pydgc

• pydgc.clusterings
  • pydgc.clusterings.batch_kmeans_gpu module
    • initialize()
    • kmeans()
    • kmeans_predict()
    • pairwise_distance()
  • pydgc.clusterings.kmeans_gpu module
    • KMeansGPU
      • KMeansGPU.initialize()
      • KMeansGPU.pairwise_distance()
      • KMeansGPU.pairwise_cosine()
      • KMeansGPU.fit()
      • KMeansGPU.predict()
• pydgc.datasets
  • pydgc.datasets.utils module
    • UserDataset
      • UserDataset.raw_file_names
      • UserDataset.processed_file_names
      • UserDataset.download()
      • UserDataset.process()
    • NonGraphDataset
      • NonGraphDataset.download()
      • NonGraphDataset.raw_file_names
      • NonGraphDataset.processed_dir
      • NonGraphDataset.processed_file_names
      • NonGraphDataset.process()
    • heat_kernel_knn_graph()
    • DGCGraphDataset
      • DGCGraphDataset.download()
    • DGCNonGraphDataset
      • DGCNonGraphDataset.download()
    • load_pyg()
    • load_dgc_graph()
    • load_dgc_non_graph()
    • load_ogb()
    • load_dataset()
    • preprocess_custom_data()
    • LoadAttribute
• pydgc.metrics
  • pydgc.metrics.utils module
    • DGCMetric
      • DGCMetric.accuracy()
      • DGCMetric.f1_score()
      • DGCMetric.nmi_score()
      • DGCMetric.ari_score()
      • DGCMetric.hom_score()
      • DGCMetric.com_score()
      • DGCMetric.sil_score()
      • DGCMetric.graph_reconstruction_error()
      • DGCMetric.purity()
      • DGCMetric.evaluate_one_epoch()
    • build_results_dict()
• pydgc.models
  • pydgc.models.ae
    • AE
      • AE.reset_parameters()
      • AE.forward()
      • AE.loss()
      • AE.train_model()
      • AE.get_embedding()
      • AE.clustering()
      • AE.evaluate()
      • AE.training
  • pydgc.models.agcdrr
    • new_graph()
    • normalize()
    • GNNLayer
      • GNNLayer.forward()
      • GNNLayer.training
    • IGAE_encoder
      • IGAE_encoder.forward()
      • IGAE_encoder.training
    • Cluster_layer
      • Cluster_layer.forward()
      • Cluster_layer.training
    • IGAE
      • IGAE.forward()
      • IGAE.calc_loss()
      • IGAE.training
    • ViewLearner
      • ViewLearner.init_emb()
      • ViewLearner.forward()
      • ViewLearner.training
    • AGCDRR
      • AGCDRR.reset_parameters()
      • AGCDRR.forward()
      • AGCDRR.loss()
      • AGCDRR.train_model()
      • AGCDRR.get_embedding()
      • AGCDRR.clustering()
      • AGCDRR.evaluate()
      • AGCDRR.training
  • pydgc.models.ccgc
    • init_clustering()
    • CCGC
      • CCGC.reset_parameters()
      • CCGC.forward()
      • CCGC.loss()
      • CCGC.train_model()
      • CCGC.get_embedding()
      • CCGC.clustering()
      • CCGC.evaluate()
      • CCGC.training
  • pydgc.models.daegc
    • GATE
      • GATE.reset_parameters()
      • GATE.forward()
      • GATE.loss()
      • GATE.train_model()
      • GATE.get_embedding()
      • GATE.clustering()
      • GATE.evaluate()
      • GATE.training
    • DAEGC
      • DAEGC.reset_parameters()
      • DAEGC.forward()
      • DAEGC.loss()
      • DAEGC.pretrain()
      • DAEGC.train_model()
      • DAEGC.get_embedding()
      • DAEGC.clustering()
      • DAEGC.evaluate()
      • DAEGC.training
  • pydgc.models.dcrn
    • normalize_adj()
    • numpy_to_torch()
    • remove_edge()
    • reconstruction_loss()
    • target_distribution()
    • distribution_loss()
    • r_loss()
    • off_diagonal()
    • cross_correlation()
    • correlation_reduction_loss()
    • dicr_loss()
    • gaussian_noised_feature()
    • AE_encoder
      • AE_encoder.forward()
      • AE_encoder.training
    • AE_decoder
      • AE_decoder.forward()
      • AE_decoder.training
    • AE
      • AE.forward()
      • AE.pretrain()
      • AE.evaluate()
      • AE.training
    • GNNLayer
      • GNNLayer.forward()
      • GNNLayer.training
    • IGAE_encoder
      • IGAE_encoder.forward()
      • IGAE_encoder.training
    • IGAE_decoder
      • IGAE_decoder.forward()
      • IGAE_decoder.training
    • IGAE
      • IGAE.forward()
      • IGAE.pretrain()
      • IGAE.training
    • Readout
      • Readout.forward()
      • Readout.training
    • DCRN
      • DCRN.reset_parameters()
      • DCRN.q_distribute()
      • DCRN.forward()
      • DCRN.loss()
      • DCRN.ae_igae_forward()
      • DCRN.pretrain()
      • DCRN.train_model()
      • DCRN.get_embedding()
      • DCRN.clustering()
      • DCRN.training
      • DCRN.evaluate()
  • pydgc.models.dfcn
    • target_distribution()
    • AE_encoder
      • AE_encoder.reset_parameters()
      • AE_encoder.forward()
      • AE_encoder.training
    • AE_decoder
      • AE_decoder.reset_parameters()
      • AE_decoder.forward()
      • AE_decoder.training
    • AE
      • AE.reset_parameters()
      • AE.forward()
      • AE.pretrain()
      • AE.training
    • GNNLayer
      • GNNLayer.reset_parameters()
      • GNNLayer.forward()
      • GNNLayer.training
    • IGAE_encoder
      • IGAE_encoder.reset_parameters()
      • IGAE_encoder.forward()
      • IGAE_encoder.training
    • IGAE_decoder
      • IGAE_decoder.reset_parameters()
      • IGAE_decoder.forward()
      • IGAE_decoder.training
    • IGAE
      • IGAE.reset_parameters()
      • IGAE.forward()
      • IGAE.pretrain()
      • IGAE.training
    • DFCN
      • DFCN.reset_parameters()
      • DFCN.forward()
      • DFCN.loss()
      • DFCN.ae_igae_forward()
      • DFCN.pretrain()
      • DFCN.train_model()
      • DFCN.training
      • DFCN.get_embedding()
      • DFCN.clustering()
      • DFCN.evaluate()
  • pydgc.models.dgc_model
    • DGCModel
      • DGCModel.reset_parameters()
      • DGCModel.forward()
      • DGCModel.loss()
      • DGCModel.train_model()
      • DGCModel.get_embedding()
      • DGCModel.clustering()
      • DGCModel.evaluate()
      • DGCModel.training
  • pydgc.models.dgcluster
    • convert_scipy_torch_sp()
    • aux_objective()
    • regularization()
    • DGCLUSTER
      • DGCLUSTER.training
      • DGCLUSTER.reset_parameters()
      • DGCLUSTER.forward()
      • DGCLUSTER.loss()
      • DGCLUSTER.train_model()
      • DGCLUSTER.get_embedding()
      • DGCLUSTER.clustering()
      • DGCLUSTER.evaluate()
  • pydgc.models.gae
    • GAE
      • GAE.reset_parameters()
      • GAE.forward()
      • GAE.loss()
      • GAE.train_model()
      • GAE.get_embedding()
      • GAE.clustering()
      • GAE.evaluate()
      • GAE.training
  • pydgc.models.gae_ssc
    • GAESSC
      • GAESSC.reset_parameters()
      • GAESSC.forward()
      • GAESSC.loss()
      • GAESSC.pretrain()
      • GAESSC.train_model()
      • GAESSC.get_embedding()
      • GAESSC.clustering()
      • GAESSC.evaluate()
      • GAESSC.training
  • pydgc.models.hsan
    • comprehensive_similarity()
    • hard_sample_aware_infoNCE()
    • square_euclid_distance()
    • phi()
    • HSAN
      • HSAN.reset_parameters()
      • HSAN.forward()
      • HSAN.high_confidence()
      • HSAN.pseudo_matrix()
      • HSAN.loss()
      • HSAN.train_model()
      • HSAN.get_embedding()
      • HSAN.clustering()
      • HSAN.evaluate()
      • HSAN.training
  • pydgc.models.magi
    • Encoder
      • Encoder.reset_parameters()
      • Encoder.forward()
      • Encoder.training
    • Loss
      • Loss.forward()
      • Loss.training
    • clustering()
    • scale()
    • MAGI
      • MAGI.reset_parameters()
      • MAGI.forward()
      • MAGI.loss()
      • MAGI.train_model()
      • MAGI.get_embedding()
      • MAGI.clustering()
      • MAGI.evaluate()
      • MAGI.training
  • pydgc.models.magi_batch
    • Encoder
      • Encoder.reset_parameters()
      • Encoder.forward()
      • Encoder.training
    • Loss
      • Loss.forward()
      • Loss.training
    • clustering()
    • scale()
    • EdgeIndex
      • EdgeIndex.edge_index
      • EdgeIndex.e_id
      • EdgeIndex.size
      • EdgeIndex.to()
    • Adj
      • Adj.adj_t
      • Adj.e_id
      • Adj.size
      • Adj.to()
    • NeighborSampler
      • NeighborSampler.drop_last
      • NeighborSampler.get_batch()
      • NeighborSampler.sample()
      • NeighborSampler.dataset
      • NeighborSampler.batch_size
      • NeighborSampler.num_workers
      • NeighborSampler.pin_memory
      • NeighborSampler.timeout
      • NeighborSampler.sampler
      • NeighborSampler.pin_memory_device
      • NeighborSampler.prefetch_factor
    • get_mask()
    • MAGIBatch
      • MAGIBatch.reset_parameters()
      • MAGIBatch.forward()
      • MAGIBatch.loss()
      • MAGIBatch.train_model()
      • MAGIBatch.get_embedding()
      • MAGIBatch.training
      • MAGIBatch.clustering()
      • MAGIBatch.evaluate()
  • pydgc.models.ns4gc
    • mask_feat()
    • drop_edge()
    • add_self_loop()
    • normalize()
    • sparse_identity()
    • sparse_diag()
    • augment()
    • GCNConv
      • GCNConv.reset_parameters()
      • GCNConv.forward()
      • GCNConv.training
    • NS4GC
      • NS4GC.reset_parameters()
      • NS4GC.embed()
      • NS4GC.forward()
      • NS4GC.loss()
      • NS4GC.train_model()
      • NS4GC.get_embedding()
      • NS4GC.clustering()
      • NS4GC.evaluate()
      • NS4GC.training
  • pydgc.models.sdcn
    • SDCN
      • SDCN.reset_parameters()
      • SDCN.forward()
      • SDCN.loss()
      • SDCN.pretrain()
      • SDCN.train_model()
      • SDCN.get_embedding()
      • SDCN.clustering()
      • SDCN.evaluate()
      • SDCN.training
• pydgc.modules
  • pydgc.modules.decoder
    • BaseDecoder
      • BaseDecoder.reset_parameters()
      • BaseDecoder.act_func
      • BaseDecoder.forward()
      • BaseDecoder.training
    • MLPDecoder
      • MLPDecoder.forward()
      • MLPDecoder.training
    • GNNAttributeDecoder
      • GNNAttributeDecoder.reset_parameters()
      • GNNAttributeDecoder.forward()
      • GNNAttributeDecoder.training
    • InnerProductDecoder
      • InnerProductDecoder.reset_parameters()
      • InnerProductDecoder.forward()
      • InnerProductDecoder.training
  • pydgc.modules.encoder
    • BaseEncoder
      • BaseEncoder.reset_parameters()
      • BaseEncoder.act_func
      • BaseEncoder.forward()
      • BaseEncoder.training
    • MLPEncoder
      • MLPEncoder.reset_parameters()
      • MLPEncoder.forward()
      • MLPEncoder.training
    • GNNEncoder
      • GNNEncoder.reset_parameters()
      • GNNEncoder.forward()
      • GNNEncoder.training
    • GATMEncoder
      • GATMEncoder.reset_parameters()
      • GATMEncoder.forward()
      • GATMEncoder.training
    • GATMConv
      • GATMConv.reset_parameters()
      • GATMConv.forward()
      • GATMConv.training
  • pydgc.modules.ssc
    • SSCLayer
      • SSCLayer.reset_parameters()
      • SSCLayer.forward()
      • SSCLayer.get_q()
      • SSCLayer.loss()
      • SSCLayer.training
  • pydgc.modules.utils
    • LayerRegistry
      • LayerRegistry.list_layers()
      • LayerRegistry.get_layer()
    • register_layer()
• pydgc.pipelines
  • pydgc.pipelines.agcdrr_pipeline
    • AGCDRRPipeline
      • AGCDRRPipeline.augment_data()
      • AGCDRRPipeline.build_model()
  • pydgc.pipelines.base_pipeline
    • BasePipeline
      • BasePipeline.load_config()
      • BasePipeline.load_logger()
      • BasePipeline.load_dataset()
      • BasePipeline.augment_data()
      • BasePipeline.build_model()
      • BasePipeline.evaluate()
      • BasePipeline.visualize()
      • BasePipeline.run()
  • pydgc.pipelines.ccgc_pipeline
    • preprocess_graph()
    • CCGCPipeline
      • CCGCPipeline.augment_data()
      • CCGCPipeline.build_model()
  • pydgc.pipelines.daegc_pipeline
    • DAEGCPipeline
      • DAEGCPipeline.augment_data()
      • DAEGCPipeline.build_model()
  • pydgc.pipelines.dcrn_pipeline
    • normalize_adj()
    • diffusion_adj()
    • sparse_mx_to_torch_sparse_tensor()
    • DCRNPipeline
      • DCRNPipeline.augment_data()
      • DCRNPipeline.build_model()
  • pydgc.pipelines.dfcn_pipeline
    • normalize()
    • sparse_mx_to_torch_sparse_tensor()
    • DFCNPipeline
      • DFCNPipeline.augment_data()
      • DFCNPipeline.build_model()
  • pydgc.pipelines.dgcluster_pipeline
    • DGCLUSTERPipeline
      • DGCLUSTERPipeline.augment_data()
      • DGCLUSTERPipeline.build_model()
  • pydgc.pipelines.gae_pipeline
    • GAEPipeline
      • GAEPipeline.augment_data()
      • GAEPipeline.build_model()
  • pydgc.pipelines.gae_ssc_pipeline
    • GAESSCPipeline
      • GAESSCPipeline.augment_data()
      • GAESSCPipeline.build_model()
  • pydgc.pipelines.hsan_pipeline
    • normalize_adj()
    • laplacian_filtering()
    • HSANPipeline
      • HSANPipeline.augment_data()
      • HSANPipeline.build_model()
  • pydgc.pipelines.magi_batch_pipeline
    • get_sim()
    • get_mask()
    • MAGIBatchPipeline
      • MAGIBatchPipeline.augment_data()
      • MAGIBatchPipeline.build_model()
  • pydgc.pipelines.magi_pipeline
    • get_sim()
    • get_mask()
    • MAGIPipeline
      • MAGIPipeline.augment_data()
      • MAGIPipeline.build_model()
  • pydgc.pipelines.ns4gc_pipeline
    • NS4GCPipeline
      • NS4GCPipeline.augment_data()
      • NS4GCPipeline.build_model()
  • pydgc.pipelines.sdcn_pipeline
    • SDCNPipeline
      • SDCNPipeline.augment_data()
      • SDCNPipeline.build_model()
• pydgc.utils
  • pydgc.utils.command
    • parse_arguments()
  • pydgc.utils.config
    • validate_and_create_path()
    • default_cfg()
    • yaml_to_cfg()
    • dump_cfg()
    • load_dataset_specific_cfg()
    • check_required_cfg()
    • generate_default_cfg()
  • pydgc.utils.device
    • count_parameters()
    • get_gpu_memory_map()
    • get_current_gpu_usage()
    • auto_select_device()
  • pydgc.utils.logger
    • get_formatted_time()
    • create_logger()
    • Logger
      • Logger.info()
      • Logger.error()
      • Logger.debug()
      • Logger.warning()
      • Logger.flag()
      • Logger.table()
      • Logger.loss()
      • Logger.model_info()
  • pydgc.utils.random
    • setup_seed()
  • pydgc.utils.transform
    • get_M()
    • target_distribution()
    • diffusion_adj()
    • add_gaussian_noise()
    • perturb_data()
    • sparse_mx_to_torch_sparse_tensor()
    • normalize_adj_torch()
  • pydgc.utils.visualization
    • DGCVisual
      • DGCVisual.check_save_format()
      • DGCVisual.plot_clustering()
      • DGCVisual.plot_heatmap()
      • DGCVisual.plot_loss()