mirror of
https://github.com/GoogleCloudPlatform/vertex-ai-samples.git
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Compare commits
1
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 Andrew Ferlitsch
|
69aa45293d |
@@ -1,22 +0,0 @@
|
||||
'''
|
||||
Viewer for the weekly regression testing of the official notebooks
|
||||
|
||||
Cloud Storage location: gs://cloud-build-notebooks-presubmit/build_results/
|
||||
'''
|
||||
import argparse
|
||||
import json
|
||||
|
||||
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument('--file', dest='file',
|
||||
default='build.json', type=str, help='build results file')
|
||||
import json
|
||||
|
||||
with open('build.json', 'r') as f:
|
||||
results = json.load(f)
|
||||
|
||||
for item in results.items():
|
||||
if item[1]['passed']:
|
||||
print(f"{item[0]},PASSED")
|
||||
else:
|
||||
print(f"{item[0]},FAILED")
|
||||
@@ -2,9 +2,9 @@ git+https://github.com/tensorflow/docs
|
||||
ipython
|
||||
jupyter
|
||||
nbconvert
|
||||
black==23.3.0
|
||||
black==22.12.0
|
||||
pyupgrade==3.4.0
|
||||
isort==5.12.0
|
||||
flake8==6.0.0
|
||||
nbqa==1.7.0
|
||||
nbqa==1.5.3
|
||||
|
||||
|
||||
@@ -42,7 +42,6 @@
|
||||
/notebooks/community/pipelines/google_cloud_pipeline_components_cloud_natural_language_pipeline.ipynb @Narwhalprime
|
||||
/notebooks/community/pipelines/google_cloud_pipeline_components_ready_to_go_text_classification_pipeline.ipynb @Narwhalprime
|
||||
/notebooks/community/feature_store/get_started_vertex_feature_store.ipynb @junkourata
|
||||
/notebooks/community/model_garden/model_garden_huggingface_local_inference.ipynb @dstnluong-google
|
||||
/notebooks/community/model_garden/model_garden_tfvision_image_classification.ipynb @genquan9
|
||||
/notebooks/community/model_garden/model_garden_tfvision_image_object_detection.ipynb @genquan9
|
||||
/notebooks/community/model_garden/model_garden_tfvision_image_segmentation.ipynb @genquan9
|
||||
|
||||
@@ -1,358 +0,0 @@
|
||||
{
|
||||
"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."
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "4dc4391f6be7"
|
||||
},
|
||||
"source": [
|
||||
"# Vertex AI Model Garden - Hugging Face Local Inference\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_huggingface_local_inference.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_huggingface_local_inference.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_huggingface_local_inference.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 GPU notebook with preinstalled HuggingFace/transformer libraries is recommended)\n",
|
||||
" </td>\n",
|
||||
"</table>"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "4e8a0fdd6f44"
|
||||
},
|
||||
"source": [
|
||||
"## Overview\n",
|
||||
"\n",
|
||||
"This notebook demonstrates how to run local inference with various Hugging Face models by using [Colab](https://colab.research.google.com/) and installing the necessary libraries or by deploying a [Vertex AI Workbench Instance](https://cloud.google.com/vertex-ai-workbench) with preinstalled transformer and diffuser libraries.\n",
|
||||
"\n",
|
||||
"### Objective\n",
|
||||
"\n",
|
||||
"* Run local inference with various transformer or diffusion models.\n",
|
||||
"\n",
|
||||
"### Costs\n",
|
||||
"\n",
|
||||
"This tutorial uses billable components of Google Cloud:\n",
|
||||
"\n",
|
||||
"* Vertex AI\n",
|
||||
"\n",
|
||||
"Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing) and use the [Pricing Calculator](https://cloud.google.com/products/calculator/) to generate a cost estimate based on your projected usage."
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "69453bf7230e"
|
||||
},
|
||||
"source": [
|
||||
"## Before you begin"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "68990d91bc5f"
|
||||
},
|
||||
"source": [
|
||||
"### Colab only"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "3d342b32fb08"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"if \"google.colab\" in str(get_ipython()):\n",
|
||||
" ! pip3 install --upgrade google-cloud-aiplatform\n",
|
||||
" from google.colab import auth as google_auth\n",
|
||||
"\n",
|
||||
" google_auth.authenticate_user()\n",
|
||||
" ! pip3 install --upgrade pip\n",
|
||||
" ! pip3 install torchvision==0.14.1\n",
|
||||
" ! pip3 install transformers==4.27.1\n",
|
||||
" ! pip3 install diffusers==0.15.1\n",
|
||||
" ! apt-get update\n",
|
||||
" ! apt-get install -y --no-install-recommends tesseract-ocr\n",
|
||||
" ! pip3 install tesseract==0.1.3\n",
|
||||
" ! pip3 install pytesseract==0.3.10\n",
|
||||
" ! pip3 install datasets==2.9.0\n",
|
||||
" ! pip3 install accelerate==0.18.0\n",
|
||||
" ! pip3 install triton==2.0.0.dev20221120\n",
|
||||
" ! pip3 install xformers==0.0.16\n",
|
||||
" ! pip3 install modelscope==1.4.2\n",
|
||||
" ! pip3 install open_clip_torch==2.17.1\n",
|
||||
" ! pip3 install pytorch-lightning==1.9.5\n",
|
||||
" ! pip3 install opencv-python-headless==4.7.0.72\n",
|
||||
" # Install gdown for downloading example training images.\n",
|
||||
" ! pip3 install gdown\n",
|
||||
" # Remove wrong cublas version.\n",
|
||||
" ! pip3 uninstall nvidia_cublas_cu11 --yes\n",
|
||||
"\n",
|
||||
" # Restart the notebook kernel after installs.\n",
|
||||
" import IPython\n",
|
||||
"\n",
|
||||
" app = IPython.Application.instance()\n",
|
||||
" app.kernel.do_shutdown(True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "05e23144b125"
|
||||
},
|
||||
"source": [
|
||||
"### Workbench only\n",
|
||||
"\n",
|
||||
"1. Follow [this link](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_huggingfacE_local_inference.ipynb) to deploy the notebook to a Vertex AI Workbench Instance.\n",
|
||||
"2. Select `Create a new Notebook`.\n",
|
||||
"3. Click `Advanced Options`.\n",
|
||||
"4. In the **Environment** tab, select `Custom Container` for **Environment**.\n",
|
||||
"5. Set the **Docker container image** field to `us-docker.pkg.dev/vertex-ai/vertex-vision-model-garden-dockers/transformers-notebook`.\n",
|
||||
"6. In the **Machine Type** tab, select a 1 `T4` GPU and select `Install NVIDIA GPU driver automatically for me`.\n",
|
||||
"7. Click `Create` to create the Vertex AI Workbench instance.\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "ad1a690839d5"
|
||||
},
|
||||
"source": [
|
||||
"## Sample code"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "0a4008240483"
|
||||
},
|
||||
"source": [
|
||||
"#### [runwayml/stable-diffusion-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5) (Text-to-image)\n",
|
||||
"Generate photo-realistic images given any text input."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "5ec6b474d1be"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import torch\n",
|
||||
"from diffusers import StableDiffusionPipeline\n",
|
||||
"\n",
|
||||
"model_id = \"runwayml/stable-diffusion-v1-5\"\n",
|
||||
"pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)\n",
|
||||
"pipe = pipe.to(\"cuda\")\n",
|
||||
"\n",
|
||||
"prompt = \"a photo of an astronaut riding a horse on mars\"\n",
|
||||
"image = pipe(prompt).images[0]\n",
|
||||
"\n",
|
||||
"display(image)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "ae94b9b23a52"
|
||||
},
|
||||
"source": [
|
||||
"#### [runwayml/stable-diffusion-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5) (Text guided image-to-image)\n",
|
||||
"Generate an image based on an initial image and a text prompt."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "0acd70f4d08a"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from io import BytesIO\n",
|
||||
"\n",
|
||||
"import requests\n",
|
||||
"import torch\n",
|
||||
"from diffusers import StableDiffusionImg2ImgPipeline\n",
|
||||
"from PIL import Image\n",
|
||||
"\n",
|
||||
"device = \"cuda\"\n",
|
||||
"model_id_or_path = \"runwayml/stable-diffusion-v1-5\"\n",
|
||||
"pipe = StableDiffusionImg2ImgPipeline.from_pretrained(\n",
|
||||
" model_id_or_path, torch_dtype=torch.float16\n",
|
||||
")\n",
|
||||
"pipe = pipe.to(device)\n",
|
||||
"\n",
|
||||
"url = \"https://raw.githubusercontent.com/CompVis/stable-diffusion/main/assets/stable-samples/img2img/sketch-mountains-input.jpg\"\n",
|
||||
"\n",
|
||||
"response = requests.get(url)\n",
|
||||
"init_image = Image.open(BytesIO(response.content)).convert(\"RGB\")\n",
|
||||
"init_image = init_image.resize((768, 512))\n",
|
||||
"\n",
|
||||
"prompt = \"A fantasy landscape, trending on artstation\"\n",
|
||||
"\n",
|
||||
"images = pipe(prompt=prompt, image=init_image, strength=0.75, guidance_scale=7.5).images\n",
|
||||
"display(images[0])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "e76b3fe8d10c"
|
||||
},
|
||||
"source": [
|
||||
"#### [runwayml/stable-diffusion-inpainting](https://huggingface.co/runwayml/stable-diffusion-inpainting) (Image-inpainting)\n",
|
||||
"Generate an image based on an original image and prompt, only editing the areas denoted by a mask image."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "8bc3238be4e7"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from io import BytesIO\n",
|
||||
"\n",
|
||||
"import requests\n",
|
||||
"import torch\n",
|
||||
"from diffusers import StableDiffusionInpaintPipeline\n",
|
||||
"from PIL import Image\n",
|
||||
"\n",
|
||||
"image_url = \"https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png\"\n",
|
||||
"image_response = requests.get(image_url)\n",
|
||||
"init_image = Image.open(BytesIO(image_response.content)).convert(\"RGB\")\n",
|
||||
"display(init_image)\n",
|
||||
"\n",
|
||||
"mask_url = \"https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png\"\n",
|
||||
"mask_response = requests.get(mask_url)\n",
|
||||
"mask_image = Image.open(BytesIO(mask_response.content)).convert(\"RGB\")\n",
|
||||
"\n",
|
||||
"pipe = StableDiffusionInpaintPipeline.from_pretrained(\n",
|
||||
" \"runwayml/stable-diffusion-inpainting\",\n",
|
||||
" revision=\"fp16\",\n",
|
||||
" torch_dtype=torch.float16,\n",
|
||||
")\n",
|
||||
"pipe.to(\"cuda\")\n",
|
||||
"\n",
|
||||
"prompt = \"Face of a yellow cat, high resolution, sitting on a park bench\"\n",
|
||||
"images = pipe(prompt=prompt, image=init_image, mask_image=mask_image).images\n",
|
||||
"display(images[0])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "1ade95a9b20e"
|
||||
},
|
||||
"source": [
|
||||
"#### [impira/layoutlm-document-qa](https://huggingface.co/impira/layoutlm-document-qa) (Document question answering)\n",
|
||||
"Answer questions about a given document."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "492d9f1de3f2"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from transformers import pipeline\n",
|
||||
"\n",
|
||||
"nlp = pipeline(\n",
|
||||
" \"document-question-answering\",\n",
|
||||
" model=\"impira/layoutlm-document-qa\",\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"print(\n",
|
||||
" nlp(\n",
|
||||
" \"https://templates.invoicehome.com/invoice-template-us-neat-750px.png\",\n",
|
||||
" \"What is the invoice number?\",\n",
|
||||
" )\n",
|
||||
")\n",
|
||||
"# [{'score': 0.9943977, 'answer': 'us-001', 'start': 15, 'end': 15}]\n",
|
||||
"\n",
|
||||
"print(\n",
|
||||
" nlp(\n",
|
||||
" \"https://miro.medium.com/max/787/1*iECQRIiOGTmEFLdWkVIH2g.jpeg\",\n",
|
||||
" \"What is the purchase amount?\",\n",
|
||||
" )\n",
|
||||
")\n",
|
||||
"# [{'score': 0.9912159, 'answer': '$1,000,000,000', 'start': 97, 'end': 97}]\n",
|
||||
"\n",
|
||||
"print(\n",
|
||||
" nlp(\n",
|
||||
" \"https://www.accountingcoach.com/wp-content/uploads/2013/10/income-statement-example@2x.png\",\n",
|
||||
" \"What are the 2020 net sales?\",\n",
|
||||
" )\n",
|
||||
")\n",
|
||||
"# [{'score': 0.978011429309845, 'answer': '$ 3,980', 'start': 15, 'end': 16}]"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"colab": {
|
||||
"name": "model_garden_huggingface_local_inference.ipynb",
|
||||
"toc_visible": true
|
||||
},
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"name": "python3"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 0
|
||||
}
|
||||
@@ -24,6 +24,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "99c1c3fc2ca5"
|
||||
@@ -54,6 +55,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "3de7470326a2"
|
||||
@@ -61,7 +63,8 @@
|
||||
"source": [
|
||||
"## Overview\n",
|
||||
"\n",
|
||||
"This notebook demonstrates running local inference for [runwayml/stable-diffusion-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5) on either [Colab](https://colab.research.google.com) or [Vertex AI Workbench](https://cloud.google.com/vertex-ai-workbench). This notebook also demonstrates finetuning runwayml/stable-diffusion-v1-5 with [Dreambooth](https://huggingface.co/docs/diffusers/training/dreambooth) and deploying it on Vertex AI for online prediction.\n",
|
||||
"This notebook demonstrates running local inference on [Vertex AI Workbench](https://cloud.google.com/vertex-ai-workbench).\n",
|
||||
"This notebook also demonstrates finetuning [runwayml/stable-diffusion-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5) with [Dreambooth](https://huggingface.co/docs/diffusers/training/dreambooth) and deploying it on Vertex AI for online prediction.\n",
|
||||
"\n",
|
||||
"### Objective\n",
|
||||
"\n",
|
||||
@@ -82,33 +85,132 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "e8a42fa49305"
|
||||
},
|
||||
"source": [
|
||||
"## Local inference (Workbench only)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "1169c41b76b3"
|
||||
},
|
||||
"source": [
|
||||
"The quickest and easiest way to use this model locally is by using Vertex AI Workbench with a pre-built custom container that has the necessary packages installed.\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"1. Follow [this link](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_stable_diffusion.ipynb) to deploy the notebook to a Vertex AI Workbench Instance.\n",
|
||||
"2. Select `Create a new Notebook`.\n",
|
||||
"3. Click `Advanced Options`.\n",
|
||||
"4. Under **Environment**, select `Custom Container` for `Environment`. \n",
|
||||
"5. Set `Docker container image` to `us-docker.pkg.dev/vertex-ai/vertex-vision-model-garden-dockers/transformers-notebook`.\n",
|
||||
"6. Under **Machine configuration**, select a GPU and select `Install NVIDIA GPU driver automatically for me`.\n",
|
||||
"7. Click `Create` to create the Vertex AI Workbench instance. \n",
|
||||
"\n",
|
||||
"Once the notebook is ready, simply execute the code block(s) below in the Workbench instance."
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "1d5ebc91c786"
|
||||
},
|
||||
"source": [
|
||||
"### Text-to-image"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "d39ed8c97cc5"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import torch\n",
|
||||
"from diffusers import StableDiffusionPipeline\n",
|
||||
"\n",
|
||||
"model_id = \"runwayml/stable-diffusion-v1-5\"\n",
|
||||
"pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)\n",
|
||||
"pipe = pipe.to(\"cuda\")\n",
|
||||
"\n",
|
||||
"prompt = \"a photo of an astronaut riding a horse on mars\"\n",
|
||||
"image = pipe(prompt).images[0]\n",
|
||||
"\n",
|
||||
"display(image)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "5aed5ed7b6f6"
|
||||
},
|
||||
"source": [
|
||||
"### Text-guided image-to-image"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "faadabb7728f"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from io import BytesIO\n",
|
||||
"\n",
|
||||
"import requests\n",
|
||||
"import torch\n",
|
||||
"from diffusers import StableDiffusionImg2ImgPipeline\n",
|
||||
"from PIL import Image\n",
|
||||
"\n",
|
||||
"device = \"cuda\"\n",
|
||||
"model_id_or_path = \"runwayml/stable-diffusion-v1-5\"\n",
|
||||
"pipe = StableDiffusionImg2ImgPipeline.from_pretrained(\n",
|
||||
" model_id_or_path, torch_dtype=torch.float16\n",
|
||||
")\n",
|
||||
"pipe = pipe.to(device)\n",
|
||||
"\n",
|
||||
"url = \"https://raw.githubusercontent.com/CompVis/stable-diffusion/main/assets/stable-samples/img2img/sketch-mountains-input.jpg\"\n",
|
||||
"\n",
|
||||
"response = requests.get(url)\n",
|
||||
"init_image = Image.open(BytesIO(response.content)).convert(\"RGB\")\n",
|
||||
"init_image = init_image.resize((768, 512))\n",
|
||||
"\n",
|
||||
"prompt = \"A fantasy landscape, trending on artstation\"\n",
|
||||
"\n",
|
||||
"images = pipe(prompt=prompt, image=init_image, strength=0.75, guidance_scale=7.5).images\n",
|
||||
"display(images[0])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "264c07757582"
|
||||
},
|
||||
"source": [
|
||||
"## Before you begin\n",
|
||||
"## 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": "ioensNKM8ned"
|
||||
},
|
||||
"source": [
|
||||
"### Setup notebook"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "d73ffa0c0b83"
|
||||
},
|
||||
"source": [
|
||||
"#### Colab only\n",
|
||||
"Run the following commands for Colab and skip this section if you are using Workbench."
|
||||
"### Colab only"
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -119,48 +221,70 @@
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"if \"google.colab\" in str(get_ipython()):\n",
|
||||
" ! pip3 install --upgrade google-cloud-aiplatform\n",
|
||||
" from google.colab import auth as google_auth\n",
|
||||
"\n",
|
||||
" google_auth.authenticate_user()\n",
|
||||
" ! pip3 install --upgrade pip\n",
|
||||
" ! pip3 install torchvision==0.14.1\n",
|
||||
" ! pip3 install transformers==4.27.1\n",
|
||||
" ! pip3 install diffusers==0.15.1\n",
|
||||
" ! pip3 install datasets==2.9.0\n",
|
||||
" ! pip3 install accelerate==0.18.0\n",
|
||||
" ! pip3 install triton==2.0.0.dev20221120\n",
|
||||
" ! pip3 install xformers==0.0.16\n",
|
||||
" # Install gdown for downloading example training images.\n",
|
||||
" ! pip3 install gdown\n",
|
||||
" # Remove wrong cublas version.\n",
|
||||
" ! pip3 uninstall nvidia_cublas_cu11 --yes\n",
|
||||
"\n",
|
||||
" # Restart the notebook kernel after installs.\n",
|
||||
" import IPython\n",
|
||||
"\n",
|
||||
" app = IPython.Application.instance()\n",
|
||||
" app.kernel.do_shutdown(True)"
|
||||
"!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()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "fb671e75ca7b"
|
||||
},
|
||||
"source": [
|
||||
"#### Workbench only\n",
|
||||
"1. Follow [this link](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_stable_diffusion_inpainting.ipynb) to deploy the notebook to a Vertex AI Workbench Instance.\n",
|
||||
"2. Select `Create a new Notebook`.\n",
|
||||
"3. Click `Advanced Options`.\n",
|
||||
"4. Under **Environment**, select `Custom Container` for `Environment`. \n",
|
||||
"5. Set `Docker container image` to `us-docker.pkg.dev/vertex-ai/vertex-vision-model-garden-dockers/transformers-notebook`.\n",
|
||||
"6. Under **Machine configuration**, select 1 `T4` GPU and select `Install NVIDIA GPU driver automatically for me`.\n",
|
||||
"7. Click `Create` to create the Vertex AI Workbench instance."
|
||||
"### Install dependencies"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "dc8ee367fb42"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# Install gdown for downloading example training images.\n",
|
||||
"!pip install gdown"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "5244aac3d929"
|
||||
},
|
||||
"source": [
|
||||
"Restart the notebook kernel after installs."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "567212ff53a6"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import IPython\n",
|
||||
"\n",
|
||||
"app = IPython.Application.instance()\n",
|
||||
"app.kernel.do_shutdown(True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "bb7adab99e41"
|
||||
@@ -180,6 +304,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "6c460088b873"
|
||||
@@ -210,6 +335,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "e828eb320337"
|
||||
@@ -232,6 +358,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "2cc825514deb"
|
||||
@@ -256,6 +383,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "0c250872074f"
|
||||
@@ -279,7 +407,6 @@
|
||||
"from io import BytesIO\n",
|
||||
"\n",
|
||||
"import requests\n",
|
||||
"import torch\n",
|
||||
"from google.cloud import aiplatform, storage\n",
|
||||
"from PIL import Image\n",
|
||||
"\n",
|
||||
@@ -365,82 +492,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "e8a42fa49305"
|
||||
},
|
||||
"source": [
|
||||
"## Run inferences locally"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "1d5ebc91c786"
|
||||
},
|
||||
"source": [
|
||||
"### Text-to-image"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "d39ed8c97cc5"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from diffusers import StableDiffusionPipeline\n",
|
||||
"\n",
|
||||
"model_id = \"runwayml/stable-diffusion-v1-5\"\n",
|
||||
"pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)\n",
|
||||
"pipe = pipe.to(\"cuda\")\n",
|
||||
"\n",
|
||||
"prompt = \"a photo of an astronaut riding a horse on mars\"\n",
|
||||
"image = pipe(prompt).images[0]\n",
|
||||
"\n",
|
||||
"display(image)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "5aed5ed7b6f6"
|
||||
},
|
||||
"source": [
|
||||
"### Text-guided image-to-image"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "faadabb7728f"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from diffusers import StableDiffusionImg2ImgPipeline\n",
|
||||
"\n",
|
||||
"device = \"cuda\"\n",
|
||||
"model_id_or_path = \"runwayml/stable-diffusion-v1-5\"\n",
|
||||
"pipe = StableDiffusionImg2ImgPipeline.from_pretrained(\n",
|
||||
" model_id_or_path, torch_dtype=torch.float16\n",
|
||||
")\n",
|
||||
"pipe = pipe.to(device)\n",
|
||||
"\n",
|
||||
"url = \"https://raw.githubusercontent.com/CompVis/stable-diffusion/main/assets/stable-samples/img2img/sketch-mountains-input.jpg\"\n",
|
||||
"\n",
|
||||
"response = requests.get(url)\n",
|
||||
"init_image = Image.open(BytesIO(response.content)).convert(\"RGB\")\n",
|
||||
"init_image = init_image.resize((768, 512))\n",
|
||||
"\n",
|
||||
"prompt = \"A fantasy landscape, trending on artstation\"\n",
|
||||
"\n",
|
||||
"images = pipe(prompt=prompt, image=init_image, strength=0.75, guidance_scale=7.5).images\n",
|
||||
"display(images[0])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "e70e3519ff8b"
|
||||
@@ -450,6 +502,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "0dc65d8f0689"
|
||||
@@ -479,6 +532,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "969cfeb79317"
|
||||
@@ -548,6 +602,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "bf7f82732e61"
|
||||
@@ -557,6 +612,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "1cc26e68d7b0"
|
||||
@@ -568,6 +624,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "cd7b56421392"
|
||||
@@ -577,6 +634,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "6d331b1ea337"
|
||||
@@ -604,6 +662,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "80b3fd2ace09"
|
||||
@@ -632,6 +691,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "af21a3cff1e0"
|
||||
@@ -656,6 +716,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "c1e51f764a60"
|
||||
@@ -665,6 +726,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "fa686a54047c"
|
||||
@@ -688,9 +750,10 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "SsjYFLvNymc0"
|
||||
"id": "80b3fd2ace09"
|
||||
},
|
||||
"source": [
|
||||
"NOTE: The model weights will be downloaded after the deployment succeeds. Thus additional 5 minutes of waiting time is needed **after** the above model deployment step succeeds and before you run the next step below. Otherwise you might see a `ServiceUnavailable: 503 502:Bad Gateway` error when you send requests to the endpoint."
|
||||
@@ -720,6 +783,7 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "ed3795d474b9"
|
||||
|
||||
+51
-114
@@ -24,7 +24,6 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "1e9c07efb6ac"
|
||||
@@ -49,13 +48,12 @@
|
||||
" <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 GPU notebook with preinstalled HuggingFace/transformer libraries is recommended)\n",
|
||||
" (a Python-3 CPU notebook is recommended)\n",
|
||||
" </td>\n",
|
||||
"</table>"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "cd8433ec804a"
|
||||
@@ -63,14 +61,13 @@
|
||||
"source": [
|
||||
"## Overview\n",
|
||||
"\n",
|
||||
"This notebook demonstrates running local inference for [runwayml/stable-diffusion-inpainting](https://huggingface.co/runwayml/stable-diffusion-inpainting) on either [Colab](https://colab.research.google.com) or [Vertex AI Workbench](https://cloud.google.com/vertex-ai-workbench). This notebook also demonstrates finetuning runwayml/stable-diffusion-inpainting with [Dreambooth](https://huggingface.co/docs/diffusers/training/dreambooth) and deploying it on Vertex-AI for online prediction.\n",
|
||||
"This notebook demonstrates finetuning [runwayml/stable-diffusion-inpainting](https://huggingface.co/runwayml/stable-diffusion-inpainting) with [Dreambooth](https://huggingface.co/docs/diffusers/training/dreambooth) and deploying it on Vertex-AI for online prediction.\n",
|
||||
"\n",
|
||||
"### Objective\n",
|
||||
"\n",
|
||||
"- Run local predictions for image-inpainting with serving dockers.\n",
|
||||
"- Finetune the stable-diffusion-inpainting model with [Dreambooth](https://huggingface.co/docs/diffusers/training/dreambooth).\n",
|
||||
"- Upload the model to [Vertex AI Model Registry](https://cloud.google.com/vertex-ai/docs/model-registry/introduction).\n",
|
||||
"- Deploy the model to a [Vertex AI Endpoint resource](https://cloud.google.com/vertex-ai/docs/predictions/using-private-endpoints).\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-inpainting.\n",
|
||||
"\n",
|
||||
"### Costs\n",
|
||||
@@ -84,36 +81,56 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "Gl3bjJsV3k4J"
|
||||
"id": "264c07757582"
|
||||
},
|
||||
"source": [
|
||||
"## Before you begin\n",
|
||||
"## Setup environment\n",
|
||||
"\n",
|
||||
"**NOTE**: Jupyter runs lines prefixed with `!` as shell commands, and it interpolates Python variables prefixed with `$` into these commands."
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "CaCslNQE37P_"
|
||||
"id": "d73ffa0c0b83"
|
||||
},
|
||||
"source": [
|
||||
"### Setup notebook"
|
||||
"### 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()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "fb671e75ca7b"
|
||||
},
|
||||
"source": [
|
||||
"#### Colab only\n",
|
||||
"Run the following commands for Colab and skip this section if you are using Workbench."
|
||||
"### Install dependencies"
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -124,50 +141,34 @@
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"if \"google.colab\" in str(get_ipython()):\n",
|
||||
" ! pip3 install --upgrade google-cloud-aiplatform\n",
|
||||
" from google.colab import auth as google_auth\n",
|
||||
"\n",
|
||||
" google_auth.authenticate_user()\n",
|
||||
" ! pip3 install --upgrade pip\n",
|
||||
" ! pip3 install torchvision==0.14.1\n",
|
||||
" ! pip3 install transformers==4.27.1\n",
|
||||
" ! pip3 install diffusers==0.15.1\n",
|
||||
" ! pip3 install datasets==2.9.0\n",
|
||||
" ! pip3 install accelerate==0.18.0\n",
|
||||
" ! pip3 install triton==2.0.0.dev20221120\n",
|
||||
" ! pip3 install xformers==0.0.16\n",
|
||||
" # Install gdown for downloading example training images.\n",
|
||||
" ! pip3 install gdown\n",
|
||||
" # Remove wrong cublas version.\n",
|
||||
" ! pip3 uninstall nvidia_cublas_cu11 --yes\n",
|
||||
"\n",
|
||||
" # Restart the notebook kernel after installs.\n",
|
||||
" import IPython\n",
|
||||
"\n",
|
||||
" app = IPython.Application.instance()\n",
|
||||
" app.kernel.do_shutdown(True)"
|
||||
"# Install gdown for downloading example training images.\n",
|
||||
"!pip install gdown"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "JaY__7zz3uWk"
|
||||
"id": "5244aac3d929"
|
||||
},
|
||||
"source": [
|
||||
"#### Workbench only\n",
|
||||
"1. Follow [this link](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_stable_diffusion_inpainting.ipynb) to deploy the notebook to a Vertex AI Workbench Instance.\n",
|
||||
"2. Select `Create a new Notebook`.\n",
|
||||
"3. Click `Advanced Options`.\n",
|
||||
"4. Under **Environment**, select `Custom Container` for `Environment`. \n",
|
||||
"5. Set `Docker container image` to `us-docker.pkg.dev/vertex-ai/vertex-vision-model-garden-dockers/transformers-notebook`.\n",
|
||||
"6. Under **Machine configuration**, select 1 `T4` GPU and select `Install NVIDIA GPU driver automatically for me`.\n",
|
||||
"7. Click `Create` to create the Vertex AI Workbench instance."
|
||||
"Restart the notebook kernel after installs."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "567212ff53a6"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import IPython\n",
|
||||
"\n",
|
||||
"app = IPython.Application.instance()\n",
|
||||
"app.kernel.do_shutdown(True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "bb7adab99e41"
|
||||
@@ -187,7 +188,6 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "6c460088b873"
|
||||
@@ -221,7 +221,6 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "e828eb320337"
|
||||
@@ -244,7 +243,6 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "2cc825514deb"
|
||||
@@ -269,7 +267,6 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "0c250872074f"
|
||||
@@ -378,59 +375,6 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "Wx18bDXC2XPR"
|
||||
},
|
||||
"source": [
|
||||
"## Run inferences locally"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "OSYVyAvu2mfN"
|
||||
},
|
||||
"source": [
|
||||
"### Image-inpainting"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "CZ2RkKT32Zj2"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import torch\n",
|
||||
"from diffusers import StableDiffusionInpaintPipeline\n",
|
||||
"\n",
|
||||
"image_url = \"https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png\"\n",
|
||||
"image_response = requests.get(image_url)\n",
|
||||
"init_image = Image.open(BytesIO(image_response.content)).convert(\"RGB\")\n",
|
||||
"display(init_image)\n",
|
||||
"\n",
|
||||
"mask_url = \"https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png\"\n",
|
||||
"mask_response = requests.get(mask_url)\n",
|
||||
"mask_image = Image.open(BytesIO(mask_response.content)).convert(\"RGB\")\n",
|
||||
"\n",
|
||||
"pipe = StableDiffusionInpaintPipeline.from_pretrained(\n",
|
||||
" \"runwayml/stable-diffusion-inpainting\",\n",
|
||||
" revision=\"fp16\",\n",
|
||||
" torch_dtype=torch.float16,\n",
|
||||
")\n",
|
||||
"pipe.to(\"cuda\")\n",
|
||||
"\n",
|
||||
"prompt = \"Face of a yellow cat, high resolution, sitting on a park bench\"\n",
|
||||
"images = pipe(prompt=prompt, image=init_image, mask_image=mask_image).images\n",
|
||||
"display(images[0])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "e70e3519ff8b"
|
||||
@@ -440,7 +384,6 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "f560edbf96c6"
|
||||
@@ -530,7 +473,6 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "90d3c379090e"
|
||||
@@ -540,7 +482,6 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "1cc26e68d7b0"
|
||||
@@ -552,7 +493,6 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "b8bb7d198315"
|
||||
@@ -562,7 +502,6 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "79b66382f849"
|
||||
@@ -590,7 +529,6 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "80b3fd2ace09"
|
||||
@@ -627,7 +565,6 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "f12f8d9c2786"
|
||||
|
||||
@@ -0,0 +1,34 @@
|
||||
tag,notebook,doc
|
||||
"AutoML, Text data",official/automl/automl-text-classification.ipynb,vertex-ai/docs/text-data/classification/train-model
|
||||
"AutoML, Tabular data",official/automl/sdk_automl_tabular_forecasting_batch.ipynb,vertex-ai/docs/tabular-data/forecasting/tutorials-samples
|
||||
"BigQuery, Vertex AI Workbench",official/workbench/exploratory_data_analysis/explore_data_in_bigquery_with_workbench.ipynb,
|
||||
"BigQuery ML, Vertex AI Model Registry, Batch prediction",official/model-registry/bqml-vertexai-model-registry.ipynb,
|
||||
"BigQuery ML, Vertex AI Model Registry, Online prediction",official/bigquery_ml/bqml-online-prediction.ipynb,
|
||||
Custom Training,official/custom/sdk-custom-image-classification-batch.ipynb,
|
||||
Custom Training,official/custom/sdk-custom-image-classification-online.ipynb,
|
||||
Tabular Data,official/automl/automl_forecasting_bqml_arima_plus_comparison.ipynb,vertex-ai/docs/tabular-data/forecasting-arima/overview
|
||||
"AutoML, Tabular Data",official/automl/automl_tabular_on_vertex_pipelines.ipynb,vertex-ai/docs/tabular-data/tabular-workflows/e2e-automl
|
||||
Vertex AI Experiments,official/experiments/comparing_pipeline_runs.ipynb,
|
||||
Vertex AI Experiments,official/experiments/build_model_experimentation_lineage_with_prebuild_code.ipynb,
|
||||
Vertex AI Experiments,official/experiments/comparing_local_trained_models.ipynb,
|
||||
Vertex AI Feature Store,official/feature_store/sdk-feature-store.ipynb,
|
||||
Matching Engine,official/matching_engine/sdk_matching_engine_for_indexing.ipynb,
|
||||
Model Monitoring,official/model_monitoring/model_monitoring.ipynb,
|
||||
Vertex AI Pipelines,official/pipelines/lightweight_functions_component_io_kfp.ipynb,
|
||||
"Vertex AI Pipelines Image data",official/pipelines/google_cloud_pipeline_components_automl_images.ipynb,
|
||||
"Vertex AI Pipelines, Tabular data",official/pipelines/automl_tabular_classification_beans.ipynb,
|
||||
"Vertex AI Pipelines, Tabular data",official/pipelines/google_cloud_pipeline_components_automl_tabular.ipynb,
|
||||
"Vertex AI Pipelines, Text data",official/pipelines/google_cloud_pipeline_components_automl_text.ipynb,
|
||||
Vertex AI Pipelines,official/pipelines/custom_model_training_and_batch_prediction.ipynb,
|
||||
Vertex AI Pipelines,official/pipelines/google_cloud_pipeline_components_model_train_upload_deploy.ipynb,
|
||||
Vertex AI Pipelines,official/pipelines/control_flow_kfp.ipynb,
|
||||
Vertex AI Pipelines,official/pipelines/metrics_viz_run_compare_kfp.ipynb,
|
||||
Vertex AI Pipelines,official/pipelines/pipelines_intro_kfp.ipynb,
|
||||
Vertex AI Vizier,official/vizier/gapic-vizier-multi-objective-optimization.ipynb,vertex-ai/docs/vizier/using-vizier
|
||||
"Vertex Explainable AI, Tabular data",official/explainable_ai/sdk_automl_tabular_binary_classification_batch_explain.ipynb,vertex-ai/docs/explainable-ai/overview
|
||||
"Vertex Explainable AI, Tabular data",official/explainable_ai/sdk_automl_tabular_classification_online_explain.ipynb,vertex-ai/docs/explainable-ai/overview
|
||||
"Vertex Explainable AI, Image data",official/explainable_ai/sdk_custom_image_classification_batch_explain.ipynb,vertex-ai/docs/explainable-ai/overview
|
||||
"Vertex Explainable AI, Image data",official/explainable_ai/sdk_custom_image_classification_online_explain.ipynb,vertex-ai/docs/explainable-ai/overview
|
||||
"Vertex Explainable AI, Tabular data",official/explainable_ai/sdk_custom_tabular_regression_batch_explain.ipynb,vertex-ai/docs/explainable-ai/overview
|
||||
"Vertex Explainable AI, Tabular data",official/explainable_ai/sdk_custom_tabular_regression_online_explain.ipynb,vertex-ai/docs/explainable-ai/overview
|
||||
Vertex ML Metadata,official/ml_metadata/sdk-metric-parameter-tracking-for-custom-jobs.ipynb,
|
||||
|
@@ -437,7 +437,7 @@
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"bq_client = bigquery.Client(project=PROJECT_ID, location=REGION)"
|
||||
"bq_client = bigquery.Client(project=PROJECT_ID)"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@@ -34,18 +34,18 @@
|
||||
"<table align=\"left\">\n",
|
||||
"\n",
|
||||
" <td>\n",
|
||||
" <a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/migration/sdk-automl-object-tracking-batch-prediction.ipynb\">\n",
|
||||
" <a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/migration/UJ15 Vertex SDK AutoML Object Tracking.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/official/migration/sdk-automl-object-tracking-batch-prediction.ipynb\">\n",
|
||||
" <a href=\"https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/migration/UJ15 Vertex SDK AutoML Object Tracking.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/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/GoogleCloudPlatform/vertex-ai-samples/main/notebooks/official/migration/sdk-automl-object-tracking-batch-prediction.ipynb\" target='_blank'>\n",
|
||||
"<a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/GoogleCloudPlatform/vertex-ai-samples/main/notebooks/official/migration/UJ15 Vertex SDK AutoML Object Tracking.ipynb\" target='_blank'>\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",
|
||||
|
||||
+3
-3
@@ -34,18 +34,18 @@
|
||||
"<table align=\"left\">\n",
|
||||
"\n",
|
||||
" <td>\n",
|
||||
" <a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/migration/sdk-automl-text-sentiment-analysis-batch-prediction.ipynb\">\n",
|
||||
" <a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/migration/UJ8 Vertex SDK AutoML Text Sentiment Analysis.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/official/migration/sdk-automl-text-sentiment-analysis-batch-prediction.ipynb\">\n",
|
||||
" <a href=\"https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/migration/UJ8 Vertex SDK AutoML Text Sentiment Analysis.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/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/GoogleCloudPlatform/vertex-ai-samples/main/notebooks/official/migration/sdk-automl-text-sentiment-analysis-batch-prediction.ipynb\" target='_blank'>\n",
|
||||
"<a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/GoogleCloudPlatform/vertex-ai-samples/main/notebooks/official/migration/UJ8 Vertex SDK AutoML Text Sentiment Analysis.ipynb\" target='_blank'>\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",
|
||||
|
||||
@@ -63,7 +63,7 @@
|
||||
"\n",
|
||||
"This notebook demonstrates how to track metrics and parameters for Vertex AI custom training jobs, and how to perform detailed analysis using this data.\n",
|
||||
"\n",
|
||||
"Learn more about [Vertex ML Metadata](https://cloud.google.com/vertex-ai/docs/ml-metadata), [Custom training](https://cloud.google.com/vertex-ai/docs/training/custom-training), and [Vertex AI Experiments](https://cloud.google.com/vertex-ai/docs/experiments/intro-vertex-ai-experiments)."
|
||||
"Learn more about [Vertex ML Metadata](https://cloud.google.com/vertex-ai/docs/ml-metadata) and [Custom training](https://cloud.google.com/vertex-ai/docs/training/custom-training)."
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -81,7 +81,6 @@
|
||||
"- Vertex AI Model\n",
|
||||
"- Vertex AI Endpoint\n",
|
||||
"- Vertex AI Custom Training Job\n",
|
||||
"- Vertex AI Experiments\n",
|
||||
"\n",
|
||||
"The steps performed include:\n",
|
||||
"- Track training parameters and prediction metrics for a custom training job.\n",
|
||||
|
||||
@@ -130,6 +130,39 @@
|
||||
"to generate a cost estimate based on your projected usage."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "setup_local"
|
||||
},
|
||||
"source": [
|
||||
"### Set up your local development environment\n",
|
||||
"\n",
|
||||
"If you are using Colab or Vertex AI Workbench Notebook, your environment already meets all the requirements to run this notebook. You can skip this step.\n",
|
||||
"\n",
|
||||
"Otherwise, make sure your environment meets this notebook's requirements. You need the following:\n",
|
||||
"\n",
|
||||
"- The Cloud Storage SDK\n",
|
||||
"- Git\n",
|
||||
"- Python 3\n",
|
||||
"- virtualenv\n",
|
||||
"- Jupyter notebook running in a virtual environment with Python 3\n",
|
||||
"\n",
|
||||
"The Cloud Storage guide to [Setting up a Python development environment](https://cloud.google.com/python/setup) and the [Jupyter installation guide](https://jupyter.org/install) provide detailed instructions for meeting these requirements. The following steps provide a condensed set of instructions:\n",
|
||||
"\n",
|
||||
"1. [Install and initialize the SDK](https://cloud.google.com/sdk/docs/).\n",
|
||||
"\n",
|
||||
"2. [Install Python 3](https://cloud.google.com/python/setup#installing_python).\n",
|
||||
"\n",
|
||||
"3. [Install virtualenv](Ihttps://cloud.google.com/python/setup#installing_and_using_virtualenv) and create a virtual environment that uses Python 3.\n",
|
||||
"\n",
|
||||
"4. Activate that environment and run `pip3 install Jupyter` in a terminal shell to install Jupyter.\n",
|
||||
"\n",
|
||||
"5. Run `jupyter notebook` on the command line in a terminal shell to launch Jupyter.\n",
|
||||
"\n",
|
||||
"6. Open this notebook in the Jupyter Notebook Dashboard.\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
@@ -149,86 +182,121 @@
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"! pip3 install --upgrade --quiet google-cloud-aiplatform \\\n",
|
||||
" google-cloud-storage \\\n",
|
||||
" 'kfp<2' \\\n",
|
||||
" 'google-cloud-pipeline-components<2'\n",
|
||||
"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 --upgrade google-cloud-aiplatform {USER_FLAG} -q\n",
|
||||
"! pip3 install -U google-cloud-storage {USER_FLAG} -q\n",
|
||||
"! pip3 install {USER_FLAG} 'kfp<2' 'google-cloud-pipeline-components<2' --upgrade -q\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"! pip3 install --upgrade --force-reinstall tensorflow 'kfp<2' google-cloud-aiplatform google-cloud-storage 'google-cloud-pipeline-components<2' -q"
|
||||
"! pip3 install --upgrade --force-reinstall $USER_FLAG tensorflow 'kfp<2' google-cloud-aiplatform google-cloud-storage 'google-cloud-pipeline-components<2' -q"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "58707a750154"
|
||||
"id": "restart"
|
||||
},
|
||||
"source": [
|
||||
"### Colab only: Uncomment the following cell to restart the kernel."
|
||||
"### Restart the kernel\n",
|
||||
"\n",
|
||||
"Once you've installed the additional packages, you need to restart the notebook kernel so it can find the packages."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "f200f10a1da3"
|
||||
"id": "restart"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# Automatically restart kernel after installs so that your environment can access the new packages\n",
|
||||
"# import IPython\n",
|
||||
"import os\n",
|
||||
"\n",
|
||||
"# app = IPython.Application.instance()\n",
|
||||
"# app.kernel.do_shutdown(True)"
|
||||
"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)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "BF1j6f9HApxa"
|
||||
"id": "before_you_begin:nogpu"
|
||||
},
|
||||
"source": [
|
||||
"## Before you begin\n",
|
||||
"\n",
|
||||
"### GPU runtime\n",
|
||||
"\n",
|
||||
"This tutorial does not require a GPU runtime.\n",
|
||||
"\n",
|
||||
"### 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 $300 free credit towards your compute/storage costs.\n",
|
||||
"\n",
|
||||
"2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
|
||||
"2. [Make sure that billing is enabled for your project.](https://cloud.google.com/billing/docs/how-to/modify-project)\n",
|
||||
"\n",
|
||||
"3. [Enable the Vertex AI API]\n",
|
||||
"3. [Enable the Vertex AI APIs, Compute Engine APIs, and Cloud Storage.](https://console.cloud.google.com/flows/enableapi?apiid=ml.googleapis.com,compute_component,storage-component.googleapis.com)\n",
|
||||
"\n",
|
||||
"4. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "WReHDGG5g0XY"
|
||||
},
|
||||
"source": [
|
||||
"#### Set your project ID\n",
|
||||
"4. [The Google Cloud SDK](https://cloud.google.com/sdk) is already installed in Google Cloud Notebook.\n",
|
||||
"\n",
|
||||
"**If you don't know your project ID**, try the following:\n",
|
||||
"* Run `gcloud config list`.\n",
|
||||
"* Run `gcloud projects list`.\n",
|
||||
"* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
|
||||
"5. Enter your project ID in the cell below. Then run the cell to make sure the\n",
|
||||
"Cloud SDK uses the right project for all the commands in this notebook.\n",
|
||||
"\n",
|
||||
"**Note**: Jupyter runs lines prefixed with `!` as shell commands, and it interpolates Python variables prefixed with `$`."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "oM1iC_MfAts1"
|
||||
"id": "set_project_id"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"PROJECT_ID = \"[your-project-id]\" # @param {type:\"string\"}\n",
|
||||
"\n",
|
||||
"# Set the project id\n",
|
||||
"! gcloud config set project {PROJECT_ID}"
|
||||
"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": "7NKIeGOFhtvI"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"!gcloud config set project {PROJECT_ID}"
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -239,7 +307,16 @@
|
||||
"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)."
|
||||
"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)."
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -250,84 +327,154 @@
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"REGION = \"us-central1\" # @param {type: \"string\"}"
|
||||
"REGION = \"[your-region]\" # @param {type: \"string\"}\n",
|
||||
"\n",
|
||||
"if REGION == \"[your-region]\":\n",
|
||||
" REGION = \"us-central1\""
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "sBCra4QMA2wR"
|
||||
"id": "timestamp"
|
||||
},
|
||||
"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": "wJjft8z1IA81"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import random\n",
|
||||
"import string\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"# Generate a uuid of a specifed length(default=8)\n",
|
||||
"def generate_uuid(length: int = 8) -> str:\n",
|
||||
" return \"\".join(random.choices(string.ascii_lowercase + string.digits, k=length))\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"UUID = generate_uuid()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "gcp_authenticate"
|
||||
},
|
||||
"source": [
|
||||
"### Authenticate your Google Cloud account\n",
|
||||
"\n",
|
||||
"Depending on your Jupyter environment, you may have to manually authenticate. Follow the relevant instructions below.\n",
|
||||
"**If you are using Vertex AI Workbench Notebook**, your environment is already authenticated. Skip this step.\n",
|
||||
"\n",
|
||||
"**1. Vertex AI Workbench**\n",
|
||||
"* Do nothing as you are already authenticated.\n",
|
||||
"**If you are using Colab**, run the cell below and follow the instructions\n",
|
||||
"when prompted to authenticate your account via oAuth.\n",
|
||||
"\n",
|
||||
"**2. Local JupyterLab instance, uncomment and run:**"
|
||||
"**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."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "254614fa0c46"
|
||||
"id": "gcp_authenticate"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# ! gcloud auth login"
|
||||
"# 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 = \"google.colab\" in sys.modules\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",
|
||||
" 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 ''"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "ef21552ccea8"
|
||||
},
|
||||
"source": [
|
||||
"**3. Colab, uncomment and run:**"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "603adbbf0532"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"IS_COLAB = False\n",
|
||||
"# from google.colab import auth\n",
|
||||
"# auth.authenticate_user()\n",
|
||||
"# IS_COLAB = True"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "f6b2ccc891ed"
|
||||
},
|
||||
"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"
|
||||
"id": "bucket:mbsdk"
|
||||
},
|
||||
"source": [
|
||||
"### Create a Cloud Storage bucket\n",
|
||||
"\n",
|
||||
"Create a storage bucket to store intermediate artifacts such as datasets."
|
||||
"**The following steps are required, regardless of your notebook environment.**\n",
|
||||
"\n",
|
||||
"When you initialize the Vertex AI 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."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "bucket"
|
||||
},
|
||||
"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 = \"gs://\" + BUCKET_NAME"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "-EcIXiGsCePi"
|
||||
"id": "create_bucket"
|
||||
},
|
||||
"source": [
|
||||
"**Only if your bucket doesn't already exist**: Run the following cell to create your Cloud Storage bucket."
|
||||
@@ -337,11 +484,31 @@
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "MzGDU7TWdts_"
|
||||
"id": "create_bucket"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"BUCKET_URI = f\"gs://your-bucket-name-{PROJECT_ID}-unique\" # @param {type:\"string\"}"
|
||||
"! 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": "validate_bucket"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"! gsutil ls -al $BUCKET_URI"
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -1066,7 +1233,7 @@
|
||||
" pipeline_func=pipeline, package_path=\"custom_model_training_spec.json\"\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"DISPLAY_NAME = \"cifar10\"\n",
|
||||
"DISPLAY_NAME = \"cifar10_\" + UUID\n",
|
||||
"\n",
|
||||
"job = aip.PipelineJob(\n",
|
||||
" display_name=DISPLAY_NAME,\n",
|
||||
|
||||
@@ -54,7 +54,6 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"attachments": {},
|
||||
"cell_type": "markdown",
|
||||
"metadata": {
|
||||
"id": "tvgnzT1CKxrO"
|
||||
@@ -66,7 +65,7 @@
|
||||
"\n",
|
||||
"To run this notebook, click the link `Open in Vertex AI Workbench` above.\n",
|
||||
"\n",
|
||||
"Learn more about [Vertex AI Workbench](https://cloud.google.com/vertex-ai/docs/workbench/introduction) and [Dataproc Serverless for Spark](https://cloud.google.com/dataproc-serverless/docs/guides/bigquery-connector-spark-example)."
|
||||
"Learn more about [Vertex AI Workbench](https://cloud.google.com/vertex-ai/docs/workbench/introduction) and [Dataproc](https://cloud.google.com/vertex-ai/docs/pipelines/dataproc-component)."
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
Reference in New Issue
Block a user