dgl.dataο
The dgl.data
package contains datasets hosted by DGL and also utilities
for downloading, processing, saving and loading data from external resources.
Base Classο
The basic DGL dataset for creating graph datasets. |
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Dataset class that loads and parses graph data from CSV files. |
Node Prediction Datasetsο
Datasets for node classification/regression tasks
Stanford Sentiment Treebank dataset. |
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Karate Club dataset for Node Classification |
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Cora citation network dataset. |
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Citeseer citation network dataset. |
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Pubmed citation network dataset. |
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CORA-Full dataset for node classification task. |
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AIFB dataset for node classification task |
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MUTAG dataset for node classification task |
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BGS dataset for node classification task |
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AM dataset. |
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'Computer' part of the AmazonCoBuy dataset for node classification task. |
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AmazonCoBuy dataset for node classification task. |
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'Computer Science (CS)' part of the Coauthor dataset for node classification task. |
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'Physics' part of the Coauthor dataset for node classification task. |
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Protein-Protein Interaction dataset for inductive node classification |
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Reddit dataset for community detection (node classification) |
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Symmetric Stochastic Block Model Mixture |
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Fraud node prediction dataset. |
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Fraud Yelp Dataset |
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Fraud Amazon Dataset |
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BA-SHAPES dataset from GNNExplainer: Generating Explanations for Graph Neural Networks |
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BA-COMMUNITY dataset from GNNExplainer: Generating Explanations for Graph Neural Networks |
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TREE-CYCLES dataset from GNNExplainer: Generating Explanations for Graph Neural Networks |
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TREE-GRIDS dataset from GNNExplainer: Generating Explanations for Graph Neural Networks |
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Wiki-CS is a Wikipedia-based dataset for node classification from Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks |
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Flickr dataset for node classification from GraphSAINT: Graph Sampling Based Inductive Learning Method |
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Yelp dataset for node classification from GraphSAINT: Graph Sampling Based Inductive Learning Method |
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PATTERN dataset for graph pattern recognition task. |
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CLUSTER dataset for semi-supervised clustering task. |
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Wikipedia page-page network on chameleons from Multi-scale Attributed Node Embedding and later modified by Geom-GCN: Geometric Graph Convolutional Networks |
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Wikipedia page-page network on squirrels from Multi-scale Attributed Node Embedding and later modified by Geom-GCN: Geometric Graph Convolutional Networks |
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Actor-only induced subgraph of the film-directoractor-writer network from Social Influence Analysis in Large-scale Networks <https://dl.acm.org/doi/10.1145/1557019.1557108>, introduced by Geom-GCN: Geometric Graph Convolutional Networks <https://arxiv.org/abs/2002.05287> |
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Cornell subset of WebKB, later modified by Geom-GCN: Geometric Graph Convolutional Networks |
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Texas subset of WebKB, later modified by Geom-GCN: Geometric Graph Convolutional Networks |
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Wisconsin subset of WebKB, later modified by Geom-GCN: Geometric Graph Convolutional Networks |
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Roman-empire dataset from the 'A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress? <https://arxiv.org/abs/2302.11640>'__ paper. |
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Amazon-ratings dataset from the 'A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress? <https://arxiv.org/abs/2302.11640>'__ paper. |
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Minesweeper dataset from the 'A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress? <https://arxiv.org/abs/2302.11640>'__ paper. |
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Tolokers dataset from the 'A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress? <https://arxiv.org/abs/2302.11640>'__ paper. |
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Questions dataset from the 'A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress? <https://arxiv.org/abs/2302.11640>'__ paper. |
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MovieLens dataset for edge prediction tasks. |
Edge Prediction Datasetsο
Datasets for edge classification/regression and link prediction
FB15k237 link prediction dataset. |
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FB15k link prediction dataset. |
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WN18 link prediction dataset. |
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BitcoinOTC dataset for fraud detection |
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ICEWS18 dataset for temporal graph |
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GDELT dataset for event-based temporal graph |
Graph Prediction Datasetsο
Datasets for graph classification/regression tasks
QM7b dataset for graph property prediction (regression) |
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QM9 dataset for graph property prediction (regression) |
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QM9Edge dataset for graph property prediction (regression) |
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The synthetic graph classification dataset class. |
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TUDataset contains lots of graph kernel datasets for graph classification. |
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LegacyTUDataset contains lots of graph kernel datasets for graph classification. |
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Dataset Class for How Powerful Are Graph Neural Networks?. |
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Fake News Graph Classification dataset. |
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BA-2motifs dataset from Parameterized Explainer for Graph Neural Network |
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ZINC dataset for the graph regression task. |
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MNIST superpixel dataset for the graph classification task. |
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CIFAR10 superpixel dataset for the graph classification task. |
Dataset adaptersο
Repurpose a dataset for a standard semi-supervised transductive node prediction task. |
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Repurpose a dataset for link prediction task. |
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Repurpose a dataset for standard graph property prediction task. |
Utilitiesο
Get the absolute path to the download directory. |
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Download a given URL. |
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Check whether the sha1 hash of the file content matches the expected hash. |
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Extract archive file. |
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Split dataset into training, validation and test set. |
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Load label dict from file |
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Save dataset related information into disk. |
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Load dataset related information from disk. |
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Split the given dataset into training, validation and test sets for transductive node predction task. |
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Provide the split masks for a node split with distributional shift based on a given node property, as proposed in Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts |
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Create a node split with distributional shift based on a given node property, as proposed in Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts |
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Subset of a dataset at specified indices |