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# Stable Diffusion
## 论文
`DENOISING DIFFUSION IMPLICIT MODELS`
- https://arxiv.org/pdf/2010.02502
## 模型结构
通过串联或更通用的交叉注意机制来调节LDM
![img](./images/model-structure.jpg)
## 算法原理
通过将图像形成过程分解为去噪自动编码器的顺序应用,扩散模型(DM)在图像数据和其他数据上实现了最先进的合成结果。为了在有限的计算资源上进行DM训练,同时保持其质量和灵活性,我们将其应用于强大的预训练自动编码器的潜在空间。在这种表示上训练扩散模型首次能够在降低复杂性和空间下采样之间达到接近最佳的点,提高了视觉逼真度。通过在模型架构中引入跨注意力层,将扩散模型变成了强大而灵活的生成器,用于文本或边界框等一般条件输入,高分辨率合成以卷积方式成为可能。我们的潜在扩散模型(LDM)在各种任务上实现了极具竞争力的性能,包括无条件图像生成、修复和超分辨率,同时与基于像素的DM相比,显著降低了计算要求。
![img](./images/algorithm.jpg)
## 环境配置
### Docker:
```
docker pull image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-py3.8-dtk24.04.3-ubuntu20.04
docker run --shm-size 10g --network=host --name=stablediffusion_v2-1 --privileged --device=/dev/kfd --device=/dev/dri --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -it image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-py3.8-dtk24.04.3-ubuntu20.04 bash
cd diffusers-0.27.0
python setup.py install
cd examples/text_to_image
pip install -r requirements.txt
```
## 数据集
pokemon-blip-captions <br>
可以从以下网址下载:
- http://113.200.138.88:18080/aidatasets/pokemon-blip-captions
## 训练
### 下载Stable Diffusion v2.1模型
```
模型文件可以从modelscope下载:
- https://www.modelscope.cn/models/AI-ModelScope/stable-diffusion-2-1-base
```
### 单机单卡运行:
```
cd examples/text_to_image
```
运行diffusers示例:
```
bash run.sh
```
### 单机多卡运行:
```
cd examples/text_to_image
```
运行diffusers示例(以四卡为例):
```
bash run-4.sh
```
## result
![img](./images/result.jpg)
### 精度
## 应用场景
### 算法类别
`以文生图`
### 热点应用行业
`绘画,动漫,媒体`
## 源码仓库及问题反馈
## 参考资料
https://github.com/Stability-AI/stablediffusion
name: "\U0001F41B Bug Report"
description: Report a bug on Diffusers
labels: [ "bug" ]
body:
- type: markdown
attributes:
value: |
Thanks a lot for taking the time to file this issue 🤗.
Issues do not only help to improve the library, but also publicly document common problems, questions, workflows for the whole community!
Thus, issues are of the same importance as pull requests when contributing to this library ❤️.
In order to make your issue as **useful for the community as possible**, let's try to stick to some simple guidelines:
- 1. Please try to be as precise and concise as possible.
*Give your issue a fitting title. Assume that someone which very limited knowledge of Diffusers can understand your issue. Add links to the source code, documentation other issues, pull requests etc...*
- 2. If your issue is about something not working, **always** provide a reproducible code snippet. The reader should be able to reproduce your issue by **only copy-pasting your code snippet into a Python shell**.
*The community cannot solve your issue if it cannot reproduce it. If your bug is related to training, add your training script and make everything needed to train public. Otherwise, just add a simple Python code snippet.*
- 3. Add the **minimum** amount of code / context that is needed to understand, reproduce your issue.
*Make the life of maintainers easy. `diffusers` is getting many issues every day. Make sure your issue is about one bug and one bug only. Make sure you add only the context, code needed to understand your issues - nothing more. Generally, every issue is a way of documenting this library, try to make it a good documentation entry.*
- 4. For issues related to community pipelines (i.e., the pipelines located in the `examples/community` folder), please tag the author of the pipeline in your issue thread as those pipelines are not maintained.
- type: markdown
attributes:
value: |
For more in-detail information on how to write good issues you can have a look [here](https://huggingface.co/course/chapter8/5?fw=pt).
- type: textarea
id: bug-description
attributes:
label: Describe the bug
description: A clear and concise description of what the bug is. If you intend to submit a pull request for this issue, tell us in the description. Thanks!
placeholder: Bug description
validations:
required: true
- type: textarea
id: reproduction
attributes:
label: Reproduction
description: Please provide a minimal reproducible code which we can copy/paste and reproduce the issue.
placeholder: Reproduction
validations:
required: true
- type: textarea
id: logs
attributes:
label: Logs
description: "Please include the Python logs if you can."
render: shell
- type: textarea
id: system-info
attributes:
label: System Info
description: Please share your system info with us. You can run the command `diffusers-cli env` and copy-paste its output below.
placeholder: Diffusers version, platform, Python version, ...
validations:
required: true
- type: textarea
id: who-can-help
attributes:
label: Who can help?
description: |
Your issue will be replied to more quickly if you can figure out the right person to tag with @.
If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
All issues are read by one of the core maintainers, so if you don't know who to tag, just leave this blank and
a core maintainer will ping the right person.
Please tag a maximum of 2 people.
Questions on DiffusionPipeline (Saving, Loading, From pretrained, ...):
Questions on pipelines:
- Stable Diffusion @yiyixuxu @DN6 @sayakpaul
- Stable Diffusion XL @yiyixuxu @sayakpaul @DN6
- Kandinsky @yiyixuxu
- ControlNet @sayakpaul @yiyixuxu @DN6
- T2I Adapter @sayakpaul @yiyixuxu @DN6
- IF @DN6
- Text-to-Video / Video-to-Video @DN6 @sayakpaul
- Wuerstchen @DN6
- Other: @yiyixuxu @DN6
Questions on models:
- UNet @DN6 @yiyixuxu @sayakpaul
- VAE @sayakpaul @DN6 @yiyixuxu
- Transformers/Attention @DN6 @yiyixuxu @sayakpaul @DN6
Questions on Schedulers: @yiyixuxu
Questions on LoRA: @sayakpaul
Questions on Textual Inversion: @sayakpaul
Questions on Training:
- DreamBooth @sayakpaul
- Text-to-Image Fine-tuning @sayakpaul
- Textual Inversion @sayakpaul
- ControlNet @sayakpaul
Questions on Tests: @DN6 @sayakpaul @yiyixuxu
Questions on Documentation: @stevhliu
Questions on JAX- and MPS-related things: @pcuenca
Questions on audio pipelines: @DN6
placeholder: "@Username ..."
contact_links:
- name: Questions / Discussions
url: https://github.com/huggingface/diffusers/discussions
about: General usage questions and community discussions
---
name: "\U0001F680 Feature Request"
about: Suggest an idea for this project
title: ''
labels: ''
assignees: ''
---
**Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...].
**Describe the solution you'd like.**
A clear and concise description of what you want to happen.
**Describe alternatives you've considered.**
A clear and concise description of any alternative solutions or features you've considered.
**Additional context.**
Add any other context or screenshots about the feature request here.
---
name: "💬 Feedback about API Design"
about: Give feedback about the current API design
title: ''
labels: ''
assignees: ''
---
**What API design would you like to have changed or added to the library? Why?**
**What use case would this enable or better enable? Can you give us a code example?**
name: "\U0001F31F New Model/Pipeline/Scheduler Addition"
description: Submit a proposal/request to implement a new diffusion model/pipeline/scheduler
labels: [ "New model/pipeline/scheduler" ]
body:
- type: textarea
id: description-request
validations:
required: true
attributes:
label: Model/Pipeline/Scheduler description
description: |
Put any and all important information relative to the model/pipeline/scheduler
- type: checkboxes
id: information-tasks
attributes:
label: Open source status
description: |
Please note that if the model implementation isn't available or if the weights aren't open-source, we are less likely to implement it in `diffusers`.
options:
- label: "The model implementation is available."
- label: "The model weights are available (Only relevant if addition is not a scheduler)."
- type: textarea
id: additional-info
attributes:
label: Provide useful links for the implementation
description: |
Please provide information regarding the implementation, the weights, and the authors.
Please mention the authors by @gh-username if you're aware of their usernames.
---
name: 🌐 Translating a New Language?
about: Start a new translation effort in your language
title: '[<languageCode>] Translating docs to <languageName>'
labels: WIP
assignees: ''
---
<!--
Note: Please search to see if an issue already exists for the language you are trying to translate.
-->
Hi!
Let's bring the documentation to all the <languageName>-speaking community 🌐.
Who would want to translate? Please follow the 🤗 [TRANSLATING guide](https://github.com/huggingface/diffusers/blob/main/docs/TRANSLATING.md). Here is a list of the files ready for translation. Let us know in this issue if you'd like to translate any, and we'll add your name to the list.
Some notes:
* Please translate using an informal tone (imagine you are talking with a friend about Diffusers 🤗).
* Please translate in a gender-neutral way.
* Add your translations to the folder called `<languageCode>` inside the [source folder](https://github.com/huggingface/diffusers/tree/main/docs/source).
* Register your translation in `<languageCode>/_toctree.yml`; please follow the order of the [English version](https://github.com/huggingface/diffusers/blob/main/docs/source/en/_toctree.yml).
* Once you're finished, open a pull request and tag this issue by including #issue-number in the description, where issue-number is the number of this issue. Please ping @stevhliu for review.
* 🙋 If you'd like others to help you with the translation, you can also post in the 🤗 [forums](https://discuss.huggingface.co/c/discussion-related-to-httpsgithubcomhuggingfacediffusers/63).
Thank you so much for your help! 🤗
# What does this PR do?
<!--
Congratulations! You've made it this far! You're not quite done yet though.
Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.
Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change.
Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/diffusers/blob/main/CONTRIBUTING.md)?
- [ ] Did you read our [philosophy doc](https://github.com/huggingface/diffusers/blob/main/PHILOSOPHY.md) (important for complex PRs)?
- [ ] Was this discussed/approved via a GitHub issue or the [forum](https://discuss.huggingface.co/c/discussion-related-to-httpsgithubcomhuggingfacediffusers/63)? Please add a link to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes? Here are the
[documentation guidelines](https://github.com/huggingface/diffusers/tree/main/docs), and
[here are tips on formatting docstrings](https://github.com/huggingface/diffusers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
## Who can review?
Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.
<!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @.
If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
Please tag fewer than 3 people.
Core library:
- Schedulers: @yiyixuxu
- Pipelines: @sayakpaul @yiyixuxu @DN6
- Training examples: @sayakpaul
- Docs: @stevhliu and @sayakpaul
- JAX and MPS: @pcuenca
- Audio: @sanchit-gandhi
- General functionalities: @sayakpaul @yiyixuxu @DN6
Integrations:
- deepspeed: HF Trainer/Accelerate: @pacman100
HF projects:
- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- transformers: [different repo](https://github.com/huggingface/transformers)
- safetensors: [different repo](https://github.com/huggingface/safetensors)
-->
name: Set up conda environment for testing
description: Sets up miniconda in your ${RUNNER_TEMP} environment and gives you the ${CONDA_RUN} environment variable so you don't have to worry about polluting non-empeheral runners anymore
inputs:
python-version:
description: If set to any value, don't use sudo to clean the workspace
required: false
type: string
default: "3.9"
miniconda-version:
description: Miniconda version to install
required: false
type: string
default: "4.12.0"
environment-file:
description: Environment file to install dependencies from
required: false
type: string
default: ""
runs:
using: composite
steps:
# Use the same trick from https://github.com/marketplace/actions/setup-miniconda
# to refresh the cache daily. This is kind of optional though
- name: Get date
id: get-date
shell: bash
run: echo "today=$(/bin/date -u '+%Y%m%d')d" >> $GITHUB_OUTPUT
- name: Setup miniconda cache
id: miniconda-cache
uses: actions/cache@v2
with:
path: ${{ runner.temp }}/miniconda
key: miniconda-${{ runner.os }}-${{ runner.arch }}-${{ inputs.python-version }}-${{ steps.get-date.outputs.today }}
- name: Install miniconda (${{ inputs.miniconda-version }})
if: steps.miniconda-cache.outputs.cache-hit != 'true'
env:
MINICONDA_VERSION: ${{ inputs.miniconda-version }}
shell: bash -l {0}
run: |
MINICONDA_INSTALL_PATH="${RUNNER_TEMP}/miniconda"
mkdir -p "${MINICONDA_INSTALL_PATH}"
case ${RUNNER_OS}-${RUNNER_ARCH} in
Linux-X64)
MINICONDA_ARCH="Linux-x86_64"
;;
macOS-ARM64)
MINICONDA_ARCH="MacOSX-arm64"
;;
macOS-X64)
MINICONDA_ARCH="MacOSX-x86_64"
;;
*)
echo "::error::Platform ${RUNNER_OS}-${RUNNER_ARCH} currently unsupported using this action"
exit 1
;;
esac
MINICONDA_URL="https://repo.anaconda.com/miniconda/Miniconda3-py39_${MINICONDA_VERSION}-${MINICONDA_ARCH}.sh"
curl -fsSL "${MINICONDA_URL}" -o "${MINICONDA_INSTALL_PATH}/miniconda.sh"
bash "${MINICONDA_INSTALL_PATH}/miniconda.sh" -b -u -p "${MINICONDA_INSTALL_PATH}"
rm -rf "${MINICONDA_INSTALL_PATH}/miniconda.sh"
- name: Update GitHub path to include miniconda install
shell: bash
run: |
MINICONDA_INSTALL_PATH="${RUNNER_TEMP}/miniconda"
echo "${MINICONDA_INSTALL_PATH}/bin" >> $GITHUB_PATH
- name: Setup miniconda env cache (with env file)
id: miniconda-env-cache-env-file
if: ${{ runner.os }} == 'macOS' && ${{ inputs.environment-file }} != ''
uses: actions/cache@v2
with:
path: ${{ runner.temp }}/conda-python-${{ inputs.python-version }}
key: miniconda-env-${{ runner.os }}-${{ runner.arch }}-${{ inputs.python-version }}-${{ steps.get-date.outputs.today }}-${{ hashFiles(inputs.environment-file) }}
- name: Setup miniconda env cache (without env file)
id: miniconda-env-cache
if: ${{ runner.os }} == 'macOS' && ${{ inputs.environment-file }} == ''
uses: actions/cache@v2
with:
path: ${{ runner.temp }}/conda-python-${{ inputs.python-version }}
key: miniconda-env-${{ runner.os }}-${{ runner.arch }}-${{ inputs.python-version }}-${{ steps.get-date.outputs.today }}
- name: Setup conda environment with python (v${{ inputs.python-version }})
if: steps.miniconda-env-cache-env-file.outputs.cache-hit != 'true' && steps.miniconda-env-cache.outputs.cache-hit != 'true'
shell: bash
env:
PYTHON_VERSION: ${{ inputs.python-version }}
ENV_FILE: ${{ inputs.environment-file }}
run: |
CONDA_BASE_ENV="${RUNNER_TEMP}/conda-python-${PYTHON_VERSION}"
ENV_FILE_FLAG=""
if [[ -f "${ENV_FILE}" ]]; then
ENV_FILE_FLAG="--file ${ENV_FILE}"
elif [[ -n "${ENV_FILE}" ]]; then
echo "::warning::Specified env file (${ENV_FILE}) not found, not going to include it"
fi
conda create \
--yes \
--prefix "${CONDA_BASE_ENV}" \
"python=${PYTHON_VERSION}" \
${ENV_FILE_FLAG} \
cmake=3.22 \
conda-build=3.21 \
ninja=1.10 \
pkg-config=0.29 \
wheel=0.37
- name: Clone the base conda environment and update GitHub env
shell: bash
env:
PYTHON_VERSION: ${{ inputs.python-version }}
CONDA_BASE_ENV: ${{ runner.temp }}/conda-python-${{ inputs.python-version }}
run: |
CONDA_ENV="${RUNNER_TEMP}/conda_environment_${GITHUB_RUN_ID}"
conda create \
--yes \
--prefix "${CONDA_ENV}" \
--clone "${CONDA_BASE_ENV}"
# TODO: conda-build could not be cloned because it hardcodes the path, so it
# could not be cached
conda install --yes -p ${CONDA_ENV} conda-build=3.21
echo "CONDA_ENV=${CONDA_ENV}" >> "${GITHUB_ENV}"
echo "CONDA_RUN=conda run -p ${CONDA_ENV} --no-capture-output" >> "${GITHUB_ENV}"
echo "CONDA_BUILD=conda run -p ${CONDA_ENV} conda-build" >> "${GITHUB_ENV}"
echo "CONDA_INSTALL=conda install -p ${CONDA_ENV}" >> "${GITHUB_ENV}"
- name: Get disk space usage and throw an error for low disk space
shell: bash
run: |
echo "Print the available disk space for manual inspection"
df -h
# Set the minimum requirement space to 4GB
MINIMUM_AVAILABLE_SPACE_IN_GB=4
MINIMUM_AVAILABLE_SPACE_IN_KB=$(($MINIMUM_AVAILABLE_SPACE_IN_GB * 1024 * 1024))
# Use KB to avoid floating point warning like 3.1GB
df -k | tr -s ' ' | cut -d' ' -f 4,9 | while read -r LINE;
do
AVAIL=$(echo $LINE | cut -f1 -d' ')
MOUNT=$(echo $LINE | cut -f2 -d' ')
if [ "$MOUNT" = "/" ]; then
if [ "$AVAIL" -lt "$MINIMUM_AVAILABLE_SPACE_IN_KB" ]; then
echo "There is only ${AVAIL}KB free space left in $MOUNT, which is less than the minimum requirement of ${MINIMUM_AVAILABLE_SPACE_IN_KB}KB. Please help create an issue to PyTorch Release Engineering via https://github.com/pytorch/test-infra/issues and provide the link to the workflow run."
exit 1;
else
echo "There is ${AVAIL}KB free space left in $MOUNT, continue"
fi
fi
done
name: Benchmarking tests
on:
workflow_dispatch:
schedule:
- cron: "30 1 1,15 * *" # every 2 weeks on the 1st and the 15th of every month at 1:30 AM
env:
DIFFUSERS_IS_CI: yes
HF_HOME: /mnt/cache
OMP_NUM_THREADS: 8
MKL_NUM_THREADS: 8
jobs:
torch_pipelines_cuda_benchmark_tests:
name: Torch Core Pipelines CUDA Benchmarking Tests
strategy:
fail-fast: false
max-parallel: 1
runs-on: [single-gpu, nvidia-gpu, a10, ci]
container:
image: diffusers/diffusers-pytorch-cuda
options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/ --gpus 0
steps:
- name: Checkout diffusers
uses: actions/checkout@v3
with:
fetch-depth: 2
- name: NVIDIA-SMI
run: |
nvidia-smi
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
python -m uv pip install pandas peft
- name: Environment
run: |
python utils/print_env.py
- name: Diffusers Benchmarking
env:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.DIFFUSERS_BOT_TOKEN }}
BASE_PATH: benchmark_outputs
run: |
export TOTAL_GPU_MEMORY=$(python -c "import torch; print(torch.cuda.get_device_properties(0).total_memory / (1024**3))")
cd benchmarks && mkdir ${BASE_PATH} && python run_all.py && python push_results.py
- name: Test suite reports artifacts
if: ${{ always() }}
uses: actions/upload-artifact@v2
with:
name: benchmark_test_reports
path: benchmarks/benchmark_outputs
\ No newline at end of file
name: Test, build, and push Docker images
on:
pull_request: # During PRs, we just check if the changes Dockerfiles can be successfully built
branches:
- main
paths:
- "docker/**"
workflow_dispatch:
schedule:
- cron: "0 0 * * *" # every day at midnight
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
env:
REGISTRY: diffusers
CI_SLACK_CHANNEL: ${{ secrets.CI_DOCKER_CHANNEL }}
jobs:
test-build-docker-images:
runs-on: ubuntu-latest
if: github.event_name == 'pull_request'
steps:
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v1
- name: Check out code
uses: actions/checkout@v3
- name: Find Changed Dockerfiles
id: file_changes
uses: jitterbit/get-changed-files@v1
with:
format: 'space-delimited'
token: ${{ secrets.GITHUB_TOKEN }}
- name: Build Changed Docker Images
run: |
CHANGED_FILES="${{ steps.file_changes.outputs.all }}"
for FILE in $CHANGED_FILES; do
if [[ "$FILE" == docker/*Dockerfile ]]; then
DOCKER_PATH="${FILE%/Dockerfile}"
DOCKER_TAG=$(basename "$DOCKER_PATH")
echo "Building Docker image for $DOCKER_TAG"
docker build -t "$DOCKER_TAG" "$DOCKER_PATH"
fi
done
if: steps.file_changes.outputs.all != ''
build-and-push-docker-images:
runs-on: ubuntu-latest
if: github.event_name != 'pull_request'
permissions:
contents: read
packages: write
strategy:
fail-fast: false
matrix:
image-name:
- diffusers-pytorch-cpu
- diffusers-pytorch-cuda
- diffusers-pytorch-compile-cuda
- diffusers-pytorch-xformers-cuda
- diffusers-flax-cpu
- diffusers-flax-tpu
- diffusers-onnxruntime-cpu
- diffusers-onnxruntime-cuda
steps:
- name: Checkout repository
uses: actions/checkout@v3
- name: Login to Docker Hub
uses: docker/login-action@v2
with:
username: ${{ env.REGISTRY }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
- name: Build and push
uses: docker/build-push-action@v3
with:
no-cache: true
context: ./docker/${{ matrix.image-name }}
push: true
tags: ${{ env.REGISTRY }}/${{ matrix.image-name }}:latest
- name: Post to a Slack channel
id: slack
uses: slackapi/slack-github-action@6c661ce58804a1a20f6dc5fbee7f0381b469e001
with:
# Slack channel id, channel name, or user id to post message.
# See also: https://api.slack.com/methods/chat.postMessage#channels
channel-id: ${{ env.CI_SLACK_CHANNEL }}
# For posting a rich message using Block Kit
payload: |
{
"text": "${{ matrix.image-name }} Docker Image build result: ${{ job.status }}\n${{ github.event.head_commit.url }}",
"blocks": [
{
"type": "section",
"text": {
"type": "mrkdwn",
"text": "${{ matrix.image-name }} Docker Image build result: ${{ job.status }}\n${{ github.event.head_commit.url }}"
}
}
]
}
env:
SLACK_BOT_TOKEN: ${{ secrets.SLACK_CIFEEDBACK_BOT_TOKEN }}
name: Build documentation
on:
push:
branches:
- main
- doc-builder*
- v*-release
- v*-patch
paths:
- "src/diffusers/**.py"
- "examples/**"
- "docs/**"
jobs:
build:
uses: huggingface/doc-builder/.github/workflows/build_main_documentation.yml@main
with:
commit_sha: ${{ github.sha }}
install_libgl1: true
package: diffusers
notebook_folder: diffusers_doc
languages: en ko zh ja pt
secrets:
token: ${{ secrets.HUGGINGFACE_PUSH }}
hf_token: ${{ secrets.HF_DOC_BUILD_PUSH }}
name: Build PR Documentation
on:
pull_request:
paths:
- "src/diffusers/**.py"
- "examples/**"
- "docs/**"
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
build:
uses: huggingface/doc-builder/.github/workflows/build_pr_documentation.yml@main
with:
commit_sha: ${{ github.event.pull_request.head.sha }}
pr_number: ${{ github.event.number }}
install_libgl1: true
package: diffusers
languages: en ko zh ja pt
name: Nightly tests on main
on:
schedule:
- cron: "0 0 * * *" # every day at midnight
env:
DIFFUSERS_IS_CI: yes
HF_HOME: /mnt/cache
OMP_NUM_THREADS: 8
MKL_NUM_THREADS: 8
PYTEST_TIMEOUT: 600
RUN_SLOW: yes
RUN_NIGHTLY: yes
SLACK_API_TOKEN: ${{ secrets.SLACK_CIFEEDBACK_BOT_TOKEN }}
jobs:
run_nightly_tests:
strategy:
fail-fast: false
matrix:
config:
- name: Nightly PyTorch CUDA tests on Ubuntu
framework: pytorch
runner: docker-gpu
image: diffusers/diffusers-pytorch-cuda
report: torch_cuda
- name: Nightly Flax TPU tests on Ubuntu
framework: flax
runner: docker-tpu
image: diffusers/diffusers-flax-tpu
report: flax_tpu
- name: Nightly ONNXRuntime CUDA tests on Ubuntu
framework: onnxruntime
runner: docker-gpu
image: diffusers/diffusers-onnxruntime-cuda
report: onnx_cuda
name: ${{ matrix.config.name }}
runs-on: ${{ matrix.config.runner }}
container:
image: ${{ matrix.config.image }}
options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/ ${{ matrix.config.runner == 'docker-tpu' && '--privileged' || '--gpus 0'}}
defaults:
run:
shell: bash
steps:
- name: Checkout diffusers
uses: actions/checkout@v3
with:
fetch-depth: 2
- name: NVIDIA-SMI
if: ${{ matrix.config.runner == 'docker-gpu' }}
run: |
nvidia-smi
- name: Install dependencies
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
python -m uv pip install -U transformers@git+https://github.com/huggingface/transformers
python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate
python -m uv pip install pytest-reportlog
- name: Environment
run: |
python utils/print_env.py
- name: Run nightly PyTorch CUDA tests
if: ${{ matrix.config.framework == 'pytorch' }}
env:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
-s -v -k "not Flax and not Onnx" \
--make-reports=tests_${{ matrix.config.report }} \
--report-log=${{ matrix.config.report }}.log \
tests/
- name: Run nightly Flax TPU tests
if: ${{ matrix.config.framework == 'flax' }}
env:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 0 \
-s -v -k "Flax" \
--make-reports=tests_${{ matrix.config.report }} \
--report-log=${{ matrix.config.report }}.log \
tests/
- name: Run nightly ONNXRuntime CUDA tests
if: ${{ matrix.config.framework == 'onnxruntime' }}
env:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
-s -v -k "Onnx" \
--make-reports=tests_${{ matrix.config.report }} \
--report-log=${{ matrix.config.report }}.log \
tests/
- name: Failure short reports
if: ${{ failure() }}
run: cat reports/tests_${{ matrix.config.report }}_failures_short.txt
- name: Test suite reports artifacts
if: ${{ always() }}
uses: actions/upload-artifact@v2
with:
name: ${{ matrix.config.report }}_test_reports
path: reports
- name: Generate Report and Notify Channel
if: always()
run: |
pip install slack_sdk tabulate
python scripts/log_reports.py >> $GITHUB_STEP_SUMMARY
run_nightly_tests_apple_m1:
name: Nightly PyTorch MPS tests on MacOS
runs-on: [ self-hosted, apple-m1 ]
steps:
- name: Checkout diffusers
uses: actions/checkout@v3
with:
fetch-depth: 2
- name: Clean checkout
shell: arch -arch arm64 bash {0}
run: |
git clean -fxd
- name: Setup miniconda
uses: ./.github/actions/setup-miniconda
with:
python-version: 3.9
- name: Install dependencies
shell: arch -arch arm64 bash {0}
run: |
${CONDA_RUN} python -m pip install --upgrade pip uv
${CONDA_RUN} python -m uv pip install -e [quality,test]
${CONDA_RUN} python -m uv pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cpu
${CONDA_RUN} python -m uv pip install accelerate@git+https://github.com/huggingface/accelerate
${CONDA_RUN} python -m uv pip install pytest-reportlog
- name: Environment
shell: arch -arch arm64 bash {0}
run: |
${CONDA_RUN} python utils/print_env.py
- name: Run nightly PyTorch tests on M1 (MPS)
shell: arch -arch arm64 bash {0}
env:
HF_HOME: /System/Volumes/Data/mnt/cache
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
run: |
${CONDA_RUN} python -m pytest -n 1 -s -v --make-reports=tests_torch_mps \
--report-log=tests_torch_mps.log \
tests/
- name: Failure short reports
if: ${{ failure() }}
run: cat reports/tests_torch_mps_failures_short.txt
- name: Test suite reports artifacts
if: ${{ always() }}
uses: actions/upload-artifact@v2
with:
name: torch_mps_test_reports
path: reports
- name: Generate Report and Notify Channel
if: always()
run: |
pip install slack_sdk tabulate
python scripts/log_reports.py >> $GITHUB_STEP_SUMMARY
name: Notify Slack about a release
on:
workflow_dispatch:
release:
types: [published]
jobs:
build:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Setup Python
uses: actions/setup-python@v4
with:
python-version: '3.8'
- name: Notify Slack about the release
env:
SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK_URL }}
run: pip install requests && python utils/notify_slack_about_release.py
name: Run dependency tests
on:
pull_request:
branches:
- main
paths:
- "src/diffusers/**.py"
push:
branches:
- main
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
check_dependencies:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.8"
- name: Install dependencies
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pip install --upgrade pip uv
python -m uv pip install -e .
python -m uv pip install pytest
- name: Check for soft dependencies
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
pytest tests/others/test_dependencies.py
\ No newline at end of file
name: Run Flax dependency tests
on:
pull_request:
branches:
- main
paths:
- "src/diffusers/**.py"
push:
branches:
- main
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
check_flax_dependencies:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.8"
- name: Install dependencies
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pip install --upgrade pip uv
python -m uv pip install -e .
python -m uv pip install "jax[cpu]>=0.2.16,!=0.3.2"
python -m uv pip install "flax>=0.4.1"
python -m uv pip install "jaxlib>=0.1.65"
python -m uv pip install pytest
- name: Check for soft dependencies
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
pytest tests/others/test_dependencies.py
name: Fast tests for PRs - Test Fetcher
on: workflow_dispatch
env:
DIFFUSERS_IS_CI: yes
OMP_NUM_THREADS: 4
MKL_NUM_THREADS: 4
PYTEST_TIMEOUT: 60
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
setup_pr_tests:
name: Setup PR Tests
runs-on: docker-cpu
container:
image: diffusers/diffusers-pytorch-cpu
options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/
defaults:
run:
shell: bash
outputs:
matrix: ${{ steps.set_matrix.outputs.matrix }}
test_map: ${{ steps.set_matrix.outputs.test_map }}
steps:
- name: Checkout diffusers
uses: actions/checkout@v3
with:
fetch-depth: 0
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
- name: Environment
run: |
python utils/print_env.py
echo $(git --version)
- name: Fetch Tests
run: |
python utils/tests_fetcher.py | tee test_preparation.txt
- name: Report fetched tests
uses: actions/upload-artifact@v3
with:
name: test_fetched
path: test_preparation.txt
- id: set_matrix
name: Create Test Matrix
# The `keys` is used as GitHub actions matrix for jobs, i.e. `models`, `pipelines`, etc.
# The `test_map` is used to get the actual identified test files under each key.
# If no test to run (so no `test_map.json` file), create a dummy map (empty matrix will fail)
run: |
if [ -f test_map.json ]; then
keys=$(python3 -c 'import json; fp = open("test_map.json"); test_map = json.load(fp); fp.close(); d = list(test_map.keys()); print(json.dumps(d))')
test_map=$(python3 -c 'import json; fp = open("test_map.json"); test_map = json.load(fp); fp.close(); print(json.dumps(test_map))')
else
keys=$(python3 -c 'keys = ["dummy"]; print(keys)')
test_map=$(python3 -c 'test_map = {"dummy": []}; print(test_map)')
fi
echo $keys
echo $test_map
echo "matrix=$keys" >> $GITHUB_OUTPUT
echo "test_map=$test_map" >> $GITHUB_OUTPUT
run_pr_tests:
name: Run PR Tests
needs: setup_pr_tests
if: contains(fromJson(needs.setup_pr_tests.outputs.matrix), 'dummy') != true
strategy:
fail-fast: false
max-parallel: 2
matrix:
modules: ${{ fromJson(needs.setup_pr_tests.outputs.matrix) }}
runs-on: docker-cpu
container:
image: diffusers/diffusers-pytorch-cpu
options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/
defaults:
run:
shell: bash
steps:
- name: Checkout diffusers
uses: actions/checkout@v3
with:
fetch-depth: 2
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pip install -e [quality,test]
python -m pip install accelerate
- name: Environment
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python utils/print_env.py
- name: Run all selected tests on CPU
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 2 --dist=loadfile -v --make-reports=${{ matrix.modules }}_tests_cpu ${{ fromJson(needs.setup_pr_tests.outputs.test_map)[matrix.modules] }}
- name: Failure short reports
if: ${{ failure() }}
continue-on-error: true
run: |
cat reports/${{ matrix.modules }}_tests_cpu_stats.txt
cat reports/${{ matrix.modules }}_tests_cpu_failures_short.txt
- name: Test suite reports artifacts
if: ${{ always() }}
uses: actions/upload-artifact@v3
with:
name: ${{ matrix.modules }}_test_reports
path: reports
run_staging_tests:
strategy:
fail-fast: false
matrix:
config:
- name: Hub tests for models, schedulers, and pipelines
framework: hub_tests_pytorch
runner: docker-cpu
image: diffusers/diffusers-pytorch-cpu
report: torch_hub
name: ${{ matrix.config.name }}
runs-on: ${{ matrix.config.runner }}
container:
image: ${{ matrix.config.image }}
options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/
defaults:
run:
shell: bash
steps:
- name: Checkout diffusers
uses: actions/checkout@v3
with:
fetch-depth: 2
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pip install -e [quality,test]
- name: Environment
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python utils/print_env.py
- name: Run Hub tests for models, schedulers, and pipelines on a staging env
if: ${{ matrix.config.framework == 'hub_tests_pytorch' }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
HUGGINGFACE_CO_STAGING=true python -m pytest \
-m "is_staging_test" \
--make-reports=tests_${{ matrix.config.report }} \
tests
- name: Failure short reports
if: ${{ failure() }}
run: cat reports/tests_${{ matrix.config.report }}_failures_short.txt
- name: Test suite reports artifacts
if: ${{ always() }}
uses: actions/upload-artifact@v2
with:
name: pr_${{ matrix.config.report }}_test_reports
path: reports
name: Fast tests for PRs - PEFT backend
on:
pull_request:
branches:
- main
paths:
- "src/diffusers/**.py"
- "tests/**.py"
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
env:
DIFFUSERS_IS_CI: yes
OMP_NUM_THREADS: 4
MKL_NUM_THREADS: 4
PYTEST_TIMEOUT: 60
jobs:
check_code_quality:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.8"
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install .[quality]
- name: Check quality
run: |
ruff check examples tests src utils scripts
ruff format examples tests src utils scripts --check
check_repository_consistency:
needs: check_code_quality
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.8"
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install .[quality]
- name: Check quality
run: |
python utils/check_copies.py
python utils/check_dummies.py
make deps_table_check_updated
run_fast_tests:
needs: [check_code_quality, check_repository_consistency]
strategy:
fail-fast: false
matrix:
lib-versions: ["main", "latest"]
name: LoRA - ${{ matrix.lib-versions }}
runs-on: docker-cpu
container:
image: diffusers/diffusers-pytorch-cpu
options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/
defaults:
run:
shell: bash
steps:
- name: Checkout diffusers
uses: actions/checkout@v3
with:
fetch-depth: 2
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
if [ "${{ matrix.lib-versions }}" == "main" ]; then
python -m uv pip install -U peft@git+https://github.com/huggingface/peft.git
python -m uv pip install -U transformers@git+https://github.com/huggingface/transformers.git
python -m uv pip install -U accelerate@git+https://github.com/huggingface/accelerate.git
else
python -m uv pip install -U peft transformers accelerate
fi
- name: Environment
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python utils/print_env.py
- name: Run fast PyTorch LoRA CPU tests with PEFT backend
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 1 --max-worker-restart=0 --dist=loadfile \
-s -v \
--make-reports=tests_${{ matrix.config.report }} \
tests/lora/test_lora_layers_peft.py
name: Fast tests for PRs
on:
pull_request:
branches:
- main
paths:
- "src/diffusers/**.py"
- "benchmarks/**.py"
- "examples/**.py"
- "scripts/**.py"
- "tests/**.py"
- ".github/**.yml"
- "utils/**.py"
push:
branches:
- ci-*
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
env:
DIFFUSERS_IS_CI: yes
OMP_NUM_THREADS: 4
MKL_NUM_THREADS: 4
PYTEST_TIMEOUT: 60
jobs:
check_code_quality:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.8"
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install .[quality]
- name: Check quality
run: |
ruff check examples tests src utils scripts
ruff format examples tests src utils scripts --check
check_repository_consistency:
needs: check_code_quality
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.8"
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install .[quality]
- name: Check quality
run: |
python utils/check_copies.py
python utils/check_dummies.py
make deps_table_check_updated
run_fast_tests:
needs: [check_code_quality, check_repository_consistency]
strategy:
fail-fast: false
matrix:
config:
- name: Fast PyTorch Pipeline CPU tests
framework: pytorch_pipelines
runner: docker-cpu
image: diffusers/diffusers-pytorch-cpu
report: torch_cpu_pipelines
- name: Fast PyTorch Models & Schedulers CPU tests
framework: pytorch_models
runner: docker-cpu
image: diffusers/diffusers-pytorch-cpu
report: torch_cpu_models_schedulers
- name: Fast Flax CPU tests
framework: flax
runner: docker-cpu
image: diffusers/diffusers-flax-cpu
report: flax_cpu
- name: PyTorch Example CPU tests
framework: pytorch_examples
runner: docker-cpu
image: diffusers/diffusers-pytorch-cpu
report: torch_example_cpu
name: ${{ matrix.config.name }}
runs-on: ${{ matrix.config.runner }}
container:
image: ${{ matrix.config.image }}
options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/
defaults:
run:
shell: bash
steps:
- name: Checkout diffusers
uses: actions/checkout@v3
with:
fetch-depth: 2
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
python -m uv pip install accelerate
- name: Environment
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python utils/print_env.py
- name: Run fast PyTorch Pipeline CPU tests
if: ${{ matrix.config.framework == 'pytorch_pipelines' }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 2 --max-worker-restart=0 --dist=loadfile \
-s -v -k "not Flax and not Onnx" \
--make-reports=tests_${{ matrix.config.report }} \
tests/pipelines
- name: Run fast PyTorch Model Scheduler CPU tests
if: ${{ matrix.config.framework == 'pytorch_models' }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 2 --max-worker-restart=0 --dist=loadfile \
-s -v -k "not Flax and not Onnx and not Dependency" \
--make-reports=tests_${{ matrix.config.report }} \
tests/models tests/schedulers tests/others
- name: Run fast Flax TPU tests
if: ${{ matrix.config.framework == 'flax' }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m pytest -n 2 --max-worker-restart=0 --dist=loadfile \
-s -v -k "Flax" \
--make-reports=tests_${{ matrix.config.report }} \
tests
- name: Run example PyTorch CPU tests
if: ${{ matrix.config.framework == 'pytorch_examples' }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install peft
python -m pytest -n 2 --max-worker-restart=0 --dist=loadfile \
--make-reports=tests_${{ matrix.config.report }} \
examples
- name: Failure short reports
if: ${{ failure() }}
run: cat reports/tests_${{ matrix.config.report }}_failures_short.txt
- name: Test suite reports artifacts
if: ${{ always() }}
uses: actions/upload-artifact@v2
with:
name: pr_${{ matrix.config.report }}_test_reports
path: reports
run_staging_tests:
needs: [check_code_quality, check_repository_consistency]
strategy:
fail-fast: false
matrix:
config:
- name: Hub tests for models, schedulers, and pipelines
framework: hub_tests_pytorch
runner: docker-cpu
image: diffusers/diffusers-pytorch-cpu
report: torch_hub
name: ${{ matrix.config.name }}
runs-on: ${{ matrix.config.runner }}
container:
image: ${{ matrix.config.image }}
options: --shm-size "16gb" --ipc host -v /mnt/hf_cache:/mnt/cache/
defaults:
run:
shell: bash
steps:
- name: Checkout diffusers
uses: actions/checkout@v3
with:
fetch-depth: 2
- name: Install dependencies
run: |
apt-get update && apt-get install libsndfile1-dev libgl1 -y
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python -m uv pip install -e [quality,test]
- name: Environment
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
python utils/print_env.py
- name: Run Hub tests for models, schedulers, and pipelines on a staging env
if: ${{ matrix.config.framework == 'hub_tests_pytorch' }}
run: |
python -m venv /opt/venv && export PATH="/opt/venv/bin:$PATH"
HUGGINGFACE_CO_STAGING=true python -m pytest \
-m "is_staging_test" \
--make-reports=tests_${{ matrix.config.report }} \
tests
- name: Failure short reports
if: ${{ failure() }}
run: cat reports/tests_${{ matrix.config.report }}_failures_short.txt
- name: Test suite reports artifacts
if: ${{ always() }}
uses: actions/upload-artifact@v2
with:
name: pr_${{ matrix.config.report }}_test_reports
path: reports
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