Deep Graph Library (DGL)
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About
Deep Graph Library (DGL) is a Python library designed to simplify the implementation of graph neural network (GNN) models, integrating seamlessly with existing deep learning frameworks like PyTorch, MXNet, and TensorFlow. DGL focuses on optimizing communication during message passing for GNNs, employing advanced techniques such as auto-batching and optimized sparse matrix operations to facilitate training on large graphs containing millions of nodes and edges. It provides various resources including tutorials for beginners and advanced users, an API reference manual, and guidance on stochastic training methodologies, multi-GPU training, and distributed setups.
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Task
Features
• comprehensive documentation and tutorials
• api reference for easy use
• auto-batching for speed optimization
• optimized for large-scale graph training
• supports pytorch, mxnet, tensorflow
• python package for gnns
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