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Fix typos, improve, update at main-page files and .github files (#5588)

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* Update keywords; remove version cuz it changes constantly?

* Update if necessary

* Fix typos and links

* version_range_max from PyTorch's setup.py; fix typos; 1 checklist is enough?

* Fix a typo

* Fix typos

* There is already a Blank issue link at the bottom of the page; direct to Diffusers' forum

* Add 🌐 Translating a New Language? page

* Update .github/ISSUE_TEMPLATE/translate.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update PHILOSOPHY.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update PHILOSOPHY.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update PHILOSOPHY.md

* Update PHILOSOPHY.md

* Update CONTRIBUTING.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update CONTRIBUTING.md

* Update CONTRIBUTING.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update PHILOSOPHY.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update PHILOSOPHY.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update README.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Add X account link

* Update setup.py

* Update CITATION.cff

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
This commit is contained in:
M. Tolga Cangöz
2023-11-14 22:46:52 +03:00
committed by GitHub
parent c7260ce253
commit 3b37488fa3
16 changed files with 182 additions and 116 deletions
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12
.github/ISSUE_TEMPLATE/bug-report.yml vendored
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@@ -1,5 +1,5 @@
name: "\U0001F41B Bug Report"
description: Report a bug on diffusers
description: Report a bug on Diffusers
labels: [ "bug" ]
body:
- type: markdown
@@ -10,7 +10,7 @@ body:
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...*
*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.
@@ -19,7 +19,7 @@ body:
- 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)
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:
@@ -47,7 +47,7 @@ body:
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, ...
placeholder: Diffusers version, platform, Python version, ...
validations:
required: true
- type: textarea
@@ -55,7 +55,7 @@ body:
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 @
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
@@ -66,7 +66,7 @@ body:
Questions on DiffusionPipeline (Saving, Loading, From pretrained, ...):
Questions on pipelines:
- Stable Diffusion @yiyixuxu @DN6 @patrickvonplaten @sayakpaul @patrickvonplaten
- Stable Diffusion @yiyixuxu @DN6 @sayakpaul @patrickvonplaten
- Stable Diffusion XL @yiyixuxu @sayakpaul @DN6 @patrickvonplaten
- Kandinsky @yiyixuxu @patrickvonplaten
- ControlNet @sayakpaul @yiyixuxu @DN6 @patrickvonplaten

5
.github/ISSUE_TEMPLATE/config.yml vendored
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@@ -1,7 +1,4 @@
contact_links:
- name: Blank issue
url: https://github.com/huggingface/diffusers/issues/new
about: Other
- name: Forum
url: https://discuss.huggingface.co/
url: https://discuss.huggingface.co/c/discussion-related-to-httpsgithubcomhuggingfacediffusers/63
about: General usage questions and community discussions

10
.github/ISSUE_TEMPLATE/feature_request.md vendored
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@@ -1,5 +1,5 @@
---
name: "\U0001F680 Feature request"
name: "\U0001F680 Feature Request"
about: Suggest an idea for this project
title: ''
labels: ''
@@ -8,13 +8,13 @@ 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 [...]
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...].
**Describe the solution you'd like**
**Describe the solution you'd like.**
A clear and concise description of what you want to happen.
**Describe alternatives you've considered**
**Describe alternatives you've considered.**
A clear and concise description of any alternative solutions or features you've considered.
**Additional context**
**Additional context.**
Add any other context or screenshots about the feature request here.

6
.github/ISSUE_TEMPLATE/new-model-addition.yml vendored
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@@ -1,5 +1,5 @@
name: "\U0001F31F New model/pipeline/scheduler addition"
description: Submit a proposal/request to implement a new diffusion model / pipeline / scheduler
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:
@@ -19,7 +19,7 @@ body:
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 implementation is available."
- label: "The model weights are available (Only relevant if addition is not a scheduler)."
- type: textarea

29
.github/ISSUE_TEMPLATE/translate.md vendored Normal file
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@@ -0,0 +1,29 @@
---
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! 🤗

6
.github/PULL_REQUEST_TEMPLATE.md vendored
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@@ -19,10 +19,10 @@ Fixes # (issue)
- [ ] 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/)? Please add a link to it if that's the case.
- [ ] 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/transformers/tree/main/docs#writing-source-documentation).
[here are tips on formatting docstrings](https://github.com/huggingface/diffusers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?
@@ -31,7 +31,7 @@ Fixes # (issue)
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 @
<!-- 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.

2
.github/actions/setup-miniconda/action.yml vendored
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@@ -4,7 +4,7 @@ description: Sets up miniconda in your ${RUNNER_TEMP} environment and gives you
inputs:
python-version:
description: If set to any value, dont use sudo to clean the workspace
description: If set to any value, don't use sudo to clean the workspace
required: false
type: string
default: "3.9"

8
.gitignore vendored
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@@ -1,4 +1,4 @@
# Initially taken from Github's Python gitignore file
# Initially taken from GitHub's Python gitignore file
# Byte-compiled / optimized / DLL files
__pycache__/
@@ -34,7 +34,7 @@ wheels/
MANIFEST
# PyInstaller
# Usually these files are written by a python script from a template
# Usually these files are written by a Python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec
@@ -153,7 +153,7 @@ debug.env
# vim
.*.swp
#ctags
# ctags
tags
# pre-commit
@@ -164,6 +164,7 @@ tags
# DS_Store (MacOS)
.DS_Store
# RL pipelines may produce mp4 outputs
*.mp4
@@ -173,4 +174,5 @@ tags
# ruff
.ruff_cache
# wandb
wandb

2
CITATION.cff
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@@ -31,10 +31,12 @@ keywords:
- deep-learning
- pytorch
- image-generation
- hacktoberfest
- diffusion
- text2image
- image2image
- score-based-generative-modeling
- stable-diffusion
- stable-diffusion-diffusers
license: Apache-2.0
version: 0.12.1

8
CODE_OF_CONDUCT.md
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@@ -7,7 +7,7 @@ We as members, contributors, and leaders pledge to make participation in our
community a harassment-free experience for everyone, regardless of age, body
size, visible or invisible disability, ethnicity, sex characteristics, gender
identity and expression, level of experience, education, socio-economic status,
nationality, personal appearance, race, religion, or sexual identity
nationality, personal appearance, race, caste, color, religion, or sexual identity
and orientation.
We pledge to act and interact in ways that contribute to an open, welcoming,
@@ -24,7 +24,7 @@ community include:
* Accepting responsibility and apologizing to those affected by our mistakes,
and learning from the experience
* Focusing on what is best not just for us as individuals, but for the
overall diffusers community
overall Diffusers community
Examples of unacceptable behavior include:
@@ -117,8 +117,8 @@ the community.
## Attribution
This Code of Conduct is adapted from the [Contributor Covenant][homepage],
version 2.0, available at
https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.
version 2.1, available at
https://www.contributor-covenant.org/version/2/1/code_of_conduct.html.
Community Impact Guidelines were inspired by [Mozilla's code of conduct
enforcement ladder](https://github.com/mozilla/diversity).

58
CONTRIBUTING.md
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@@ -14,7 +14,7 @@ specific language governing permissions and limitations under the License.
We ❤️ contributions from the open-source community! Everyone is welcome, and all types of participation –not just code– are valued and appreciated. Answering questions, helping others, reaching out, and improving the documentation are all immensely valuable to the community, so don't be afraid and get involved if you're up for it!
Everyone is encouraged to start by saying 👋 in our public Discord channel. We discuss the latest trends in diffusion models, ask questions, show off personal projects, help each other with contributions, or just hang out ☕. <a href="https://Discord.gg/G7tWnz98XR"><img alt="Join us on Discord" src="https://img.shields.io/Discord/823813159592001537?color=5865F2&logo=Discord&logoColor=white"></a>
Everyone is encouraged to start by saying 👋 in our public Discord channel. We discuss the latest trends in diffusion models, ask questions, show off personal projects, help each other with contributions, or just hang out ☕. <a href="https://discord.gg/G7tWnz98XR"><img alt="Join us on Discord" src="https://img.shields.io/discord/823813159592001537?color=5865F2&logo=Discord&logoColor=white"></a>
Whichever way you choose to contribute, we strive to be part of an open, welcoming, and kind community. Please, read our [code of conduct](https://github.com/huggingface/diffusers/blob/main/CODE_OF_CONDUCT.md) and be mindful to respect it during your interactions. We also recommend you become familiar with the [ethical guidelines](https://huggingface.co/docs/diffusers/conceptual/ethical_guidelines) that guide our project and ask you to adhere to the same principles of transparency and responsibility.
@@ -28,11 +28,11 @@ the core library.
In the following, we give an overview of different ways to contribute, ranked by difficulty in ascending order. All of them are valuable to the community.
* 1. Asking and answering questions on [the Diffusers discussion forum](https://discuss.huggingface.co/c/discussion-related-to-httpsgithubcomhuggingfacediffusers) or on [Discord](https://discord.gg/G7tWnz98XR).
* 2. Opening new issues on [the GitHub Issues tab](https://github.com/huggingface/diffusers/issues/new/choose)
* 3. Answering issues on [the GitHub Issues tab](https://github.com/huggingface/diffusers/issues)
* 2. Opening new issues on [the GitHub Issues tab](https://github.com/huggingface/diffusers/issues/new/choose).
* 3. Answering issues on [the GitHub Issues tab](https://github.com/huggingface/diffusers/issues).
* 4. Fix a simple issue, marked by the "Good first issue" label, see [here](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22).
* 5. Contribute to the [documentation](https://github.com/huggingface/diffusers/tree/main/docs/source).
* 6. Contribute a [Community Pipeline](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3Acommunity-examples)
* 6. Contribute a [Community Pipeline](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3Acommunity-examples).
* 7. Contribute to the [examples](https://github.com/huggingface/diffusers/tree/main/examples).
* 8. Fix a more difficult issue, marked by the "Good second issue" label, see [here](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22Good+second+issue%22).
* 9. Add a new pipeline, model, or scheduler, see ["New Pipeline/Model"](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22New+pipeline%2Fmodel%22) and ["New scheduler"](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22New+scheduler%22) issues. For this contribution, please have a look at [Design Philosophy](https://github.com/huggingface/diffusers/blob/main/PHILOSOPHY.md).
@@ -40,7 +40,7 @@ In the following, we give an overview of different ways to contribute, ranked by
As said before, **all contributions are valuable to the community**.
In the following, we will explain each contribution a bit more in detail.
For all contributions 4.-9. you will need to open a PR. It is explained in detail how to do so in [Opening a pull request](#how-to-open-a-pr)
For all contributions 4-9, you will need to open a PR. It is explained in detail how to do so in [Opening a pull request](#how-to-open-a-pr).
### 1. Asking and answering questions on the Diffusers discussion forum or on the Diffusers Discord
@@ -91,12 +91,12 @@ open a new issue nevertheless and link to the related issue.
New issues usually include the following.
#### 2.1. Reproducible, minimal bug reports.
#### 2.1. Reproducible, minimal bug reports
A bug report should always have a reproducible code snippet and be as minimal and concise as possible.
This means in more detail:
- Narrow the bug down as much as you can, **do not just dump your whole code file**
- Format your code
- Narrow the bug down as much as you can, **do not just dump your whole code file**.
- Format your code.
- Do not include any external libraries except for Diffusers depending on them.
- **Always** provide all necessary information about your environment; for this, you can run: `diffusers-cli env` in your shell and copy-paste the displayed information to the issue.
- Explain the issue. If the reader doesn't know what the issue is and why it is an issue, she cannot solve it.
@@ -105,9 +105,9 @@ This means in more detail:
For more information, please have a look through the [How to write a good issue](#how-to-write-a-good-issue) section.
You can open a bug report [here](https://github.com/huggingface/diffusers/issues/new/choose).
You can open a bug report [here](https://github.com/huggingface/diffusers/issues/new?assignees=&labels=bug&projects=&template=bug-report.yml).
#### 2.2. Feature requests.
#### 2.2. Feature requests
A world-class feature request addresses the following points:
@@ -125,21 +125,21 @@ Awesome! Tell us what problem it solved for you.
You can open a feature request [here](https://github.com/huggingface/diffusers/issues/new?assignees=&labels=&template=feature_request.md&title=).
#### 2.3 Feedback.
#### 2.3 Feedback
Feedback about the library design and why it is good or not good helps the core maintainers immensely to build a user-friendly library. To understand the philosophy behind the current design philosophy, please have a look [here](https://huggingface.co/docs/diffusers/conceptual/philosophy). If you feel like a certain design choice does not fit with the current design philosophy, please explain why and how it should be changed. If a certain design choice follows the design philosophy too much, hence restricting use cases, explain why and how it should be changed.
If a certain design choice is very useful for you, please also leave a note as this is great feedback for future design decisions.
You can open an issue about feedback [here](https://github.com/huggingface/diffusers/issues/new?assignees=&labels=&template=feedback.md&title=).
#### 2.4 Technical questions.
#### 2.4 Technical questions
Technical questions are mainly about why certain code of the library was written in a certain way, or what a certain part of the code does. Please make sure to link to the code in question and please provide detail on
why this part of the code is difficult to understand.
You can open an issue about a technical question [here](https://github.com/huggingface/diffusers/issues/new?assignees=&labels=bug&template=bug-report.yml).
#### 2.5 Proposal to add a new model, scheduler, or pipeline.
#### 2.5 Proposal to add a new model, scheduler, or pipeline
If the diffusion model community released a new model, pipeline, or scheduler that you would like to see in the Diffusers library, please provide the following information:
@@ -156,14 +156,14 @@ You can open a request for a model/pipeline/scheduler [here](https://github.com/
Answering issues on GitHub might require some technical knowledge of Diffusers, but we encourage everybody to give it a try even if you are not 100% certain that your answer is correct.
Some tips to give a high-quality answer to an issue:
- Be as concise and minimal as possible
- Be as concise and minimal as possible.
- Stay on topic. An answer to the issue should concern the issue and only the issue.
- Provide links to code, papers, or other sources that prove or encourage your point.
- Answer in code. If a simple code snippet is the answer to the issue or shows how the issue can be solved, please provide a fully reproducible code snippet.
Also, many issues tend to be simply off-topic, duplicates of other issues, or irrelevant. It is of great
help to the maintainers if you can answer such issues, encouraging the author of the issue to be
more precise, provide the link to a duplicated issue or redirect them to [the forum](https://discuss.huggingface.co/c/discussion-related-to-httpsgithubcomhuggingfacediffusers/63) or [Discord](https://discord.gg/G7tWnz98XR)
more precise, provide the link to a duplicated issue or redirect them to [the forum](https://discuss.huggingface.co/c/discussion-related-to-httpsgithubcomhuggingfacediffusers/63) or [Discord](https://discord.gg/G7tWnz98XR).
If you have verified that the issued bug report is correct and requires a correction in the source code,
please have a look at the next sections.
@@ -202,7 +202,7 @@ Please have a look at [this page](https://github.com/huggingface/diffusers/tree/
### 6. Contribute a community pipeline
[Pipelines](https://huggingface.co/docs/diffusers/api/pipelines/overview) are usually the first point of contact between the Diffusers library and the user.
Pipelines are examples of how to use Diffusers [models](https://huggingface.co/docs/diffusers/api/models) and [schedulers](https://huggingface.co/docs/diffusers/api/schedulers/overview).
Pipelines are examples of how to use Diffusers [models](https://huggingface.co/docs/diffusers/api/models/overview) and [schedulers](https://huggingface.co/docs/diffusers/api/schedulers/overview).
We support two types of pipelines:
- Official Pipelines
@@ -242,27 +242,27 @@ We support two types of training examples:
Research training examples are located in [examples/research_projects](https://github.com/huggingface/diffusers/tree/main/examples/research_projects) whereas official training examples include all folders under [examples](https://github.com/huggingface/diffusers/tree/main/examples) except the `research_projects` and `community` folders.
The official training examples are maintained by the Diffusers' core maintainers whereas the research training examples are maintained by the community.
This is because of the same reasons put forward in [6. Contribute a community pipeline](#contribute-a-community-pipeline) for official pipelines vs. community pipelines: It is not feasible for the core maintainers to maintain all possible training methods for diffusion models.
This is because of the same reasons put forward in [6. Contribute a community pipeline](#6-contribute-a-community-pipeline) for official pipelines vs. community pipelines: It is not feasible for the core maintainers to maintain all possible training methods for diffusion models.
If the Diffusers core maintainers and the community consider a certain training paradigm to be too experimental or not popular enough, the corresponding training code should be put in the `research_projects` folder and maintained by the author.
Both official training and research examples consist of a directory that contains one or more training scripts, a requirements.txt file, and a README.md file. In order for the user to make use of the
training examples, it is required to clone the repository:
```
```bash
git clone https://github.com/huggingface/diffusers
```
as well as to install all additional dependencies required for training:
```
```bash
pip install -r /examples/<your-example-folder>/requirements.txt
```
Therefore when adding an example, the `requirements.txt` file shall define all pip dependencies required for your training example so that once all those are installed, the user can run the example's training script. See, for example, the [DreamBooth `requirements.txt` file](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/requirements.txt).
Training examples of the Diffusers library should adhere to the following philosophy:
- All the code necessary to run the examples should be found in a single Python file
- One should be able to run the example from the command line with `python <your-example>.py --args`
- All the code necessary to run the examples should be found in a single Python file.
- One should be able to run the example from the command line with `python <your-example>.py --args`.
- Examples should be kept simple and serve as **an example** on how to use Diffusers for training. The purpose of example scripts is **not** to create state-of-the-art diffusion models, but rather to reproduce known training schemes without adding too much custom logic. As a byproduct of this point, our examples also strive to serve as good educational materials.
To contribute an example, it is highly recommended to look at already existing examples such as [dreambooth](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/train_dreambooth.py) to get an idea of how they should look like.
@@ -281,7 +281,7 @@ If you are contributing to the official training examples, please also make sure
usually more complicated to solve than [Good first issues](https://github.com/huggingface/diffusers/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22).
The issue description usually gives less guidance on how to fix the issue and requires
a decent understanding of the library by the interested contributor.
If you are interested in tackling a second good issue, feel free to open a PR to fix it and link the PR to the issue. If you see that a PR has already been opened for this issue but did not get merged, have a look to understand why it wasn't merged and try to open an improved PR.
If you are interested in tackling a good second issue, feel free to open a PR to fix it and link the PR to the issue. If you see that a PR has already been opened for this issue but did not get merged, have a look to understand why it wasn't merged and try to open an improved PR.
Good second issues are usually more difficult to get merged compared to good first issues, so don't hesitate to ask for help from the core maintainers. If your PR is almost finished the core maintainers can also jump into your PR and commit to it in order to get it merged.
### 9. Adding pipelines, models, schedulers
@@ -337,8 +337,8 @@ to be merged;
9. Add high-coverage tests. No quality testing = no merge.
- If you are adding new `@slow` tests, make sure they pass using
`RUN_SLOW=1 python -m pytest tests/test_my_new_model.py`.
CircleCI does not run the slow tests, but GitHub actions does every night!
10. All public methods must have informative docstrings that work nicely with markdown. See `[pipeline_latent_diffusion.py](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion.py)` for an example.
CircleCI does not run the slow tests, but GitHub Actions does every night!
10. All public methods must have informative docstrings that work nicely with markdown. See [`pipeline_latent_diffusion.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion.py) for an example.
11. Due to the rapidly growing repository, it is important to make sure that no files that would significantly weigh down the repository are added. This includes images, videos, and other non-text files. We prefer to leverage a hf.co hosted `dataset` like
[`hf-internal-testing`](https://huggingface.co/hf-internal-testing) or [huggingface/documentation-images](https://huggingface.co/datasets/huggingface/documentation-images) to place these files.
If an external contribution, feel free to add the images to your PR and ask a Hugging Face member to migrate your images
@@ -364,7 +364,7 @@ under your GitHub user account.
2. Clone your fork to your local disk, and add the base repository as a remote:
```bash
$ git clone git@github.com:<your Github handle>/diffusers.git
$ git clone git@github.com:<your GitHub handle>/diffusers.git
$ cd diffusers
$ git remote add upstream https://github.com/huggingface/diffusers.git
```
@@ -402,7 +402,7 @@ with this command:
$ pip install -e ".[test]"
```
You can run the full test suite with the following command, but it takes
You can also run the full test suite with the following command, but it takes
a beefy machine to produce a result in a decent amount of time now that
Diffusers has grown a lot. Here is the command for it:
@@ -430,7 +430,7 @@ make a commit with `git commit` to record your changes locally:
```bash
$ git add modified_file.py
$ git commit
$ git commit -m "A descriptive message about your changes."
```
It is a good idea to sync your copy of the code with the original
@@ -493,7 +493,7 @@ To avoid pinging the upstream repository which adds reference notes to each upst
when syncing the main branch of a forked repository, please, follow these steps:
1. When possible, avoid syncing with the upstream using a branch and PR on the forked repository. Instead, merge directly into the forked main.
2. If a PR is absolutely necessary, use the following steps after checking out your branch:
```
```bash
$ git checkout -b your-branch-for-syncing
$ git pull --squash --no-commit upstream main
$ git commit -m '<your message without GitHub references>'
@@ -502,4 +502,4 @@ $ git push --set-upstream origin your-branch-for-syncing
### Style guide
For documentation strings, 🧨 Diffusers follows the [google style](https://google.github.io/styleguide/pyguide.html).
For documentation strings, 🧨 Diffusers follows the [Google style](https://google.github.io/styleguide/pyguide.html).

32
PHILOSOPHY.md
View File

@@ -22,7 +22,7 @@ In a nutshell, Diffusers is built to be a natural extension of PyTorch. Therefor
## Usability over Performance
- While Diffusers has many built-in performance-enhancing features (see [Memory and Speed](https://huggingface.co/docs/diffusers/optimization/fp16)), models are always loaded with the highest precision and lowest optimization. Therefore, by default diffusion pipelines are always instantiated on CPU with float32 precision if not otherwise defined by the user. This ensures usability across different platforms and accelerators and means that no complex installations are required to run the library.
- Diffusers aim at being a **light-weight** package and therefore has very few required dependencies, but many soft dependencies that can improve performance (such as `accelerate`, `safetensors`, `onnx`, etc...). We strive to keep the library as lightweight as possible so that it can be added without much concern as a dependency on other packages.
- Diffusers aims to be a **light-weight** package and therefore has very few required dependencies, but many soft dependencies that can improve performance (such as `accelerate`, `safetensors`, `onnx`, etc...). We strive to keep the library as lightweight as possible so that it can be added without much concern as a dependency on other packages.
- Diffusers prefers simple, self-explainable code over condensed, magic code. This means that short-hand code syntaxes such as lambda functions, and advanced PyTorch operators are often not desired.
## Simple over easy
@@ -31,13 +31,13 @@ As PyTorch states, **explicit is better than implicit** and **simple is better t
- We follow PyTorch's API with methods like [`DiffusionPipeline.to`](https://huggingface.co/docs/diffusers/main/en/api/diffusion_pipeline#diffusers.DiffusionPipeline.to) to let the user handle device management.
- Raising concise error messages is preferred to silently correct erroneous input. Diffusers aims at teaching the user, rather than making the library as easy to use as possible.
- Complex model vs. scheduler logic is exposed instead of magically handled inside. Schedulers/Samplers are separated from diffusion models with minimal dependencies on each other. This forces the user to write the unrolled denoising loop. However, the separation allows for easier debugging and gives the user more control over adapting the denoising process or switching out diffusion models or schedulers.
- Separately trained components of the diffusion pipeline, *e.g.* the text encoder, the unet, and the variational autoencoder, each have their own model class. This forces the user to handle the interaction between the different model components, and the serialization format separates the model components into different files. However, this allows for easier debugging and customization. Dreambooth or textual inversion training
is very simple thanks to diffusers' ability to separate single components of the diffusion pipeline.
- Separately trained components of the diffusion pipeline, *e.g.* the text encoder, the UNet, and the variational autoencoder, each has their own model class. This forces the user to handle the interaction between the different model components, and the serialization format separates the model components into different files. However, this allows for easier debugging and customization. DreamBooth or Textual Inversion training
is very simple thanks to Diffusers' ability to separate single components of the diffusion pipeline.
## Tweakable, contributor-friendly over abstraction
For large parts of the library, Diffusers adopts an important design principle of the [Transformers library](https://github.com/huggingface/transformers), which is to prefer copy-pasted code over hasty abstractions. This design principle is very opinionated and stands in stark contrast to popular design principles such as [Don't repeat yourself (DRY)](https://en.wikipedia.org/wiki/Don%27t_repeat_yourself).
In short, just like Transformers does for modeling files, diffusers prefers to keep an extremely low level of abstraction and very self-contained code for pipelines and schedulers.
In short, just like Transformers does for modeling files, Diffusers prefers to keep an extremely low level of abstraction and very self-contained code for pipelines and schedulers.
Functions, long code blocks, and even classes can be copied across multiple files which at first can look like a bad, sloppy design choice that makes the library unmaintainable.
**However**, this design has proven to be extremely successful for Transformers and makes a lot of sense for community-driven, open-source machine learning libraries because:
- Machine Learning is an extremely fast-moving field in which paradigms, model architectures, and algorithms are changing rapidly, which therefore makes it very difficult to define long-lasting code abstractions.
@@ -47,24 +47,24 @@ Functions, long code blocks, and even classes can be copied across multiple file
At Hugging Face, we call this design the **single-file policy** which means that almost all of the code of a certain class should be written in a single, self-contained file. To read more about the philosophy, you can have a look
at [this blog post](https://huggingface.co/blog/transformers-design-philosophy).
In diffusers, we follow this philosophy for both pipelines and schedulers, but only partly for diffusion models. The reason we don't follow this design fully for diffusion models is because almost all diffusion pipelines, such
as [DDPM](https://huggingface.co/docs/diffusers/v0.12.0/en/api/pipelines/ddpm), [Stable Diffusion](https://huggingface.co/docs/diffusers/v0.12.0/en/api/pipelines/stable_diffusion/overview#stable-diffusion-pipelines), [UnCLIP (Dalle-2)](https://huggingface.co/docs/diffusers/v0.12.0/en/api/pipelines/unclip#overview) and [Imagen](https://imagen.research.google/) all rely on the same diffusion model, the [UNet](https://huggingface.co/docs/diffusers/api/models#diffusers.UNet2DConditionModel).
In Diffusers, we follow this philosophy for both pipelines and schedulers, but only partly for diffusion models. The reason we don't follow this design fully for diffusion models is because almost all diffusion pipelines, such
as [DDPM](https://huggingface.co/docs/diffusers/api/pipelines/ddpm), [Stable Diffusion](https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion/overview#stable-diffusion-pipelines), [unCLIP (DALL·E 2)](https://huggingface.co/docs/diffusers/api/pipelines/unclip) and [Imagen](https://imagen.research.google/) all rely on the same diffusion model, the [UNet](https://huggingface.co/docs/diffusers/api/models/unet2d-cond).
Great, now you should have generally understood why 🧨 Diffusers is designed the way it is 🤗.
We try to apply these design principles consistently across the library. Nevertheless, there are some minor exceptions to the philosophy or some unlucky design choices. If you have feedback regarding the design, we would ❤️ to hear it [directly on GitHub](https://github.com/huggingface/diffusers/issues/new?assignees=&labels=&template=feedback.md&title=).
## Design Philosophy in Details
Now, let's look a bit into the nitty-gritty details of the design philosophy. Diffusers essentially consist of three major classes, [pipelines](https://github.com/huggingface/diffusers/tree/main/src/diffusers/pipelines), [models](https://github.com/huggingface/diffusers/tree/main/src/diffusers/models), and [schedulers](https://github.com/huggingface/diffusers/tree/main/src/diffusers/schedulers).
Let's walk through more in-detail design decisions for each class.
Now, let's look a bit into the nitty-gritty details of the design philosophy. Diffusers essentially consists of three major classes: [pipelines](https://github.com/huggingface/diffusers/tree/main/src/diffusers/pipelines), [models](https://github.com/huggingface/diffusers/tree/main/src/diffusers/models), and [schedulers](https://github.com/huggingface/diffusers/tree/main/src/diffusers/schedulers).
Let's walk through more detailed design decisions for each class.
### Pipelines
Pipelines are designed to be easy to use (therefore do not follow [*Simple over easy*](#simple-over-easy) 100%)), are not feature complete, and should loosely be seen as examples of how to use [models](#models) and [schedulers](#schedulers) for inference.
Pipelines are designed to be easy to use (therefore do not follow [*Simple over easy*](#simple-over-easy) 100%), are not feature complete, and should loosely be seen as examples of how to use [models](#models) and [schedulers](#schedulers) for inference.
The following design principles are followed:
- Pipelines follow the single-file policy. All pipelines can be found in individual directories under src/diffusers/pipelines. One pipeline folder corresponds to one diffusion paper/project/release. Multiple pipeline files can be gathered in one pipeline folder, as it’s done for [`src/diffusers/pipelines/stable-diffusion`](https://github.com/huggingface/diffusers/tree/main/src/diffusers/pipelines/stable_diffusion). If pipelines share similar functionality, one can make use of the [#Copied from mechanism](https://github.com/huggingface/diffusers/blob/125d783076e5bd9785beb05367a2d2566843a271/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_img2img.py#L251).
- Pipelines all inherit from [`DiffusionPipeline`]
- Pipelines all inherit from [`DiffusionPipeline`].
- Every pipeline consists of different model and scheduler components, that are documented in the [`model_index.json` file](https://huggingface.co/runwayml/stable-diffusion-v1-5/blob/main/model_index.json), are accessible under the same name as attributes of the pipeline and can be shared between pipelines with [`DiffusionPipeline.components`](https://huggingface.co/docs/diffusers/main/en/api/diffusion_pipeline#diffusers.DiffusionPipeline.components) function.
- Every pipeline should be loadable via the [`DiffusionPipeline.from_pretrained`](https://huggingface.co/docs/diffusers/main/en/api/diffusion_pipeline#diffusers.DiffusionPipeline.from_pretrained) function.
- Pipelines should be used **only** for inference.
@@ -82,15 +82,15 @@ Models are designed as configurable toolboxes that are natural extensions of [Py
The following design principles are followed:
- Models correspond to **a type of model architecture**. *E.g.* the [`UNet2DConditionModel`] class is used for all UNet variations that expect 2D image inputs and are conditioned on some context.
- All models can be found in [`src/diffusers/models`](https://github.com/huggingface/diffusers/tree/main/src/diffusers/models) and every model architecture shall be defined in its file, e.g. [`unet_2d_condition.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/unet_2d_condition.py), [`transformer_2d.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/transformer_2d.py), etc...
- Models **do not** follow the single-file policy and should make use of smaller model building blocks, such as [`attention.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention.py), [`resnet.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/resnet.py), [`embeddings.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/embeddings.py), etc... **Note**: This is in stark contrast to Transformers' modeling files and shows that models do not really follow the single-file policy.
- Models intend to expose complexity, just like PyTorch's module does, and give clear error messages.
- Models **do not** follow the single-file policy and should make use of smaller model building blocks, such as [`attention.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention.py), [`resnet.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/resnet.py), [`embeddings.py`](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/embeddings.py), etc... **Note**: This is in stark contrast to Transformers' modelling files and shows that models do not really follow the single-file policy.
- Models intend to expose complexity, just like PyTorch's `Module` class, and give clear error messages.
- Models all inherit from `ModelMixin` and `ConfigMixin`.
- Models can be optimized for performance when it doesn’t demand major code changes, keeps backward compatibility, and gives significant memory or compute gain.
- Models can be optimized for performance when it doesn’t demand major code changes, keep backward compatibility, and give significant memory or compute gain.
- Models should by default have the highest precision and lowest performance setting.
- To integrate new model checkpoints whose general architecture can be classified as an architecture that already exists in Diffusers, the existing model architecture shall be adapted to make it work with the new checkpoint. One should only create a new file if the model architecture is fundamentally different.
- Models should be designed to be easily extendable to future changes. This can be achieved by limiting public function arguments, configuration arguments, and "foreseeing" future changes, *e.g.* it is usually better to add `string` "...type" arguments that can easily be extended to new future types instead of boolean `is_..._type` arguments. Only the minimum amount of changes shall be made to existing architectures to make a new model checkpoint work.
- The model design is a difficult trade-off between keeping code readable and concise and supporting many model checkpoints. For most parts of the modeling code, classes shall be adapted for new model checkpoints, while there are some exceptions where it is preferred to add new classes to make sure the code is kept concise and
readable longterm, such as [UNet blocks](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/unet_2d_blocks.py) and [Attention processors](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py).
readable long-term, such as [UNet blocks](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/unet_2d_blocks.py) and [Attention processors](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py).
### Schedulers
@@ -99,10 +99,10 @@ Schedulers are responsible to guide the denoising process for inference as well
The following design principles are followed:
- All schedulers are found in [`src/diffusers/schedulers`](https://github.com/huggingface/diffusers/tree/main/src/diffusers/schedulers).
- Schedulers are **not** allowed to import from large utils files and shall be kept very self-contained.
- One scheduler python file corresponds to one scheduler algorithm (as might be defined in a paper).
- One scheduler Python file corresponds to one scheduler algorithm (as might be defined in a paper).
- If schedulers share similar functionalities, we can make use of the `#Copied from` mechanism.
- Schedulers all inherit from `SchedulerMixin` and `ConfigMixin`.
- Schedulers can be easily swapped out with the [`ConfigMixin.from_config`](https://huggingface.co/docs/diffusers/main/en/api/configuration#diffusers.ConfigMixin.from_config) method as explained in detail [here](./using-diffusers/schedulers.md).
- Schedulers can be easily swapped out with the [`ConfigMixin.from_config`](https://huggingface.co/docs/diffusers/main/en/api/configuration#diffusers.ConfigMixin.from_config) method as explained in detail [here](./docs/source/en/using-diffusers/schedulers.md).
- Every scheduler has to have a `set_num_inference_steps`, and a `step` function. `set_num_inference_steps(...)` has to be called before every denoising process, *i.e.* before `step(...)` is called.
- Every scheduler exposes the timesteps to be "looped over" via a `timesteps` attribute, which is an array of timesteps the model will be called upon.
- The `step(...)` function takes a predicted model output and the "current" sample (x_t) and returns the "previous", slightly more denoised sample (x_t-1).

39
README.md
View File

@@ -1,3 +1,19 @@
<!---
Copyright 2022 - The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
-->
<p align="center">
<br>
<img src="https://raw.githubusercontent.com/huggingface/diffusers/main/docs/source/en/imgs/diffusers_library.jpg" width="400"/>
@@ -14,7 +30,10 @@
<img alt="GitHub release" src="https://static.pepy.tech/badge/diffusers/month">
</a>
<a href="CODE_OF_CONDUCT.md">
<img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-2.0-4baaaa.svg">
<img alt="Contributor Covenant" src="https://img.shields.io/badge/Contributor%20Covenant-2.1-4baaaa.svg">
</a>
<a href="https://twitter.com/diffuserslib">
<img alt="X account" src="https://img.shields.io/twitter/url/https/twitter.com/diffuserslib.svg?style=social&label=Follow%20%40diffuserslib">
</a>
</p>
@@ -24,7 +43,7 @@
- State-of-the-art [diffusion pipelines](https://huggingface.co/docs/diffusers/api/pipelines/overview) that can be run in inference with just a few lines of code.
- Interchangeable noise [schedulers](https://huggingface.co/docs/diffusers/api/schedulers/overview) for different diffusion speeds and output quality.
- Pretrained [models](https://huggingface.co/docs/diffusers/api/models) that can be used as building blocks, and combined with schedulers, for creating your own end-to-end diffusion systems.
- Pretrained [models](https://huggingface.co/docs/diffusers/api/models/overview) that can be used as building blocks, and combined with schedulers, for creating your own end-to-end diffusion systems.
## Installation
@@ -58,7 +77,7 @@ Please refer to the [How to use Stable Diffusion in Apple Silicon](https://huggi
## Quickstart
Generating outputs is super easy with 🤗 Diffusers. To generate an image from text, use the `from_pretrained` method to load any pretrained diffusion model (browse the [Hub](https://huggingface.co/models?library=diffusers&sort=downloads) for 4000+ checkpoints):
Generating outputs is super easy with 🤗 Diffusers. To generate an image from text, use the `from_pretrained` method to load any pretrained diffusion model (browse the [Hub](https://huggingface.co/models?library=diffusers&sort=downloads) for 14000+ checkpoints):
```python
from diffusers import DiffusionPipeline
@@ -141,12 +160,12 @@ just hang out ☕.
</tr>
<tr>
<td>Text-to-Image</td>
<td><a href="https://huggingface.co/docs/diffusers/api/pipelines/unclip">unclip</a></td>
<td><a href="https://huggingface.co/docs/diffusers/api/pipelines/unclip">unCLIP</a></td>
<td><a href="https://huggingface.co/kakaobrain/karlo-v1-alpha"> kakaobrain/karlo-v1-alpha </a></td>
</tr>
<tr>
<td>Text-to-Image</td>
<td><a href="https://huggingface.co/docs/diffusers/api/pipelines/if">DeepFloyd IF</a></td>
<td><a href="https://huggingface.co/docs/diffusers/api/pipelines/deepfloyd_if">DeepFloyd IF</a></td>
<td><a href="https://huggingface.co/DeepFloyd/IF-I-XL-v1.0"> DeepFloyd/IF-I-XL-v1.0 </a></td>
</tr>
<tr>
@@ -156,12 +175,12 @@ just hang out ☕.
</tr>
<tr style="border-top: 2px solid black">
<td>Text-guided Image-to-Image</td>
<td><a href="https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion/controlnet">Controlnet</a></td>
<td><a href="https://huggingface.co/docs/diffusers/api/pipelines/controlnet">ControlNet</a></td>
<td><a href="https://huggingface.co/lllyasviel/sd-controlnet-canny"> lllyasviel/sd-controlnet-canny </a></td>
</tr>
<tr>
<td>Text-guided Image-to-Image</td>
<td><a href="https://huggingface.co/docs/diffusers/api/pipelines/pix2pix">Instruct Pix2Pix</a></td>
<td><a href="https://huggingface.co/docs/diffusers/api/pipelines/pix2pix">InstructPix2Pix</a></td>
<td><a href="https://huggingface.co/timbrooks/instruct-pix2pix"> timbrooks/instruct-pix2pix </a></td>
</tr>
<tr>
@@ -171,7 +190,7 @@ just hang out ☕.
</tr>
<tr style="border-top: 2px solid black">
<td>Text-guided Image Inpainting</td>
<td><a href="https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion/inpaint">Stable Diffusion Inpaint</a></td>
<td><a href="https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion/inpaint">Stable Diffusion Inpainting</a></td>
<td><a href="https://huggingface.co/runwayml/stable-diffusion-inpainting"> runwayml/stable-diffusion-inpainting </a></td>
</tr>
<tr style="border-top: 2px solid black">
@@ -202,9 +221,9 @@ just hang out ☕.
- https://github.com/deep-floyd/IF
- https://github.com/bentoml/BentoML
- https://github.com/bmaltais/kohya_ss
- +3000 other amazing GitHub repositories 💪
- +6000 other amazing GitHub repositories 💪
Thank you for using us ❤️
Thank you for using us ❤️.
## Credits

22
docs/TRANSLATING.md
View File

@@ -1,10 +1,22 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
-->
### Translating the Diffusers documentation into your language
As part of our mission to democratize machine learning, we'd love to make the Diffusers library available in many more languages! Follow the steps below if you want to help translate the documentation into your language 🙏.
**🗞️ Open an issue**
To get started, navigate to the [Issues](https://github.com/huggingface/diffusers/issues) page of this repo and check if anyone else has opened an issue for your language. If not, open a new issue by selecting the "Translation template" from the "New issue" button.
To get started, navigate to the [Issues](https://github.com/huggingface/diffusers/issues) page of this repo and check if anyone else has opened an issue for your language. If not, open a new issue by selecting the "🌐 Translating a New Language?" from the "New issue" button.
Once an issue exists, post a comment to indicate which chapters you'd like to work on, and we'll add your name to the list.
@@ -16,7 +28,7 @@ First, you'll need to [fork the Diffusers repo](https://docs.github.com/en/get-s
Once you've forked the repo, you'll want to get the files on your local machine for editing. You can do that by cloning the fork with Git as follows:
```bash
git clone https://github.com/YOUR-USERNAME/diffusers.git
git clone https://github.com/<YOUR-USERNAME>/diffusers.git
```
**📋 Copy-paste the English version with a new language code**
@@ -29,10 +41,10 @@ You'll only need to copy the files in the [`docs/source/en`](https://github.com/
```bash
cd ~/path/to/diffusers/docs
cp -r source/en source/LANG-ID
cp -r source/en source/<LANG-ID>
```
Here, `LANG-ID` should be one of the ISO 639-1 or ISO 639-2 language codes -- see [here](https://www.loc.gov/standards/iso639-2/php/code_list.php) for a handy table.
Here, `<LANG-ID>` should be one of the ISO 639-1 or ISO 639-2 language codes -- see [here](https://www.loc.gov/standards/iso639-2/php/code_list.php) for a handy table.
**✍️ Start translating**
@@ -40,7 +52,7 @@ The fun part comes - translating the text!
The first thing we recommend is translating the part of the `_toctree.yml` file that corresponds to your doc chapter. This file is used to render the table of contents on the website.
> 🙋 If the `_toctree.yml` file doesn't yet exist for your language, you can create one by copy-pasting from the English version and deleting the sections unrelated to your chapter. Just make sure it exists in the `docs/source/LANG-ID/` directory!
> 🙋 If the `_toctree.yml` file doesn't yet exist for your language, you can create one by copy-pasting from the English version and deleting the sections unrelated to your chapter. Just make sure it exists in the `docs/source/<LANG-ID>/` directory!
The fields you should add are `local` (with the name of the file containing the translation; e.g. `autoclass_tutorial`), and `title` (with the title of the doc in your language; e.g. `Load pretrained instances with an AutoClass`) -- as a reference, here is the `_toctree.yml` for [English](https://github.com/huggingface/diffusers/blob/main/docs/source/en/_toctree.yml):

53
setup.py
View File

@@ -15,12 +15,12 @@
"""
Simple check list from AllenNLP repo: https://github.com/allenai/allennlp/blob/main/setup.py
To create the package for pypi.
To create the package for PyPI.
1. Run `make pre-release` (or `make pre-patch` for a patch release) then run `make fix-copies` to fix the index of the
documentation.
If releasing on a special branch, copy the updated README.md on the main branch for your the commit you will make
If releasing on a special branch, copy the updated README.md on the main branch for the commit you will make
for the post-release and run `make fix-copies` on the main branch as well.
2. Run Tests for Amazon Sagemaker. The documentation is located in `./tests/sagemaker/README.md`, otherwise @philschmid.
@@ -30,29 +30,29 @@ To create the package for pypi.
4. Checkout the release branch (v<RELEASE>-release, for example v4.19-release), and commit these changes with the
message: "Release: <RELEASE>" and push.
5. Wait for the tests on main to be completed and be green (otherwise revert and fix bugs)
5. Wait for the tests on main to be completed and be green (otherwise revert and fix bugs).
6. Add a tag in git to mark the release: "git tag v<RELEASE> -m 'Adds tag v<RELEASE> for pypi' "
6. Add a tag in git to mark the release: "git tag v<RELEASE> -m 'Adds tag v<RELEASE> for PyPI'"
Push the tag to git: git push --tags origin v<RELEASE>-release
7. Build both the sources and the wheel. Do not change anything in setup.py between
creating the wheel and the source distribution (obviously).
For the wheel, run: "python setup.py bdist_wheel" in the top level directory.
(this will build a wheel for the python version you use to build it).
For the wheel, run: "python setup.py bdist_wheel" in the top level directory
(This will build a wheel for the Python version you use to build it).
For the sources, run: "python setup.py sdist"
You should now have a /dist directory with both .whl and .tar.gz source versions.
Long story cut short, you need to run both before you can upload the distribution to the
test pypi and the actual pypi servers:
test PyPI and the actual PyPI servers:
python setup.py bdist_wheel && python setup.py sdist
8. Check that everything looks correct by uploading the package to the pypi test server:
8. Check that everything looks correct by uploading the package to the PyPI test server:
twine upload dist/* -r pypitest
(pypi suggest using twine as other methods upload files via plaintext.)
(pypi suggests using twine as other methods upload files via plaintext.)
You may have to specify the repository url, use the following command then:
twine upload dist/* -r pypitest --repository-url=https://test.pypi.org/legacy/
@@ -64,20 +64,21 @@ To create the package for pypi.
pip install -i https://testpypi.python.org/pypi diffusers
Check you can run the following commands:
python -c "python -c "from diffusers import __version__; print(__version__)"
python -c "from diffusers import __version__; print(__version__)"
python -c "from diffusers import DiffusionPipeline; pipe = DiffusionPipeline.from_pretrained('fusing/unet-ldm-dummy-update'); pipe()"
python -c "from diffusers import DiffusionPipeline; pipe = DiffusionPipeline.from_pretrained('hf-internal-testing/tiny-stable-diffusion-pipe', safety_checker=None); pipe('ah suh du')"
python -c "from diffusers import *"
9. Upload the final version to actual pypi:
9. Upload the final version to the actual PyPI:
twine upload dist/* -r pypi
10. Prepare the release notes and publish them on github once everything is looking hunky-dory.
10. Prepare the release notes and publish them on GitHub once everything is looking hunky-dory.
11. Run `make post-release` (or, for a patch release, `make post-patch`). If you were on a branch for the release,
you need to go back to main before executing this.
"""
import sys
import os
import re
from distutils.core import Command
@@ -142,7 +143,7 @@ deps = {b: a for a, b in (re.findall(r"^(([^!=<>~]+)(?:[!=<>~].*)?$)", x)[0] for
# anywhere. If you need to quickly access the data from this table in a shell, you can do so easily with:
#
# python -c 'import sys; from diffusers.dependency_versions_table import deps; \
# print(" ".join([ deps[x] for x in sys.argv[1:]]))' tokenizers datasets
# print(" ".join([deps[x] for x in sys.argv[1:]]))' tokenizers datasets
#
# Just pass the desired package names to that script as it's shown with 2 packages above.
#
@@ -151,7 +152,7 @@ deps = {b: a for a, b in (re.findall(r"^(([^!=<>~]+)(?:[!=<>~].*)?$)", x)[0] for
# You can then feed this for example to `pip`:
#
# pip install -U $(python -c 'import sys; from diffusers.dependency_versions_table import deps; \
# print(" ".join([ deps[x] for x in sys.argv[1:]]))' tokenizers datasets)
# print(" ".join([deps[x] for x in sys.argv[1:]]))' tokenizers datasets)
#
@@ -182,7 +183,7 @@ class DepsTableUpdateCommand(Command):
content = [
"# THIS FILE HAS BEEN AUTOGENERATED. To update:",
"# 1. modify the `_deps` dict in setup.py",
"# 2. run `make deps_table_update``",
"# 2. run `make deps_table_update`",
"deps = {",
entries,
"}",
@@ -194,7 +195,6 @@ class DepsTableUpdateCommand(Command):
f.write("\n".join(content))
extras = {}
extras = {}
@@ -242,6 +242,8 @@ install_requires = [
deps["Pillow"],
]
version_range_max = max(sys.version_info[1], 10) + 1
setup(
name="diffusers",
version="0.24.0.dev0", # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
@@ -268,30 +270,33 @@ setup(
"Intended Audience :: Science/Research",
"License :: OSI Approved :: Apache Software License",
"Operating System :: OS Independent",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Programming Language :: Python :: 3",
]
+ [
f"Programming Language :: Python :: 3.{i}"
for i in range(8, version_range_max)
],
cmdclass={"deps_table_update": DepsTableUpdateCommand},
)
# Release checklist
# 1. Change the version in __init__.py and setup.py.
# 2. Commit these changes with the message: "Release: Release"
# 3. Add a tag in git to mark the release: "git tag RELEASE -m 'Adds tag RELEASE for pypi' "
# 3. Add a tag in git to mark the release: "git tag RELEASE -m 'Adds tag RELEASE for PyPI'"
# Push the tag to git: git push --tags origin main
# 4. Run the following commands in the top-level directory:
# python setup.py bdist_wheel
# python setup.py sdist
# 5. Upload the package to the pypi test server first:
# 5. Upload the package to the PyPI test server first:
# twine upload dist/* -r pypitest
# twine upload dist/* -r pypitest --repository-url=https://test.pypi.org/legacy/
# 6. Check that you can install it in a virtualenv by running:
# pip install -i https://testpypi.python.org/pypi diffusers
# diffusers env
# diffusers test
# 7. Upload the final version to actual pypi:
# 7. Upload the final version to the actual PyPI:
# twine upload dist/* -r pypi
# 8. Add release notes to the tag in github once everything is looking hunky-dory.
# 9. Update the version in __init__.py, setup.py to the new version "-dev" and push to master
# 8. Add release notes to the tag in GitHub once everything is looking hunky-dory.
# 9. Update the version in __init__.py, setup.py to the new version "-dev" and push to main.

2
src/diffusers/dependency_versions_table.py
View File

@@ -1,6 +1,6 @@
# THIS FILE HAS BEEN AUTOGENERATED. To update:
# 1. modify the `_deps` dict in setup.py
# 2. run `make deps_table_update``
# 2. run `make deps_table_update`
deps = {
"Pillow": "Pillow",
"accelerate": "accelerate>=0.11.0",