mirror of
https://github.com/BillyOutlast/flash-attention-prebuild-wheels-rocm.git
synced 2026-07-01 01:27:54 -04:00
Junya Morioka
239 lines
8.8 KiB
Markdown
239 lines
8.8 KiB
Markdown
# flash-attention pre-build wheels
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This repository provides wheels for the pre-built [flash-attention](https://github.com/Dao-AILab/flash-attention).
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Since building flash-attention takes a **very long time** and is resource-intensive,
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I also build and provide combinations of CUDA and PyTorch that are not officially distributed.
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The building Github Actions Workflow can be found [here](./.github/workflows/build.yml).
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The built packages are available on the [release page](https://github.com/mjun0812/flash-attention-prebuild-wheels/releases).
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**This repository uses a self-hosted runner and AWS CodeBuild for building the wheels. If you find this project helpful, please consider sponsoring to help maintain the infrastructure!**
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[](https://github.com/sponsors/mjun0812)
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[](https://buymeacoffee.com/mjun0812)
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**Special thanks to [@KiralyCraft](https://github.com/KiralyCraft) for providing the computing resources used to build wheels. Thank you!!**
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## Install
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1. Select the versions for Python, CUDA, PyTorch, and flash_attn.
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```bash
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flash_attn-[flash_attn Version]+cu[CUDA Version]torch[PyTorch Version]-cp[Python Version]-cp[Python Version]-linux_x86_64.whl
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# Example: Python 3.11, CUDA 12.4, PyTorch 2.5, and flash_attn 2.6.3
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flash_attn-2.6.3+cu124torch2.5-cp312-cp312-linux_x86_64.whl
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```
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2. Find the corresponding version of a wheel from the **[Search Page](https://mjunya.com/flash-attention-prebuild-wheels/)**, [Packages](./doc/packages.md) page, or [releases](https://github.com/mjun0812/flash-attention-prebuild-wheels/releases) page.
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3. Direct Install or Download and Local Install
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```bash
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# Direct Install
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pip install https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/download/v0.0.0/flash_attn-2.6.3+cu124torch2.5-cp312-cp312-linux_x86_64.whl
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# Download and Local Install
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wget https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/download/v0.0.0/flash_attn-2.6.3+cu124torch2.5-cp312-cp312-linux_x86_64.whl
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pip install ./flash_attn-2.6.3+cu124torch2.5-cp312-cp312-linux_x86_64.whl
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```
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## Packages
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> [!NOTE]
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> Since v0.7.0, wheels are built with manylinux2_28 platform.
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> These wheels are compatible with old glibc versions (<=2.17).
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> [!NOTE]
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> Since v0.5.0, wheels are built with a local version label indicating the CUDA and PyTorch versions.
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> Example: `pip list` -> `flash_attn==2.8.3 -> flash_attn==2.8.3+cu130torch2.9`
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See [./doc/packages.md](./doc/packages.md) for the full list of available packages.
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## History
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The history of this repository is available [here](./doc/release_history.md).
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## Citation
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If you use this repository in your research and find it helpful, please cite this repository!
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```bibtex
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@misc{flash-attention-prebuild-wheels,
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author = {Morioka, Junya},
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year = {2025},
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title = {mjun0812/flash-attention-prebuild-wheels},
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url = {https://github.com/mjun0812/flash-attention-prebuild-wheels},
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howpublished = {https://github.com/mjun0812/flash-attention-prebuild-wheels},
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}
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```
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## Acknowledgments
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- [@okaris](https://github.com/okaris) : Sponsored me!
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- [@xhiroga](https://github.com/xhiroga) : Sponsored me!
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- cjustus613 : Buy me a coffee!
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- [@KiralyCraft](https://github.com/KiralyCraft) : Provided with computing resource!
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- [@kun432](https://github.com/kun432) : 2x Buy me a coffee!
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- [@wodeyuzhou](https://github.com/wodeyuzhou) : Sponsored me!
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- Gabr1e1 : Buy me a coffee!
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- wp : Buy me a coffee!
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## Star History and Download Statistics
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<a href="https://www.star-history.com/#mjun0812/flash-attention-prebuild-wheels&type=date&legend=top-left">
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<picture>
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<source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=mjun0812/flash-attention-prebuild-wheels&type=date&theme=dark&legend=top-left" />
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<source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/svg?repos=mjun0812/flash-attention-prebuild-wheels&type=date&legend=top-left" />
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<img alt="Star History Chart" src="https://api.star-history.com/svg?repos=mjun0812/flash-attention-prebuild-wheels&type=date&legend=top-left" height="400px"/>
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</picture>
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</a>
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<img src="./doc/data/download_graph.png" height="400">
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## Original Repository
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[repo](https://github.com/Dao-AILab/flash-attention)
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```bibtex
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@inproceedings{dao2022flashattention,
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title={Flash{A}ttention: Fast and Memory-Efficient Exact Attention with {IO}-Awareness},
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author={Dao, Tri and Fu, Daniel Y. and Ermon, Stefano and Rudra, Atri and R{\'e}, Christopher},
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booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
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year={2022}
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}
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@inproceedings{dao2023flashattention2,
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title={Flash{A}ttention-2: Faster Attention with Better Parallelism and Work Partitioning},
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author={Dao, Tri},
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booktitle={International Conference on Learning Representations (ICLR)},
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year={2024}
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}
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```
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## Self build
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If you cannot find the version you are looking for, you can fork this repository and create a wheel on GitHub Actions.
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1. Fork this repository
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2. Edit Python script [`create_matrix.py`](https://github.com/mjun0812/flash-attention-prebuild-wheels/blob/main/create_matrix.py) to set the version you want to build. You can use GitHub hosted runners or self-hosted runners with below settings.
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3. Add tag `v*.*.*` to trigger the build workflow. `git tag v*.*.* && git push --tags`
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Please note that depending on the combination of versions, it may not be possible to build.
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### Self-Hosted Runner Build
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In some version combinations, you cannot build wheels on GitHub-hosted runners due to job time limitations.
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To build the wheels for these versions, you can use self-hosted runners.
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#### Getting One-Time Registry Token for GitHub Actions Runner
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```bash
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gh api \
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-X POST \
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/repos/[OWNER]/[REPOSITORY]/actions/runners/registration-token
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```
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#### Setup Linux Self-Hosted Runner
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Clone the repository and navigate to the self-hosted-runner directory.
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```bash
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git clone https://github.com/mjun0812/flash-attention-prebuild-wheels.git
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cd flash-attention-prebuild-wheels/self-hosted-runner
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```
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Create environment files from the template. Create one file per architecture you want to build.
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```bash
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# For x86_64
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cp env.template env
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# For ARM64
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cp env.template env.arm
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```
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Edit the environment file(s) to set the required variables.
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```bash
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# Registry Token for GitHub Personal Access Token
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PERSONAL_ACCESS_TOKEN=[Github Personal Access Token]
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# or Registry Token for GitHub Actions Runner
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REGISTRY_TOKEN=[Runner Registry Token]
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# Optional
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RUNNER_LABELS=Linux,self-hosted
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```
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Edit the `compose.yml` file if you use a repository forked from this repository.
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```yaml
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runner:
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platform: linux/amd64
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privileged: true
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restart: always
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env_file:
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- .env
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environment:
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REPOSITORY_URL: https://github.com/[YOUR_USERNAME]/flash-attention-prebuild-wheels
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RUNNER_NAME: self-hosted-runner
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RUNNER_GROUP: default
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TARGET_ARCH: x64
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build:
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context: .
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dockerfile: Dockerfile
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args:
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GH_RUNNER_VERSION: 2.329.0
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TARGET_ARCH: x64
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PLATFORM: linux/amd64
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volumes:
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- fa-self:/var/lib/docker
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runner-arm:
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platform: linux/arm64
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privileged: true
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restart: always
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env_file:
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- .env.arm
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environment:
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REPOSITORY_URL: https://github.com/[YOUR_USERNAME]/flash-attention-prebuild-wheels
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RUNNER_NAME: self-hosted-runner-arm
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RUNNER_GROUP: default
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TARGET_ARCH: arm64
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build:
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context: .
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dockerfile: Dockerfile
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args:
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GH_RUNNER_VERSION: 2.329.0
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TARGET_ARCH: arm64
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PLATFORM: linux/arm64
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volumes:
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- fa-self-arm:/var/lib/docker
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```
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Build and run the docker container(s).
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```bash
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# x86_64 runner
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docker compose build runner
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docker compose up -d runner
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# ARM64 runner (optional)
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docker compose build runner-arm
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docker compose up -d runner-arm
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```
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## Build Environments
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This repository builds wheels across multiple platforms and environments:
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| Platform | Runner Type | Container Image |
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| **Linux x86_64** | GitHub-hosted (`ubuntu-22.04`) | - |
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| **Linux x86_64** | Self-hosted | `ubuntu:22.04` or `manylinux_2_28_x86_64` |
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| **Linux ARM64** | GitHub-hosted (`ubuntu-22.04-arm`) | - |
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| **Windows x86_64** | GitHub-hosted (`windows-2022`) | - |
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| **Windows x86_64** | AWS CodeBuild | - |
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