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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="CASL is for machine learning in the real world. Open source projects making up CASL include AdaptDL, AutoDist, Tuun, Texar, Texar-PyTorch, Forte, Stave, Alpa. Partners include Petuum, Carnegie Mellon, MBZUAI, Stanford, and Berkeley.">
<!-- casl-summary specific assets -->
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<link href="casl-summary-assets/css/carousel.css" rel="stylesheet" />
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<link rel="manifest" href="../site.webmanifest">
<title>CASL Projects - An open toolkit for composable, automatic, and scalable learning</title>
</head>
<body style="min-width: unset; width: unset;">
<div class="container marketing">
<!-- Three columns of text below the carousel -->
<!-- First Row -->
<div class="row">
<div class="col-lg-3">
<div class="threecard">
<div class="logo-group">
<img
class="img-circle"
src="casl-summary-assets/assets/adaptdl-text.png"
alt="adapt_dl"
height="70"
/>
</div>
<div class="short-description">
<p>Resource-adaptive cluster scheduler for deep learning training.</p>
</div>
<h2 class="card-button">
<a href="#">
AdaptDL: About
</a>
<div class="card-description">
<span class="card-desc-close">×</span>
AdaptDL is a resource-adaptive deep learning (DL) training and scheduling framework. The goal of AdaptDL is to make distributed DL easy and efficient in dynamic-resource environments such as shared clusters and the cloud.
</div>
</h2>
<div class="marketing-buttons">
<p>
<a
class="btn btn-default"
href="https://github.com/petuum/adaptdl"
role="button"
target="_blank"
>
<img
src="casl-summary-assets/assets/GitHub-Mark-32px.png"
/>Github »</a
>
<a
class="btn btn-default"
href="https://adaptdl.readthedocs.org/"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/document-icon.png"
/>Docs »</a
>
</p>
<p>
<a
class="btn btn-default"
href="https://github.com/petuum/adaptdl/tree/master/examples"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/example-icon.png"
/>Examples »</a
>
<a
class="btn btn-default"
href="https://adaptdl.readthedocs.io/en/latest/"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/teacher-icon.png"
/>Tutorials »</a
>
</p>
</div>
</div>
</div>
<div class="col-lg-3">
<div class="threecard">
<div class="logo-group">
<img
class="img-circle"
src="casl-summary-assets/assets/autodist-text.png"
alt="autodist"
height="55"
/>
</div>
<div class="short-description">
<p>Speed up and distribute your Deep Learning models automatically.</p>
</div>
<h2 class="card-button">
<a href="#">
AutoDist: About
</a>
<div class="card-description">
<span class="card-desc-close">×</span>
AutoDist is a distributed deep learning training engine for TensorFlow. AutoDist provides a user-friendly interface to distribute the training of a wide variety deep learning models across many GPUs with scalability and minimal code change.
</div>
</h2>
<div class="marketing-buttons">
<p>
<a
class="btn btn-default"
href="https://github.com/petuum/autodist"
role="button"
target="_blank"
>
<img
src="casl-summary-assets/assets/GitHub-Mark-32px.png"
/>Github »</a
>
<a
class="btn btn-default"
href="https://petuum.github.io/autodist"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/document-icon.png"
/>Docs »</a
>
</p>
<p>
<a
class="btn btn-default"
href="https://github.com/petuum/autodist/tree/master/examples/benchmark"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/example-icon.png"
/>Examples »</a
>
<a
class="btn btn-default"
href="https://petuum.github.io/autodist/usage/tutorials/getting-started.html"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/teacher-icon.png"
/>Tutorials »</a
>
</p>
</div>
</div>
</div>
<div class="col-lg-3">
<div class="threecard">
<div class="logo-group">
<img
class="img-circle"
src="casl-summary-assets/assets/tuun.png"
alt="tuun"
height="48"
/>
</div>
<div class="short-description">
<p>Efficient hyperparameter tuning via uncertainty modeling</p>
</div>
<h2 class="card-button">
<a href="#">
Tuun: About
</a>
<div class="card-description">
<span class="card-desc-close">×</span>
Tuun is a toolkit for efficient hyperparameter tuning via uncertainty modeling, with a focus on flexible model choice, scalability, and use in distributed settings.
</div>
</h2>
<div class="marketing-buttons">
<p>
<a
class="btn btn-default"
href="https://github.com/petuum/tuun"
role="button"
target="_blank"
>
<img
src="casl-summary-assets/assets/GitHub-Mark-32px.png"
/>Github »</a
>
<a
class="btn btn-default"
href="https://petuum.github.io/tuun/"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/document-icon.png"
/>Docs »</a
>
</p>
<p>
<a
class="btn btn-default"
href="https://github.com/petuum/tuun/tree/master/examples"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/example-icon.png"
/>Examples »</a
>
<a
class="btn btn-default"
href="https://petuum.github.io/tuun/quick_start.html"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/teacher-icon.png"
/>Tutorials »</a
>
</p>
</div>
</div>
</div>
<div class="col-lg-3">
<div class="threecard">
<div class="logo-group">
<img
class="img-circle"
src="casl-summary-assets/assets/alpa-text.png"
alt="alpa"
height="43"
/>
</div>
<div class="short-description">
<p>Auto parallelization for large-scale neural networks</p>
</div>
<h2 class="card-button">
<a href="#">
Alpa: About
</a>
<div class="card-description">
<span class="card-desc-close">×</span>
Alpa is a system for large-scale distributed training. Alpa is specifically designed for training giant neural networks that cannot fit into a single device.
</div>
</h2>
<div class="marketing-buttons">
<p>
<a
class="btn btn-default"
href="https://github.com/alpa-projects/alpa"
role="button"
target="_blank"
>
<img
src="casl-summary-assets/assets/GitHub-Mark-32px.png"
/>Github »</a
>
<a
class="btn btn-default"
href="https://alpa-projects.github.io/"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/document-icon.png"
/>Docs »</a
>
</p>
<p>
<a
class="btn btn-default"
href="https://alpa-projects.github.io/tutorials/"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/example-icon.png"
/>Examples »</a
>
<a
class="btn btn-default"
href="https://alpa-projects.github.io/developer/developer_guide.html"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/teacher-icon.png"
/>Tutorials »</a
>
</p>
</div>
</div>
</div>
</div>
<!-- Second Row -->
<div class="row">
<div class="col-lg-3">
<div class="threecard">
<div class="logo-group">
<img
class="img-circle"
src="casl-summary-assets/assets/texar-text.png"
alt="texar"
height="55"
/>
<img
class="texar-subcategory-img"
class="img-circle"
src="casl-summary-assets/assets/tensorflow.png"
alt="texar"
/>
</div>
<div class="short-description">
<p>Toolkit for Machine Learning and Text Generation</p>
</div>
<h2 class="card-button">
<a href="#">
Texar-TF: About
</a>
<div class="card-description">
<span class="card-desc-close">×</span>
Texar is a highly modularized and customizable toolkit to support a broad set of machine
learning (ML), especially natural language processing (NLP) and text generation tasks.</br></br>
Texar provides comprehensive modules for <b>data processing</b>, <b>model architectures</b>,
<b>loss functions</b>, <b>training and inference algorithms</b>, <b>evaluation</b>, etc.
</br></br>
Use Texar to compose whatever models and algorithms you want.
</div>
</h2>
<div class="marketing-buttons">
<p>
<a
class="btn btn-default"
href="https://github.com/asyml/texar"
role="button"
target="_blank"
>
<img
src="casl-summary-assets/assets/GitHub-Mark-32px.png"
/>Github »</a
>
<a
class="btn btn-default"
href="https://texar.readthedocs.io/en/latest/"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/document-icon.png"
/>Docs »</a
>
</p>
<p>
<a
class="btn btn-default"
href="https://github.com/asyml/texar/tree/master/examples"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/example-icon.png"
/>Examples »</a
>
<a
class="btn btn-default"
href="https://github.com/asyml/texar/tree/master/examples"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/teacher-icon.png"
/>Tutorials »</a
>
</p>
</div>
</div>
</div>
<div class="col-lg-3">
<div class="threecard">
<div class="logo-group">
<img
class="img-circle"
src="casl-summary-assets/assets/texar-text.png"
alt="texar"
height="55"
/>
<img
class="texar-subcategory-img"
class="img-circle"
src="casl-summary-assets/assets/pytorch.png"
alt="texar"
/>
</div>
<div class="short-description">
<p>Toolkit for Machine Learning and Text Generation</p>
</div>
<h2 class="card-button">
<a href="#">
Texar-PyTorch: About
</a>
<div class="card-description">
<span class="card-desc-close">×</span>
Texar-PyTorch is the PyTorch equivalence of Texar-TF, with mostly the <b>same</b>
interfaces. </br></br>
Texar-PyTorch integrates many of the best features of TensorFlow into PyTorch,
delivering a set of highly usable and customizable modules superior to PyTorch
native ones, including
<ul>
<li> <b>Data:</b> More ready-to-use APIs; more customizable; more efficient
<li> <b>Model:</b> Better factorization; more comprehensive high-level APIs
<li> <b>Training:</b> High-level APIs to avoid any boilerplate code
</ul>
</div>
</h2>
<div class="marketing-buttons">
<p>
<a
class="btn btn-default"
href="https://github.com/asyml/texar-pytorch"
role="button"
target="_blank"
>
<img
src="casl-summary-assets/assets/GitHub-Mark-32px.png"
/>Github »</a
>
<a
class="btn btn-default"
href="https://texar-pytorch.readthedocs.io/en/latest"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/document-icon.png"
/>Docs »</a
>
</p>
<p>
<a
class="btn btn-default"
href="https://github.com/asyml/texar-pytorch/tree/master/examples"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/example-icon.png"
/>Examples »</a
>
<a
class="btn btn-default"
href="https://github.com/asyml/texar-pytorch/tree/master/examples"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/teacher-icon.png"
/>Tutorials »</a
>
</p>
</div>
</div>
</div>
<div class="col-lg-3">
<div class="threecard">
<div class="logo-group">
<img
class="img-circle"
src="casl-summary-assets/assets/Forte-dark-text.png"
alt="forte"
height="55"
/>
</div>
<div class="short-description">
<p>NLP Pipeline with Text Analysis, Generation, & Retrieval</p>
</div>
<h2 class="card-button">
<a href="#">
Forte: About
</a>
<div class="card-description">
<span class="card-desc-close">×</span>
Forte is a high-level and customizable toolkit for building arbitrary complex NLP pipelines.
With Forte, you can:
<ul>
<li> Plug in any NLP components in a pipeline, including <b>text analysis</b>,
<b>generation</b>, <b>retrieval</b>, etc.
<li> Wrap any off-the-shelf NLP models from other libraries as pipeline components,
such as <b>spaCy</b>, <b>StanfordNLP</b>, <b>AllenNLP</b>, etc.
<li> Obtain a <b>uniform representation</b> of data and intermediate results throughout
pipeline.
</ul>
</div>
</h2>
<div class="marketing-buttons">
<p>
<a
class="btn btn-default"
href="https://github.com/asyml/forte"
role="button"
target="_blank"
>
<img
src="casl-summary-assets/assets/GitHub-Mark-32px.png"
/>Github »</a
>
<a
class="btn btn-default"
href="https://asyml-forte.readthedocs.io/en/latest/?badge=latest"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/document-icon.png"
/>Docs »</a
>
</p>
<p>
<a
class="btn btn-default"
href="https://github.com/asyml/forte/tree/master/examples"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/example-icon.png"
/>Examples »</a
>
<a
class="btn btn-default"
href="https://github.com/asyml/forte/wiki"
role="button"
target="_blank"
><img
src="casl-summary-assets/assets/teacher-icon.png"
/>Tutorials »</a
>
</p>
</div>
</div>
</div>
<div class="col-lg-3">
<div class="threecard">
<div class="logo-group">
<img
class="img-circle"
src="casl-summary-assets/assets/[email protected]"
alt="stave"
height="55"
/>
</div>
<div class="short-description">
<p>Building web interfaces for your NLP workflows</p>
</div>
<h2 class="card-button">
<a href="#">
Stave: About
</a>
<div class="card-description">
<span class="card-desc-close">×</span>
Stave is a extendable toolkit for building front end interfaces for NLP projects.
Stave excels at:
<ui>
<li>A general annotation and visualization interface for core NLP tasks.</li>
<li>Integrated and backed up by the strong machine learning and NLP toolkit built by ASYML: Texar and Forte.</li>
<li>Can be easily extended by building plugins for your requirements.</li>
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</h2>
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<p>An automatic differentiation library for generalized
meta-learning and multilevel optimization</p>
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Betty: About
</a>
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Betty is a PyTorch library for generalized-meta learning
(GML) and multilevel optimization (MLO) that provides a
unified programming interface for a number of GML/MLO
applications including meta-learning, hyperparameter
optimization, neural architecture search, data reweighting,
adversarial learning, and reinforcement learning.
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