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dataWithGCNSetting: Cora， Citeseer and PubMed. The dataset is split as training, validate, and test following the prior work (Kipf GCN).
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dtaGenerator.py: to read dataset
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Model.py: GCN model
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centeralizedTrain.py: train GCN in centeralized scenario.
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utils.py: includes some functions, such as the function to process adjacency matrix.
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clients: clients end
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sever.py: the server end to train GCN in Federated scenario.
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experimentsOfFed.py & experimentsOfLEpochs: experiments codes
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