Custom motif generation #6179
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Custom motif generation #6179
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rusty1s
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explain
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BlazStojanovic
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Dec 12, 2022
rusty1s
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Dec 12, 2022
This PR implements benchmark dataset overall framework and API for generating benchmark datasets (#5817). Any feedback is appreciated, especially regarding the proposed architecture. ### Implementing a new graph generator - Create a class inside generators inheriting from GraphGenerator - Implement `generate_base_graph` using the provided methods (`generate_feature` and `attach_motif`) - See #6072 and #6073 to check how it was implemented - The current Motif generator used here will be replaced by #6179 ### Example for the final user ``` motif = Motif('house') generator = BAGraph(num_nodes=300, num_motifs=80, motif=motif) dataset = ExplainerDataset(generator) ``` TODO: - [x] Finish graph generator (provide all necessary methods: feature generator, label generator) - [x] Add tests - [x] Add to Change log - [x] Documentation Co-authored-by: rusty1s <matthias.fey@tu-dortmund.de>
rusty1s
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This task is part of GNN Explainability Dataset Generation
Implementation of the base class for motif generation. It depends on the framework and API to generate benchmark datasets.
The base class follows some of the structure from @rfdavid PRs. However, I changed a bit since I believe using Data is a better and cleaner approach to generate structures and create wrappers for other structures in PyG or NetworkX.
Once I have some feedback about the
MotifGenerator, I will go ahead andGraphGenerator.attach_motif()