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<h3 style="background-color:powderblue;">[Deprecated!] GraphStorm documentations have moved to <a href="https://graphstorm.readthedocs.io/en/latest/">graphstorm.readthedocs.io</a>.</h3>

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<h1>Welcome to the GraphStorm v0.1.2 Documentation and Tutorials<a class="headerlink" href="#welcome-to-the-graphstorm-documentation-and-tutorials" title="Permalink to this heading">#</a></h1> <div class="toctree-wrapper compound"> </div> <div class="toctree-wrapper compound"> </div> <div class="toctree-wrapper compound"> </div> <div class="toctree-wrapper compound"> </div> <p>GraphStorm is a graph machine learning (GML) framework designed for enterprise use cases. It simplifies the development, training and deployment of GML models on industry-scale graphs (measured in billons of nodes and edges) by providing scalable training and inference pipelines of GML models. GraphStorm comes with a collection of built-in GML models, allowing users to train a GML model with a single command, eliminating the need to write any code. Moreover, GraphStorm provides a wide range of configurations to customiz model implementations and training pipelines, enhancing model performance. In addition, GraphStorm offers a programming interface that enables users to train custom GML models in a distributed manner. Users can bring their own model implementations and leverage the GraphStorm training pipeline for scalability.</p> <section id="getting-started"> <h2>Getting Started<a class="headerlink" href="#getting-started" title="Permalink to this heading">#</a></h2> <p>For beginners, please first start with the <a class="reference internal" href="install-env-setup#setup"><span class="std std-ref">GraphStorm Docker environment setup</span></a>. This tutorial covers how to set up a Docker environment and build a GraphStorm Docker image, which serves as the Standalone running environment for GraphStorm. We are working on supporting more running environments for GraphStorm.</p> <p>Once successfully set up the GraphStorm Docker running environment,</p> <ul class="simple"> <li><p>follow the <a class="reference internal" href="tutorials-quick-start#quick-start-standalone"><span class="std std-ref">GraphStorm Standalone Mode Quick-Start Tutorial</span></a> to run examples using GraphStorm built-in data and models, hence getting familiar with GraphStorm’s usage of training and inference.</p></li> <li><p>follow the <a class="reference internal" href="tutorials-own-data#use-own-data"><span class="std std-ref">Use Your Own Graph Data Tutorial</span></a> to prepare your own graph data for using GraphStorm.</p></li> <li><p>read the <a class="reference internal" href="configuration-configuration-run#configurations-run"><span class="std std-ref">GraphStorm Training and Inference Configurations</span></a> to learn the various configurations provided by GraphStorm that can help to achieve the best performance.</p></li> </ul> </section> <section id="scale-to-giant-graphs"> <h2>Scale to Giant Graphs<a class="headerlink" href="#scale-to-giant-graphs" title="Permalink to this heading">#</a></h2> <p>For experienced users who wish to train and run infernece on very large graphs,</p> <ul class="simple"> <li><p>follow the <a class="reference internal" href="scale-distributed#distributed-cluster"><span class="std std-ref">Use GraphStorm in a Distributed Cluster</span></a> tutorial to use GraphStorm in the Distributed mode.</p></li> <li><p>follow the <a class="reference internal" href="scale-sagemaker"><span class="std std-ref">Use GraphStorm on SageMaker</span></a> tutorial to use GraphStorm in the Distribute mode based on Amazon SageMaker.</p></li> </ul> </section> <section id="advanced-topics"> <h2>Advanced Topics<a class="headerlink" href="#advanced-topics" title="Permalink to this heading">#</a></h2> <p>For users who want to use their own GML models in GraphStorm,</p> <ul class="simple"> <li><p>follow the <a class="reference internal" href="advanced-own-models#use-own-models"><span class="std std-ref">Use Your Own GNN Models</span></a> tutorial to learn the programming interfaces and the steps of how to modify users’ own models.</p></li> <li><p>For users who want to use text as node features, follow the <a class="reference internal" href="advanced-language-models#"><span class="std std-ref">Use Text as Node Features</span></a> tutorial to learn how to leverage BERT models to use text as node features in GraphStorm.</p></li> <li><p>There are various usages of GraphStorm helping to both speed up training process and boost model performance. Users can find these usages in the <a class="reference internal" href="graphstorm-advanced-usages#"><span class="std std-ref">Advanced Usages</span></a> page.</p></li> </ul> </section> <section id="contribution"> <h2>Contribution<a class="headerlink" href="#contribution" title="Permalink to this heading">#</a></h2> <p>GraphStorm is free software; you can redistribute it and/or modify it under the terms of the Apache License 2.0. We welcome contributions. Join us on <a class="reference external" href="https://github.com/awslabs/graphstorm">GitHub</a>.</p> </section> </section>