Skip to main content

MLPerf Automations and Scripts

License Downloads MLC script automation features test MLPerf Inference ABTF POC Test

Welcome to the MLPerf Automations and Scripts repository! This repository is your go-to resource for tools, automations, and scripts designed to streamline the execution of MLPerf benchmarks—with a strong emphasis on MLPerf Inference benchmarks.

Starting January 2025, MLPerf automation scripts is powered by MLCFlow automation interface. This new and simplified framework replaces the previous Collective Mind (CM), providing a more robust, efficient, and self-contained solution for benchmarking workflows, making MLPerf automations independent of any external projects.


🚀 Key Features

  • Automated Benchmarking – Simplifies running MLPerf Inference benchmarks with minimal manual intervention.
  • Modular and Extensible – Easily extend the scripts to support additional benchmarks and configurations.
  • Seamless Integration – Compatible with Docker, cloud environments, and local machines.

🧰 MLCFlow (MLC) Automations

Building upon the robust foundation of its predecessor, the Collective Mind (CM) framework, MLCFlow elevates machine learning workflows by simplifying complex tasks such as Docker container management and caching. Written in Python, the mlcflow package offers a versatile interface, supporting both a user-friendly command-line interface (CLI) and a flexible API for effortless automation script management.

At its core, MLCFlow relies on a single powerful automation, the Script, which is extended by two actions: CacheAction and DockerAction. Together, these components provide streamlined functionality to optimize and enhance your ML workflow automation experience.


🤝 Contributing

We welcome contributions from the community! To contribute:

  1. Submit pull requests (PRs) to the dev branch.
  2. Review our CONTRIBUTORS.md for guidelines and best practices.
  3. Explore more about MLPerf Inference automation in the official MLPerf Inference Documentation.

Your contributions help drive the project forward!


💬 Join the Discussion

Connect with us on the MLCommons Benchmark Infra Discord channel to engage in discussions about MLCFlow and MLPerf Automations. We’d love to hear your thoughts, questions, and ideas!


📰 Stay Updated

Keep track of the latest development progress and tasks on our MLPerf Automations Development Board.
Stay tuned for exciting updates and announcements!


📄 License

This project is licensed under the Apache 2.0 License.


💡 Acknowledgments and Funding

This project is made possible through the generous support of:

We appreciate their contributions and sponsorship!


Thank you for your interest and support in MLPerf Automations and Scripts!

Release files for mlc-scripts 1.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for mlc-scripts 1.1.0
File Size Uploaded
mlc_scripts-1.1.0.tar.gz 9.5 kB Details

Release files / mlc_scripts-1.1.0.tar.gz

Download URL mlc_scripts-1.1.0.tar.gz
Size 9.5 kB
Tags Source
SHA-256 checksum
How to use checksums
b27e562086603afef237736cf07767ef3bcdbd6a0a27a611f3e574a529ae47c5
BLAKE2b-256 checksum
How to use checksums
41b8a228ace8b208c3d54b40823bd54ccd727001372a96c7ef78252cb1b9109d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 14, 2025.

Transparency log
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page