open-source

On June 11th, 2020, we launched the CASL (Composible, Automatic, and Scable ML) open source consortium that brings our research and development at Petuum Inc. and CMU Sailing Lab on Distributed ML (e.g., AutoDist, AdaptDL), Automated ML (e.g., Dragonfly, ProBO), and Composable ML (e.g., Texar, Forte) implemented across PyTorch and TensorFlow under a unified umbrella for a Production and Industrial AI Platform.

SAILING Members: If you want to add your open-source project to this page, please refer to the instruction.

project

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AdaptDL

Resource-adaptive cluster scheduler for deep learning training.
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AutoDist

Speed up and distribute your Deep Learning models automatically.
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Tuun

Efficient hyperparameter tuning via uncertainty modeling.
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Alpa

Auto parallelization for large-scale neural networks.
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Texar-PyTorch

Toolkit for Machine Learning and Text Generation.
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Texar

Toolkit for Machine Learning and Text Generation.
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Forte

NLP Pipeline with Text Analysis, Generation, & Retrieval.
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Stave

Building web interfaces for your NLP workflows.
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Betty

An automatic differentiation library for generalized meta-learning and multilevel optimization.
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Dragonfly

An open source python library for scalable Bayesian optimisation.
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Uncertainty Toolbox

A python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization.
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Contextualized

Contextualized is a statistical machine learning toolbox for estimating models, distributions, and functions with context-specific parameters.
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GenAMap

GenAMap is an open-source platform for visual machine learning of genome-phenome associations.
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Robustar

Interactive Toolbox for Robust Vision Classification.