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DGL - Deep Graph Library DGL empowers a variety of domain-specific projects including DGL-KE for learning large-scale knowledge graph embeddings, DGL-LifeSci for bioinformatics and cheminformatics, and many others
Deglycyrrhizinated Licorice (DGL): Gut Benefits and Beyond One of my all-time favorites is deglycyrrhizinated licorice, or DGL The reason I love this supplement is that it addresses many health issues, and I am a big fan of addressing many issues with one stone, so to speak Licorice has been used in many forms throughout the centuries by many cultures
DGL for acid reflux: Benefits, risks, and other options Deglycyrrhizinated licorice (DGL) is licorice that does not contain glycyrrhizic acid Some people think DGL can reduce acid reflux, but the evidence is inconclusive
Dgl | Anaconda. org DGL is an easy-to-use, high performance and scalable Python package for deep learning on graphs DGL is framework agnostic, meaning if a deep graph model is a component of an end-to-end application, the rest of the logics can be implemented in any major frameworks, such as PyTorch, Apache MXNet or TensorFlow
Releases · dmlc dgl - GitHub We're thrilled to announce the release of DGL 2 2 1 🎉🎉🎉 The supported PyTorch versions are 2 1 0 1 2, 2 2 0 1 2, 2 3 0 See install command here MiniBatch in GraphBolt is refactored: seed_nodes and node_paris are replaced with unified seeds attribute through out the pipeline Refer to the latest examples for more details by @yxy235
DGL Overview - NVIDIA Docs The NVIDIA® Deep Learning SDK accelerates widely-used deep learning frameworks such as DGL DGL is an easy-to-use, high performance and scalable Python package for deep learning on graphs
GitHub - dmlc dgl: Python package built to ease deep learning on graph . . . DGL is an easy-to-use, high performance and scalable Python package for deep learning on graphs DGL is framework agnostic, meaning if a deep graph model is a component of an end-to-end application, the rest of the logics can be implemented in any major frameworks, such as PyTorch, Apache MXNet or TensorFlow
Deep Graph Library - DGL Amazon SageMaker now supports DGL, simplifying implementation of DGL models A Deep Learning container (MXNet 1 6 and PyTorch 1 3) bundles all the software dependencies and the SageMaker API automatically sets up and scales the infrastructure required to train graphs