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Add issue/PR templates, code of conduct & better contributing guide (#1963)

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* Add issue/PR templates, code of conduct & better contributing guide

* Apply suggestions from code review

Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com>

---------

Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com>
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# 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. They may suggest changes to make the code even better.
-->
<!-- 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/trl/blob/main/CONTRIBUTING.md#create-a-pull-request),
Pull Request section?
- [ ] Was this discussed/approved via a GitHub issue? 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/trl/tree/main/docs).
- [ ] 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.

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name: "\U0001F41B Bug Report"
description: Submit a bug report to help us improve TRL
labels: [ "bug" ]
body:
- type: markdown
attributes:
value: |
Thanks for taking the time to fill out this bug report! 🤗
Before you submit your bug report:
- If it is your first time submitting, be sure to check our [bug report guidelines](https://github.com/huggingface/trl/blob/main/CONTRIBUTING.md#did-you-find-a-bug)
- type: textarea
id: system-info
attributes:
label: System Info
description: Please share your system info with us. You can run the command `transformers-cli env` and copy-paste its output below.
placeholder: trl version, transformers version, platform, python version, ...
validations:
required: true
- type: checkboxes
id: information-scripts-examples
attributes:
label: Information
description: 'The problem arises when using:'
options:
- label: "The official example scripts"
- label: "My own modified scripts"
- type: checkboxes
id: information-tasks
attributes:
label: Tasks
description: "The tasks I am working on are:"
options:
- label: "An officially supported task in the `examples` folder"
- label: "My own task or dataset (give details below)"
- type: textarea
id: reproduction
validations:
required: true
attributes:
label: Reproduction
description: |
Please provide a code sample that reproduces the problem you ran into. It can be a Colab link or just a code snippet.
If you have code snippets, error messages, stack traces please provide them here as well.
Important! Use code tags to correctly format your code. See https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks#syntax-highlighting
Do not use screenshots, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
placeholder: |
Steps to reproduce the behavior:
1.
2.
3.
- type: textarea
id: expected-behavior
validations:
required: true
attributes:
label: Expected behavior
description: "A clear and concise description of what you would expect to happen."

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name: "\U0001F680 Feature request"
description: Submit a proposal/request for a new TRL feature
labels: [ "Feature request" ]
body:
- type: textarea
id: feature-request
validations:
required: true
attributes:
label: Feature request
description: |
A clear and concise description of the feature proposal. Please provide a link to the paper and code in case they exist.
- type: textarea
id: motivation
validations:
required: true
attributes:
label: Motivation
description: |
Please outline the motivation for the proposal. Is your feature request related to a problem? e.g., I'm always frustrated when [...]. If this is related to another GitHub issue, please link here too.
- type: textarea
id: contribution
validations:
required: true
attributes:
label: Your contribution
description: |
Is there any way that you could help, e.g. by submitting a PR? Make sure to read the CONTRIBUTING.MD [readme](https://github.com/huggingface/trl/blob/main/CONTRIBUTING.md)

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name: "\U0001F31F New trainer addition"
description: Submit a proposal/request to implement a new trainer for a post-training method
labels: [ "New trainer" ]
body:
- type: textarea
id: description-request
validations:
required: true
attributes:
label: Method description
description: |
Put any and all important information relative to the method
- type: checkboxes
id: information-tasks
attributes:
label: Open source status
description: |
Please note that if the method implementation isn't available or model weights with training datasets aren't available, we are less likely to implement it in `trl`.
options:
- label: "The method implementation is available"
- label: "The model weights are available"
- label: "The training datasets are available"
- 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.

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# Contributor Covenant Code of Conduct
## Our Pledge
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, caste, color, religion, or sexual
identity and orientation.
We pledge to act and interact in ways that contribute to an open, welcoming,
diverse, inclusive, and healthy community.
## Our Standards
Examples of behavior that contributes to a positive environment for our
community include:
* Demonstrating empathy and kindness toward other people
* Being respectful of differing opinions, viewpoints, and experiences
* Giving and gracefully accepting constructive feedback
* 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
community
Examples of unacceptable behavior include:
* The use of sexualized language or imagery, and sexual attention or advances of
any kind
* Trolling, insulting or derogatory comments, and personal or political attacks
* Public or private harassment
* Publishing others' private information, such as a physical or email address,
without their explicit permission
* Other conduct which could reasonably be considered inappropriate in a
professional setting
## Enforcement Responsibilities
Community leaders are responsible for clarifying and enforcing our standards of
acceptable behavior and will take appropriate and fair corrective action in
response to any behavior that they deem inappropriate, threatening, offensive,
or harmful.
Community leaders have the right and responsibility to remove, edit, or reject
comments, commits, code, wiki edits, issues, and other contributions that are
not aligned to this Code of Conduct, and will communicate reasons for moderation
decisions when appropriate.
## Scope
This Code of Conduct applies within all community spaces, and also applies when
an individual is officially representing the community in public spaces.
Examples of representing our community include using an official e-mail address,
posting via an official social media account, or acting as an appointed
representative at an online or offline event.
## Enforcement
Instances of abusive, harassing, or otherwise unacceptable behavior may be
reported to the community leaders responsible for enforcement at
feedback@huggingface.co.
All complaints will be reviewed and investigated promptly and fairly.
All community leaders are obligated to respect the privacy and security of the
reporter of any incident.
## Enforcement Guidelines
Community leaders will follow these Community Impact Guidelines in determining
the consequences for any action they deem in violation of this Code of Conduct:
### 1. Correction
**Community Impact**: Use of inappropriate language or other behavior deemed
unprofessional or unwelcome in the community.
**Consequence**: A private, written warning from community leaders, providing
clarity around the nature of the violation and an explanation of why the
behavior was inappropriate. A public apology may be requested.
### 2. Warning
**Community Impact**: A violation through a single incident or series of
actions.
**Consequence**: A warning with consequences for continued behavior. No
interaction with the people involved, including unsolicited interaction with
those enforcing the Code of Conduct, for a specified period of time. This
includes avoiding interactions in community spaces as well as external channels
like social media. Violating these terms may lead to a temporary or permanent
ban.
### 3. Temporary Ban
**Community Impact**: A serious violation of community standards, including
sustained inappropriate behavior.
**Consequence**: A temporary ban from any sort of interaction or public
communication with the community for a specified period of time. No public or
private interaction with the people involved, including unsolicited interaction
with those enforcing the Code of Conduct, is allowed during this period.
Violating these terms may lead to a permanent ban.
### 4. Permanent Ban
**Community Impact**: Demonstrating a pattern of violation of community
standards, including sustained inappropriate behavior, harassment of an
individual, or aggression toward or disparagement of classes of individuals.
**Consequence**: A permanent ban from any sort of public interaction within the
community.
## Attribution
This Code of Conduct is adapted from the [Contributor Covenant][homepage],
version 2.1, available at
[https://www.contributor-covenant.org/version/2/1/code_of_conduct.html][v2.1].
Community Impact Guidelines were inspired by
[Mozilla's code of conduct enforcement ladder][Mozilla CoC].
For answers to common questions about this code of conduct, see the FAQ at
[https://www.contributor-covenant.org/faq][FAQ]. Translations are available at
[https://www.contributor-covenant.org/translations][translations].
[homepage]: https://www.contributor-covenant.org
[v2.1]: https://www.contributor-covenant.org/version/2/1/code_of_conduct.html
[Mozilla CoC]: https://github.com/mozilla/diversity
[FAQ]: https://www.contributor-covenant.org/faq
[translations]: https://www.contributor-covenant.org/translations

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CONTRIBUTING.md
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# How to contribute
# How to contribute to TRL?
## How to get started
Everyone is welcome to contribute, and we value everybody's contribution. Code
contributions are not the only way to help the community. Answering questions, helping
others, and improving the documentation are also immensely valuable.
Before you start contributing make sure you installed all the dev tools:
It also helps us if you spread the word! Reference the library in blog posts
about the awesome projects it made possible, shout out on Twitter every time it has
helped you, or simply ⭐️ the repository to say thank you.
However you choose to contribute, please be mindful and respect our
[code of conduct](https://github.com/huggingface/trl/blob/main/CODE_OF_CONDUCT.md).
**This guide was heavily inspired by the awesome [scikit-learn guide to contributing](https://github.com/scikit-learn/scikit-learn/blob/main/CONTRIBUTING.md).**
## Ways to contribute
There are several ways you can contribute to TRL:
* Fix outstanding issues with the existing code.
* Submit issues related to bugs or desired new features.
* Implement trainers for new post-training algorithms.
* Contribute to the examples or to the documentation.
If you don't know where to start, there is a special [Good First
Issue](https://github.com/huggingface/trl/contribute) listing. It will give you a list of
open issues that are beginner-friendly and help you start contributing to open-source. The best way to do that is to open a Pull Request and link it to the issue that you'd like to work on. We try to give priority to opened PRs as we can easily track the progress of the fix, and if the contributor does not have time anymore, someone else can take the PR over.
For something slightly more challenging, you can also take a look at the [Good Second Issue](https://github.com/huggingface/trl/labels/Good%20Second%20Issue) list. In general though, if you feel like you know what you're doing, go for it and we'll help you get there! 🚀
> All contributions are equally valuable to the community. 🥰
Before you start contributing make sure you have installed all the dev tools:
```bash
make dev
```
## Did you find a bug?
## Fixing outstanding issues
* Ensure the bug was not already reported by searching on GitHub under Issues.
* If you're unable to find an open issue addressing the problem, open a new one. Be sure to include a title and clear description, as much relevant information as possible, and a code sample or an executable test case demonstrating the expected behavior that is not occurring.
* Be sure to add the complete error messages.
If you notice an issue with the existing code and have a fix in mind, feel free to [start contributing](#create-a-pull-request) and open a Pull Request!
#### Did you write a patch that fixes a bug?
## Submitting a bug-related issue or feature request
* Open a new GitHub pull request with the patch.
* Ensure that your PR includes a test that fails without your patch, and pass with it.
* Ensure the PR description clearly describes the problem and solution. Include the relevant issue number if applicable.
Do your best to follow these guidelines when submitting a bug-related issue or a feature request. It will make it easier for us to come back to you quickly and with good feedback.
## PR submission guidelines
### Did you find a bug?
* Keep each PR focused. While it's more convenient, do not combine several unrelated fixes together. Create as many branches as needing to keep each PR focused.
* Do not mix style changes/fixes with "functional" changes. It's very difficult to review such PRs and it most likely get rejected.
* Do not add/remove vertical whitespace. Preserve the original style of the file you edit as much as you can.
* Do not turn an already submitted PR into your development playground. If after you submitted PR, you discovered that more work is needed - close the PR, do the required work and then submit a new PR. Otherwise each of your commits requires attention from maintainers of the project.
* If, however, you submitted a PR and received a request for changes, you should proceed with commits inside that PR, so that the maintainer can see the incremental fixes and won't need to review the whole PR again. In the exception case where you realize it'll take many many commits to complete the requests, then it's probably best to close the PR, do the work and then submit it again. Use common sense where you'd choose one way over another.
The TRL library is robust and reliable thanks to users who report the problems they encounter.
### Before you submit a PR
Before you report an issue, we would really appreciate it if you could **make sure the bug was not
already reported** (use the search bar on GitHub under Issues). Your issue should also be related to bugs in the library itself, and not your code.
First you want to make sure that all the tests pass:
Once you've confirmed the bug hasn't already been reported, please include the following information in your issue so we can quickly resolve it:
* Your **OS type and version**, **Python**, **PyTorch**, **TRL** and **Transformers** versions.
* A short, self-contained, code snippet that allows us to reproduce the bug in
less than 30s.
* The *full* traceback if an exception is raised.
* Attach any other additional information, like screenshots, you think may help.
To get the OS and software versions automatically, run the following command:
```bash
make test
transformers-cli env
```
Then before submitting your PR make sure the code quality follows the standards. You can run the following command to format:
### Do you want a new feature?
If there is a new feature you'd like to see in TRL, please open an issue and describe:
1. What is the *motivation* behind this feature? Is it related to a problem or frustration with the library? Is it a feature related to something you need for a project? Is it something you worked on and think it could benefit the community?
Whatever it is, we'd love to hear about it!
2. Describe your requested feature in as much detail as possible. The more you can tell us about it, the better we'll be able to help you.
3. Provide a *code snippet* that demonstrates the features usage.
4. If the feature is related to a paper, please include a link.
If your issue is well written we're already 80% of the way there by the time you create it.
## Do you want to implement a new trainer?
New post-training methods are published on a frequent basis and those which satisfy the following criteria are good candidates to be integrated in TRL:
* **Simplicity:** does the new method achieve similar performance as prior methods, but with less complexity? A good example is [Direct Preference Optimization](https://arxiv.org/abs/2305.18290) (DPO), which provided a simpler and compelling alternative to RLHF methods.
* **Efficiency:** does the new method provide a significant improvement in training efficiency? A good example is [Odds Ratio Preference Optimization](https://arxiv.org/abs/2403.07691v2), which utilises a similar objective as DPO, but requires half the GPU VRAM.
Methods which only provide incremental improvements at the expense of added complexity or compute costs are unlikely to be included in TRL.
If you want to implement a trainer for a new post-training method, first open an issue and provide the following information:
* A short description of the method and a link to the paper.
* Link to the implementation if it is open-sourced.
* Link to model weights trained with the method if they are available.
Based on the community and maintainer feedback, the next step will be to implement the trainer and config classes. See the following examples for inspiration:
* Paired preference optimisation: [`dpo_trainer.py`](./trl/trainer/dpo_trainer.py) and [`dpo_config.py`](./trl/trainer/dpo_config.py)
* RL-based optimisation: [`rloo_trainer.py](./trl/trainer/rloo_trainer.py) and [`rloo_config.py](./trl/trainer/rloo_config.py)
* Online optimisation: [`online_dpo_trainer.py`](./trl/trainer/online_dpo_trainer.py) and [`online_dpo_config.py`](./trl/trainer/online_dpo_config.py)
## Do you want to add documentation?
We're always looking for improvements to the documentation that make it more clear and accurate. Please let us know how the documentation can be improved, such as typos, dead links and any missing, unclear or inaccurate content.. We'll be happy to make the changes or help you make a contribution if you're interested!
## Submitting a pull request (PR)
Before writing code, we strongly advise you to search through the existing PRs or
issues to make sure that nobody is already working on the same thing. If you are
unsure, it is always a good idea to open an issue to get some feedback.
You will need basic `git` proficiency to be able to contribute to
TRL. `git` is not the easiest tool to use but it has the greatest
manual. Type `git --help` in a shell and enjoy. If you prefer books, [Pro
Git](https://git-scm.com/book/en/v2) is a very good reference.
Follow these steps to start contributing:
1. Fork the [repository](https://github.com/huggingface/trl) by
clicking on the 'Fork' button on the repository's page. This creates a copy of the code
under your GitHub user account.
2. Clone your fork to your local disk, and add the base repository as a remote. The following command
assumes you have your public SSH key uploaded to GitHub. See the following guide for more
[information](https://docs.github.com/en/repositories/creating-and-managing-repositories/cloning-a-repository).
```bash
$ git clone git@github.com:<your Github handle>/trl.git
$ cd trl
$ git remote add upstream https://github.com/huggingface/trl.git
```
3. Create a new branch to hold your development changes, and do this for every new PR you work on.
Start by synchronizing your `main` branch with the `upstream/main` branch (ore details in the [GitHub Docs](https://docs.github.com/en/github/collaborating-with-issues-and-pull-requests/syncing-a-fork)):
```bash
$ git checkout main
$ git fetch upstream
$ git merge upstream/main
```
Once your `main` branch is synchronized, create a new branch from it:
```bash
$ git checkout -b a-descriptive-name-for-my-changes
```
**Do not** work on the `main` branch.
4. Set up a development environment by running the following command in a conda or a virtual environment you've created for working on this library:
```bash
$ make dev
```
(If TRL was already installed in the virtual environment, remove
it with `pip uninstall trl` before reinstalling it.)
Alternatively, if you are using [Visual Studio Code](https://code.visualstudio.com/Download), the fastest way to get set up is by using
the provided Dev Container. Documentation on how to get started with dev containers is available [here](https://code.visualstudio.com/docs/remote/containers).
5. Develop the features on your branch.
As you work on the features, you should make sure that the test suite
passes. You should run the tests impacted by your changes like this (see
below an explanation regarding the environment variable):
```bash
$ pytest tests/<TEST_TO_RUN>.py
```
> For the following commands leveraging the `make` utility, we recommend using the WSL system when running on
> Windows. More information [here](https://docs.microsoft.com/en-us/windows/wsl/about).
You can also run the full suite with the following command.
```bash
$ make test
```
TRL relies on `ruff` to format its source code
consistently. After you make changes, apply automatic style corrections and code verifications
that can't be automated in one go with:
This target is also optimized to only work with files modified by the PR you're working on.
If you prefer to run the checks one after the other, the following command apply the
style corrections:
```bash
$ make precommit
```
Once you're happy with your changes, add changed files using `git add` and
make a commit with `git commit` to record your changes locally:
```bash
$ git add modified_file.py
$ git commit
```
Please write [good commit messages](https://chris.beams.io/posts/git-commit/).
It is a good idea to sync your copy of the code with the original
repository regularly. This way you can quickly account for changes:
```bash
$ git fetch upstream
$ git rebase upstream/main
```
Push the changes to your account using:
```bash
$ git push -u origin a-descriptive-name-for-my-changes
```
6. Once you are satisfied (**and the checklist below is happy too**), go to the
webpage of your fork on GitHub. Click on 'Pull request' to send your changes
to the project maintainers for review.
7. It's ok if maintainers ask you for changes. It happens to core contributors
too! So everyone can see the changes in the Pull request, work in your local
branch and push the changes to your fork. They will automatically appear in
the pull request.
### Checklist
1. The title of your pull request should be a summary of its contribution;
2. If your pull request addresses an issue, please mention the issue number in
the pull request description to make sure they are linked (and people
consulting the issue know you are working on it);
3. To indicate a work in progress please prefix the title with `[WIP]`, or mark
the PR as a draft PR. These are useful to avoid duplicated work, and to differentiate
it from PRs ready to be merged;
4. Make sure existing tests pass;
5. Add high-coverage tests. No quality testing = no merge.
### Tests
An extensive test suite is included to test the library behavior and several examples. Library tests can be found in
the [tests folder](https://github.com/huggingface/trl/tree/main/tests).
We use `pytest` in order to run the tests. From the root of the
repository, here's how to run tests with `pytest` for the library:
```bash
make precommit
$ python -m pytest -sv ./tests
```
Make sure to install `pre-commit` before running the command:
```bash
pip install pre-commit
```
## Do you want to contribute to the documentation?
* Docs are in the `docs/` folder and can be updated there.
In fact, that's how `make test` is implemented (sans the `pip install` line)!
You can specify a smaller set of tests in order to test only the feature
you're working on.