "  </td>\n",
+        "  <td>\n",
+        "    <a href=\"https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/community/model_garden/model_garden_pytorch_blip2.ipynb\">\n",
+        "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
+        "      View on GitHub\n",
+        "    </a>\n",
+        "  </td>\n",
+        "  <td>\n",
+        "    <a href=\"https://console.cloud.google.com/vertex-ai/notebooks/deploy-notebook?download_url=https://raw.githubusercontent.com/GoogleCloudPlatform/vertex-ai-samples/main/notebooks/community/model_garden/model_garden_pytorch_blip2.ipynb\">\n",
+        "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
+        "Open in Vertex AI Workbench\n",
+        "    </a>\n",
+        "    (a Python-3 CPU notebook is recommended)\n",
+        "  </td>\n",
+        "</table>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "d8cd12648da4"
+      },
+      "source": [
+        "## Overview\n",
+        "\n",
+        "This notebook demonstrates deploying the pre-trained [BLIP2](https://huggingface.co/Salesforce/blip2-opt-2.7b) model on Vertex AI for online prediction.\n",
+        "\n",
+        "### Objective\n",
+        "\n",
+        "- Upload the model to [Model Registry](https://cloud.google.com/vertex-ai/docs/model-registry/introduction).\n",
+        "- Deploy the model on [Endpoint](https://cloud.google.com/vertex-ai/docs/predictions/using-private-endpoints).\n",
+        "- Run online predictions for image captioning.\n",
+        "\n",
+        "### Costs\n",
+        "\n",
+        "This tutorial uses billable components of Google Cloud:\n",
+        "\n",
+        "* Vertex AI\n",
+        "* Cloud Storage\n",
+        "\n",
+        "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing) and [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."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "264c07757582"
+      },
+      "source": [
+        "## Setup environment\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": "d73ffa0c0b83"
+      },
+      "source": [
+        "### Colab only"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "2707b02ef5df"
+      },
+      "outputs": [],
+      "source": [
+        "!pip3 install --upgrade google-cloud-aiplatform"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "b60a4d7100bf"
+      },
+      "outputs": [],
+      "source": [
+        "from google.colab import auth as google_auth\n",
+        "\n",
+        "google_auth.authenticate_user()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "0f826ff482a2"
+      },
+      "source": [
+        "### Setup Google Cloud project\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. [Create a Cloud Storage bucket](https://cloud.google.com/storage/docs/creating-buckets) for storing experiment outputs."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "8958ebc71868"
+      },
+      "source": [
+        "Fill following variables for experiments environment:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "9db30f827a65"
+      },
+      "outputs": [],
+      "source": [
+        "# Cloud project id.\n",
+        "PROJECT_ID = \"\"  # @param {type:\"string\"}\n",
+        "\n",
+        "# The region you want to launch jobs in.\n",
+        "REGION = \"us-central1\"  # @param {type:\"string\"}\n",
+        "\n",
+        "# The Cloud Storage bucket for storing experiments output. Fill it without the 'gs://' prefix.\n",
+        "GCS_BUCKET = \"\"  # @param {type:\"string\"}"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "92f16e22c20b"
+      },
+      "source": [
+        "Initialize Vertex AI API:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "1680c257acfb"
+      },
+      "outputs": [],
+      "source": [
+        "from google.cloud import aiplatform\n",
+        "\n",
+        "aiplatform.init(project=PROJECT_ID, location=REGION, staging_bucket=GCS_BUCKET)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "6ca48b699d17"
+      },
+      "source": [
+        "### Define constants"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "de9882ea89ea"
+      },
+      "outputs": [],
+      "source": [
+        "# The pre-built serving docker image.\n",
+        "# The model artifacts are embedded within the container, except for model weights which will be downloaded during deployment.\n",
+        "SERVE_DOCKER_URI = \"us-docker.pkg.dev/vertex-ai-restricted/vertex-vision-model-garden-dockers/pytorch-transformers-serve\""
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "10188266a5cd"
+      },
+      "source": [
+        "### Define common functions"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "cac4478ae098"
+      },
+      "outputs": [],
+      "source": [
+        "import base64\n",
+        "import os\n",
+        "from datetime import datetime\n",
+        "from io import BytesIO\n",
+        "\n",
+        "import requests\n",
+        "from google.cloud import aiplatform\n",
+        "from PIL import Image\n",
+        "\n",
+        "\n",
+        "def create_job_name(prefix):\n",
+        "    user = os.environ.get(\"USER\")\n",
+        "    now = datetime.now().strftime(\"%Y%m%d_%H%M%S\")\n",
+        "    job_name = f\"{prefix}-{user}-{now}\"\n",
+        "    return job_name\n",
+        "\n",
+        "\n",
+        "def download_image(url):\n",
+        "    response = requests.get(url)\n",
+        "    return Image.open(BytesIO(response.content))\n",
+        "\n",
+        "\n",
+        "def image_to_base64(image, format=\"JPEG\"):\n",
+        "    buffer = BytesIO()\n",
+        "    image.save(buffer, format=format)\n",
+        "    image_str = base64.b64encode(buffer.getvalue()).decode(\"utf-8\")\n",
+        "    return image_str\n",
+        "\n",
+        "\n",
+        "def base64_to_image(image_str):\n",
+        "    image = Image.open(BytesIO(base64.b64decode(image_str)))\n",
+        "    return image\n",
+        "\n",
+        "\n",
+        "def image_grid(imgs, rows=2, cols=2):\n",
+        "    w, h = imgs[0].size\n",
+        "    grid = Image.new(\"RGB\", size=(cols * w, rows * h))\n",
+        "    for i, img in enumerate(imgs):\n",
+        "        grid.paste(img, box=(i % cols * w, i // cols * h))\n",
+        "    return grid\n",
+        "\n",
+        "\n",
+        "def deploy_model(model_id, task):\n",
+        "    model_name = \"blip-image-captioning\"\n",
+        "    endpoint = aiplatform.Endpoint.create(display_name=f\"{model_name}-endpoint\")\n",
+        "    serving_env = {\n",
+        "        \"MODEL_ID\": model_id,\n",
+        "        \"TASK\": task,\n",
+        "    }\n",
+        "    # If the model_id is a GCS path, use artifact_uri to pass it to serving docker.\n",
+        "    artifact_uri = model_id if model_id.startswith(\"gs://\") else None\n",
+        "    model = aiplatform.Model.upload(\n",
+        "        display_name=model_name,\n",
+        "        serving_container_image_uri=SERVE_DOCKER_URI,\n",
+        "        serving_container_ports=[7080],\n",
+        "        serving_container_predict_route=\"/predictions/transformers_serving\",\n",
+        "        serving_container_health_route=\"/ping\",\n",
+        "        serving_container_environment_variables=serving_env,\n",
+        "        artifact_uri=artifact_uri,\n",
+        "    )\n",
+        "    model.deploy(\n",
+        "        endpoint=endpoint,\n",
+        "        machine_type=\"n1-standard-8\",\n",
+        "        accelerator_type=\"NVIDIA_TESLA_T4\",\n",
+        "        accelerator_count=1,\n",
+        "        deploy_request_timeout=1800,\n",
+        "    )\n",
+        "    return model, endpoint"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "d2d72ecdb8c9"
+      },
+      "source": [
+        "## Upload and deploy models"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "9448c5f545fa"
+      },
+      "source": [
+        "This section uploads the pre-trained model to Model Registry and deploys it on the Endpoint with 1 T4 GPU.\n",
+        "\n",
+        "The model deployment step will take ~15 minutes to complete.\n",
+        "\n",
+        "Once deployed, you can send images to get descriptions."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "19e8aeec969c"
+      },
+      "source": [
+        "### Image captioning"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "b4b46c28d8b1"
+      },
+      "outputs": [],
+      "source": [
+        "model, endpoint = deploy_model(\n",
+        "    model_id=\"Salesforce/blip2-opt-2.7b\", task=\"image-to-text\"\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "12893aa2c5af"
+      },
+      "source": [
+        "NOTE: The model weights will be downloaded after the deployment succeeds. When the model is very large it could add 5~15mins additional time before the endpoint is ready for prediction."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "6be655247cb1"
+      },
+      "outputs": [],
+      "source": [
+        "image = download_image(\"http://images.cocodataset.org/val2017/000000039769.jpg\")\n",
+        "display(image)\n",
+        "\n",
+        "instances = [\n",
+        "    {\"image\": image_to_base64(image)},\n",
+        "]\n",
+        "preds = endpoint.predict(instances=instances).predictions\n",
+        "print(preds)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "2ccf3714dbe9"
+      },
+      "outputs": [],
+      "source": [
+        "# Undeploy model and delete endpoint.\n",
+        "endpoint.delete(force=True)\n",
+        "\n",
+        "# Delete models.\n",
+        "model.delete()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "01e11d85d504"
+      },
+      "source": [
+        "### VQA (Visual-Question-Answering)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "26018d961cf9"
+      },
+      "outputs": [],
+      "source": [
+        "model, endpoint = deploy_model(\n",
+        "    model_id=\"Salesforce/blip2-opt-2.7b\", task=\"visual-question-answering\"\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "0ac7f8d945e3"
+      },
+      "source": [
+        "NOTE: The model weights will be downloaded after the deployment succeeds. When the model is very large it could add 5~15mins additional time before the endpoint is ready for prediction."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "f19c342829fd"
+      },
+      "outputs": [],
+      "source": [
+        "image = download_image(\n",
+        "    \"https://media.newyorker.com/cartoons/63dc6847be24a6a76d90eb99/master/w_1160,c_limit/230213_a26611_838.jpg\"\n",
+        ")\n",
+        "display(image)\n",
+        "\n",
+        "question = \"Question: What are they doing? Answer:\"\n",
+        "instances = [\n",
+        "    {\"image\": image_to_base64(image), \"text\": question},\n",
+        "]\n",
+        "preds = endpoint.predict(instances=instances).predictions\n",
+        "print(question)\n",
+        "print(preds)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "712eb9d0b336"
+      },
+      "outputs": [],
+      "source": [
+        "# Undeploy model and delete endpoint.\n",
+        "endpoint.delete(force=True)\n",
+        "\n",
+        "# Delete models.\n",
+        "model.delete()"
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "name": "model_garden_pytorch_blip2.ipynb",
+      "toc_visible": true
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
@@ -273,7 +273,11 @@
        "\n",
        "def draw_image_with_boxes(image, boxes):\n",
        "    fig, ax = plt.subplots()\n",
+        "    plt.axis(\"off\")\n",
        "    ax.imshow(image)\n",
+        "    if len(boxes) == 0:\n",
+        "        return\n",
+        "    boxes = boxes[\"boxes\"]\n",
        "    for box in boxes:\n",
        "        x, y = box[\"xmin\"], box[\"ymin\"]\n",
        "        width, height = box[\"xmax\"] - x, box[\"ymax\"] - y\n",
@@ -281,7 +285,6 @@
        "            (x, y), width, height, linewidth=2, edgecolor=\"yellow\", facecolor=\"none\"\n",
        "        )\n",
        "        ax.add_patch(rect)\n",
-        "    plt.axis(\"off\")\n",
        "    plt.show()\n",
        "\n",
        "\n",
@@ -362,7 +365,7 @@
        "    {\"image\": image_to_base64(image), \"text\": \"cat\"},\n",
        "]\n",
        "preds = endpoint.predict(instances=instances).predictions\n",
-        "draw_image_with_boxes(image, preds[0][\"boxes\"])\n",
+        "draw_image_with_boxes(image, preds[0])\n",
        "print(preds)"
      ]
    },
@@ -242,22 +242,7 @@
      "source": [
        "## Notes about service account and permission\n",
        "\n",
-        "**By default no configuration is required**, if you run into any permission related issue, please make sure the service accounts above have the required roles:\n",
-        "\n",
-        "|Service account email|Description|Roles|\n",
-        "|---|---|---|\n",
-        "|PROJECT_NUMBER-compute@developer.gserviceaccount.com|Compute Engine default service account|Dataflow Developer, Dataflow Worker, Storage Admin, BigQuery Data Editor, Vertex AI User, Service Account User|\n",
-        "|service-PROJECT_NUMBER@gcp-sa-aiplatform.iam.gserviceaccount.com|AI Platform Service Agent|Vertex AI Service Agent|\n",
-        "\n",
-        "\n",
-        "1. Goto https://console.cloud.google.com/iam-admin/iam.\n",
-        "2. Check the \"Include Google-provided role grants\" checkbox.\n",
-        "3. Find the above emails.\n",
-        "4. Grant the corresponding roles.\n",
-        "\n",
-        "### Using data source from a different project\n",
-        "- For the BQ data source, grant both service accounts the \"BigQuery Data Viewer\" role.\n",
-        "- For the CSV data source, grant both service accounts the \"Storage Object Viewer\" role.\n"
+        "**By default no configuration is required**, if you run into any permission related issue, please make sure the service accounts have the required roles listed in the [Service accounts for Tabular Workflow for End-to-End AutoML documentation](https://cloud.google.com/vertex-ai/docs/tabular-data/tabular-workflows/service-accounts#e2e-automl)."
      ]
    },
    {
@@ -1577,7 +1577,7 @@
  ],
  "metadata": {
    "colab": {
-      "name": "UJ10 Vertex SDK Custom Scikit-Learn with pre-built training container.ipynb",
+      "name": "sdk-custom-scikit-learn-prebuilt-container.ipynb",
      "toc_visible": true
    },
    "kernelspec": {
@@ -201,8 +201,8 @@
        "\n",
        "! pip3 install --upgrade {USER_FLAG} google-cloud-aiplatform \\\n",
        "                                    google-cloud-storage \\\n",
-        "                                    kfp \\\n",
-        "                                    google-cloud-pipeline-components -q"
+        "                                    'kfp<2' \\\n",
+        "                                    'google-cloud-pipeline-components<2' -q"
      ]
    },
    {
@@ -165,11 +165,11 @@
        "# Install the packages\n",
        "USER=''\n",
        "! pip3 install {USER} --upgrade google-cloud-aiplatform \\\n",
-        "                                google-cloud-pipeline-components\n",
+        "                                'google-cloud-pipeline-components<2'\n",
        "! pip3 install {USER}           tensorflow==2.5 \\\n",
        "                                tensorflow_hub\n",
        "  \n",
-        "! pip3 install {USER} --upgrade kfp"
+        "! pip3 install {USER} --upgrade 'kfp<2'"
      ]
    },
    {
@@ -175,7 +175,7 @@
        "\n",
        "! pip3 install --upgrade google-cloud-aiplatform {USER_FLAG} -q\n",
        "! pip3 install -U google-cloud-storage {USER_FLAG} -q\n",
-        "! pip3 install {USER_FLAG} kfp google-cloud-pipeline-components --upgrade -q"
+        "! pip3 install {USER_FLAG} 'kfp<2' 'google-cloud-pipeline-components<2' --upgrade -q"
      ]
    },
    {
@@ -197,10 +197,10 @@
        "\n",
        "! pip3 install --upgrade google-cloud-aiplatform {USER_FLAG} -q\n",
        "! pip3 install -U google-cloud-storage {USER_FLAG} -q\n",
-        "! pip3 install {USER_FLAG} kfp google-cloud-pipeline-components --upgrade -q\n",
+        "! pip3 install {USER_FLAG} 'kfp<2' 'google-cloud-pipeline-components<2' --upgrade -q\n",
        "\n",
        "\n",
-        "! pip3 install --upgrade --force-reinstall $USER_FLAG tensorflow kfp google-cloud-aiplatform google-cloud-storage google-cloud-pipeline-components -q"
+        "! pip3 install --upgrade --force-reinstall $USER_FLAG tensorflow 'kfp<2' google-cloud-aiplatform google-cloud-storage 'google-cloud-pipeline-components<2' -q"
      ]
    },
    {
@@ -224,8 +224,8 @@
        "                            google-cloud-bigquery \\\n",
        "                            pandas \\\n",
        "                            pyarrow \\\n",
-        "                            kfp \\\n",
-        "                            google-cloud-pipeline-components {USER_FLAG} -q \n",
+        "                            'kfp<2' \\\n",
+        "                            'google-cloud-pipeline-components<2' {USER_FLAG} -q \n",
        "! pip3 install db-dtypes {USER_FLAG} -q"
      ]
    },
@@ -149,8 +149,8 @@
        "! pip3 install -U tensorflow-transform==1.2  -q\n",
        "! pip3 install -U tensorflow-io==0.18  -q\n",
        "! pip3 install --upgrade google-cloud-aiplatform[tensorboard] -q\n",
-        "! pip3 install --upgrade google-cloud-pipeline-components  -q\n",
-        "! pip3 install --upgrade kfp -q"
+        "! pip3 install --upgrade 'google-cloud-pipeline-components<2'  -q\n",
+        "! pip3 install --upgrade 'kfp<2' -q"
      ]
    },
    {
@@ -138,8 +138,8 @@
        "import os\n",
        "\n",
        "! pip3 install --upgrade google-cloud-aiplatform \\\n",
-        "                         google-cloud-pipeline-components --quiet\n",
-        "! pip3 install --upgrade kfp --quiet\n",
+        "                         'google-cloud-pipeline-components<2' --quiet\n",
+        "! pip3 install --upgrade 'kfp<2' --quiet\n",
        "! pip3 install --upgrade tensorflow==2.7 --quiet"
      ]
    },
@@ -193,7 +193,7 @@
        "if IS_WORKBENCH_NOTEBOOK:\n",
        "    USER_FLAG = \"--user\"\n",
        "\n",
-        "! pip3 install --upgrade --quiet {USER_FLAG} google-cloud-aiplatform kfp google-cloud-pipeline-components google-cloud-storage"
+        "! pip3 install --upgrade --quiet {USER_FLAG} google-cloud-aiplatform 'kfp<2' 'google-cloud-pipeline-components<2' google-cloud-storage"
      ]
    },
    {
@@ -198,7 +198,7 @@
        "\n",
        "! pip3 install --upgrade google-cloud-aiplatform \\\n",
        "                        google-cloud-storage \\\n",
-        "                        $USER kfp google-cloud-pipeline-components -q "
+        "                        $USER 'kfp<2' 'google-cloud-pipeline-components<2' -q "
      ]
    },
    {
@@ -196,7 +196,7 @@
        "\n",
        "! pip3 install --upgrade google-cloud-aiplatform {USER_FLAG} -q\n",
        "! pip3 install -U google-cloud-storage $USER_FLAG -q\n",
-        "! pip3 install $USER kfp google-cloud-pipeline-components --upgrade -q"
+        "! pip3 install $USER 'kfp<2' 'google-cloud-pipeline-components<2' --upgrade -q"
      ]
    },
    {
@@ -198,8 +198,8 @@
        "\n",
        "! pip3 install --upgrade {USER_FLAG} -q google-cloud-aiplatform \\\n",
        "                                        google-cloud-storage {USER_FLAG} \\\n",
-        "                                        kfp \\\n",
-        "                                        google-cloud-pipeline-components"
+        "                                        'kfp<2' \\\n",
+        "                                        'google-cloud-pipeline-components<2'"
      ]
    },
    {
@@ -199,8 +199,8 @@
        "\n",
        "\n",
        "! pip3 install --upgrade google-cloud-aiplatform \\\n",
-        "                        google-cloud-pipeline-components \\\n",
-        "                        kfp $USER_FLAG -q"
+        "                        'google-cloud-pipeline-components<2' \\\n",
+        "                        'kfp<2' $USER_FLAG -q"
      ]
    },
    {
@@ -203,7 +203,7 @@
        "\n",
        "! pip3 install --upgrade google-cloud-aiplatform {USER_FLAG} -q\n",
        "! pip3 install -U google-cloud-storage {USER_FLAG} -q\n",
-        "! pip3 install {USER_FLAG} kfp google-cloud-pipeline-components --upgrade -q"
+        "! pip3 install {USER_FLAG} 'kfp<2' 'google-cloud-pipeline-components<2' --upgrade -q"
      ]
    },
    {
@@ -201,7 +201,7 @@
        "\n",
        "! pip3 install --upgrade google-cloud-aiplatform {USER_FLAG} -q\n",
        "! pip3 install -U google-cloud-storage {USER_FLAG} -q\n",
-        "! pip3 install {USER_FLAG} kfp google-cloud-pipeline-components --upgrade -q\n",
+        "! pip3 install {USER_FLAG} 'kfp<2' 'google-cloud-pipeline-components<2' --upgrade -q\n",
        "\n",
        "if os.getenv(\"IS_TESTING\"):\n",
        "    ! pip3 install --upgrade matplotlib $USER_FLAG -q"
@@ -168,11 +168,11 @@
        "# Install the packages\n",
        "USER=''\n",
        "! pip3 install {USER} --upgrade google-cloud-aiplatform \\\n",
-        "                                google-cloud-pipeline-components\n",
+        "                                'google-cloud-pipeline-components<2'\n",
        "! pip3 install {USER}           tensorflow==2.5 \\\n",
        "                                tensorflow_hub\n",
        "\n",
-        "! pip3 install {USER} --upgrade kfp"
+        "! pip3 install {USER} --upgrade 'kfp<2'"
      ]
    },
    {
@@ -128,8 +128,8 @@
        "# Install the packages\n",
        "! pip3 install --upgrade google-cloud-aiplatform \\\n",
        "                        google-cloud-storage \\\n",
-        "                        kfp \\\n",
-        "                        google-cloud-pipeline-components"
+        "                        'kfp<2' \\\n",
+        "                        'google-cloud-pipeline-components<2'"
      ]
    },
    {
@@ -268,22 +268,7 @@
      "source": [
        "## Notes about service account and permission\n",
        "\n",
-        "**By default no configuration is required**, if you run into any permission related issue, please make sure the service accounts above have the required roles:\n",
-        "\n",
-        "|Service account email|Description|Roles|\n",
-        "|---|---|---|\n",
-        "|PROJECT_NUMBER-compute@developer.gserviceaccount.com|Compute Engine default service account|Dataflow Admin, Dataflow Worker, Storage Admin, BigQuery Admin, Vertex AI User|\n",
-        "|service-PROJECT_NUMBER@gcp-sa-aiplatform.iam.gserviceaccount.com|AI Platform Service Agent|Vertex AI Service Agent|\n",
-        "\n",
-        "\n",
-        "1. Goto https://console.cloud.google.com/iam-admin/iam.\n",
-        "2. Check the \"Include Google-provided role grants\" checkbox.\n",
-        "3. Find the above emails.\n",
-        "4. Grant the corresponding roles.\n",
-        "\n",
-        "### Using data source from a different project\n",
-        "- For the BQ data source, grant both service accounts the \"BigQuery Data Viewer\" role.\n",
-        "- For the CSV data source, grant both service accounts the \"Storage Object Viewer\" role.\n"
+        "**By default no configuration is required**, if you run into any permission related issue, please make sure the service accounts have the required roles listed in the [Service accounts for Tabular Workflow for TabNet, and Tabular Workflow for Wide & Deep, and Prophet documentation](https://cloud.google.com/vertex-ai/docs/tabular-data/tabular-workflows/service-accounts#fte-workflow)."
      ]
    },
    {
@@ -268,22 +268,7 @@
      "source": [
        "## Notes about service account and permission\n",
        "\n",
-        "**By default no configuration is required**, if you run into any permission related issue, please make sure the service accounts above have the required roles:\n",
-        "\n",
-        "|Service account email|Description|Roles|\n",
-        "|---|---|---|\n",
-        "|PROJECT_NUMBER-compute@developer.gserviceaccount.com|Compute Engine default service account|Dataflow Admin, Dataflow Worker, Storage Admin, BigQuery Admin, Vertex AI User|\n",
-        "|service-PROJECT_NUMBER@gcp-sa-aiplatform.iam.gserviceaccount.com|AI Platform Service Agent|Vertex AI Service Agent|\n",
-        "\n",
-        "\n",
-        "1. Goto https://console.cloud.google.com/iam-admin/iam.\n",
-        "2. Check the \"Include Google-provided role grants\" checkbox.\n",
-        "3. Find the above emails.\n",
-        "4. Grant the corresponding roles.\n",
-        "\n",
-        "### Using data source from a different project\n",
-        "- For the BQ data source, grant both service accounts the \"BigQuery Data Viewer\" role.\n",
-        "- For the CSV data source, grant both service accounts the \"Storage Object Viewer\" role."
+        "**By default no configuration is required**, if you run into any permission related issue, please make sure the service accounts have the required roles listed in the [Service accounts for Tabular Workflow for TabNet, and Tabular Workflow for Wide & Deep, and Prophet documentation](https://cloud.google.com/vertex-ai/docs/tabular-data/tabular-workflows/service-accounts#fte-workflow)."
      ]
    },
    {
Author	SHA1	Message	Date
Andrew Ferlitsch	5c49bc6fe7	fix: rename UJ10	2023-04-19 23:51:55 +00:00
Connor McCarthyandGitHub	098ad42f70	pin kfp in google_cloud_pipeline_components_automl_text (#1748 )	2023-04-19 23:01:21 +00:00
Connor McCarthyandGitHub	1f141d0059	pin kfp in google_cloud_pipeline_components_automl_images (#1746 )	2023-04-19 19:29:50 +00:00
Andrew FerlitschandGitHub	e0a1608783	fix: pin kfp and gcpc < 2.0 (#1738 )	2023-04-19 18:37:16 +00:00
Connor McCarthyandGitHub	1a469a09df	pin kfp in google_cloud_pipeline_components_automl_tabular (#1747 )	2023-04-19 18:14:04 +00:00
Connor McCarthyandGitHub	bc3f6d3819	pin kfp in custom_model_training_and_batch_prediction (#1741 )	2023-04-19 16:53:23 +00:00
Andrew FerlitschandGitHub	f088a3ce69	update (#1736 )	2023-04-19 16:52:34 +00:00
Connor McCarthyandGitHub	863660042b	pin kfp in custom_tabular_train_batch_pred_bq_pipeline (#1742 )	2023-04-19 16:51:11 +00:00
Connor McCarthyandGitHub	7162248267	pin kfp in google_cloud_pipeline_components_model_train_upload_deploy (#1749 )	2023-04-19 16:50:43 +00:00
Connor McCarthyandGitHub	2e908a8efa	pin kfp in get_started_with_hpt_pipeline_components (#1743 )	2023-04-19 16:50:13 +00:00
Connor McCarthyandGitHub	588d2c880e	pin kfp in get_started_with_machine_management (#1745 )	2023-04-19 16:49:12 +00:00
Connor McCarthyandGitHub	54f10c7411	pin kfp in google_cloud_pipeline_components_model_upload_predict_evaluate (#1750 )	2023-04-19 16:48:46 +00:00
Connor McCarthyandGitHub	0c2b9e9f45	pin kfp in multicontender_vs_champion_deployment_method (#1753 )	2023-04-19 16:48:21 +00:00
Connor McCarthyandGitHub	fe07d416e5	pin kfp in challenger_vs_blessed_deployment_method (#1739 )	2023-04-19 16:04:05 +00:00
Connor McCarthyandGitHub	9c69cbfd54	pin kfp in control_flow_kfp (#1740 )	2023-04-19 16:03:33 +00:00
Connor McCarthyandGitHub	2a25be6af2	pin kfp in lightweight_functions_component_io_kfp (#1751 )	2023-04-19 16:02:52 +00:00
Connor McCarthyandGitHub	9680a7e772	pin kfp in metrics_viz_run_compare_kfp (#1752 )	2023-04-19 16:02:03 +00:00
Connor McCarthyandGitHub	30527875ed	pin kfp in pipelines_intro_kfp (#1754 )	2023-04-19 16:01:36 +00:00
yishan-pu GitHub Yishan Pu	8c11e19d86	Update service accounts and permissions info in the Wide and Deep notebook (#1737 ) Co-authored-by: Yishan Pu <yishanpu@google.com>	2023-04-19 15:24:34 +00:00
yishan-pu GitHub Yishan Pu	f44f51c06d	Update the service accounts and permissions info in the TabNet notebook (#1734 ) Co-authored-by: Yishan Pu <yishanpu@google.com>	2023-04-18 16:06:42 +00:00
yishan-pu GitHub Yishan Pu	840b537ea6	Update the E2E AutoML Notebook regarding the service accounts and permissions info (#1731 ) Co-authored-by: Yishan Pu <yishanpu@google.com>	2023-04-17 23:16:28 +00:00
Xiang XuandGitHub	d2602b944f	Add blip2 notebook (#1730 ) * add blip2 * resolve comments	2023-04-17 23:14:34 +00:00
Xiang XuandGitHub	bb39135946	fix owlvit (#1729 )	2023-04-17 15:19:36 +00:00
gericdongandGitHub	cb72a56e55	feat: PyTorch train and deploy E2E with pre-built containers (#1728 ) * feat: PyTorch train and deploy E2E with pre-built containers * address review comments * address review comment 2 * suppress gsutil warning messags * Use unique names * Corrected the project id template	2023-04-17 14:56:43 +00:00
Andrew FerlitschandGitHub	eee97362d0	fix: migrate tabnet (#1727 ) * fix: migrate tabnet * fix: describe * updates from review	2023-04-13 21:09:23 +00:00