A kind of training method and device of graph neural network corresponding to directed graph
A neural network and directed graph technology, applied in the field of graph neural networks, can solve the problems of increasing the data processing burden and increasing the data storage cost of the graph learning system, and achieve the effect of flexible training
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[0070] The technical solutions of the embodiments of the present specification will be described in detail below with reference to the accompanying drawings.
[0071] The embodiments of this specification disclose a method and device for training a graph neural network corresponding to a directed graph. The following first introduces the application scenarios and technical concepts of the method, as follows:
[0072] As mentioned above, in the current graph learning system, if you want to realize the training of graph neural network based on the same graph data flexibly combined with the direction of the edges, you need to do additional processing on the graph data, such as the DGL system (one A kind of graph learning system), which considers all graphs to be directed graphs. In the DGL system, when a directed graph is used as an undirected graph to train a graph neural network, the directed graph needs to be modified, that is, all the edges of the directed graph need to be mod...
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