pygip.models package

Subpackages

• pygip.models.attack package
  • Subpackages
    • pygip.models.attack.mea package
      • Submodules
      • pygip.models.attack.mea.MEA module
      • Module contents
  • Submodules
  • pygip.models.attack.AdvMEA module
    • AdvMEA
      • AdvMEA._abc_impl
      • AdvMEA._load_model()
      • AdvMEA._to_cpu()
      • AdvMEA._train_target_model()
      • AdvMEA.attack()
      • AdvMEA.supported_api_types
  • pygip.models.attack.CEGA module
    • CEGA
      • CEGA._abc_impl
      • CEGA.attack()
      • CEGA.supported_api_types
    • GCN_drop
      • GCN_drop.forward()
    • GcnNet
      • GcnNet.forward()
    • accuracy()
    • attack0()
    • aug_normalized_adjacency()
    • aug_random_walk()
    • calculate_entropy()
    • compute_distance()
    • compute_rank()
    • convert_pyg_to_dgl()
    • evaluate()
    • find_short_dist()
    • get_current_neighbors_1()
    • get_current_neighbors_dense()
    • get_entropy_contribute()
    • get_max_info_entropy_node_set()
    • get_max_nnd_node_dense()
    • get_receptive_fields_dense()
    • init_mask()
    • load_data()
    • load_data_from_grain()
    • normalize()
    • page_rank()
    • parse_index_file()
    • perturb_avg()
    • perturb_features()
    • quantile_selection()
    • rank_centrality()
    • rank_cluster()
    • rank_density()
    • rank_diversity()
    • rank_entropy()
    • rank_perturb()
    • set_seed()
    • sparse_mx_to_torch_sparse_tensor()
    • update_sub_train_mask()
  • pygip.models.attack.DataFreeMEA module
    • DFEAAttack
      • DFEAAttack._abc_impl
      • DFEAAttack._forward()
      • DFEAAttack._load_model()
      • DFEAAttack._train_target_model()
      • DFEAAttack.attack()
      • DFEAAttack.evaluate()
      • DFEAAttack.supported_api_types
    • DFEATypeI
      • DFEATypeI._abc_impl
      • DFEATypeI.attack()
    • DFEATypeII
      • DFEATypeII._abc_impl
      • DFEATypeII.attack()
    • DFEATypeIII
      • DFEATypeIII._abc_impl
      • DFEATypeIII.attack()
    • GraphGenerator
      • GraphGenerator.generate()
  • pygip.models.attack.base module
    • BaseAttack
      • BaseAttack.supported_api_types
      • BaseAttack.supported_datasets
      • BaseAttack.device
      • BaseAttack.dataset
      • BaseAttack.graph_dataset
      • BaseAttack.graph_data
      • BaseAttack.num_nodes
      • BaseAttack.num_features
      • BaseAttack.num_classes
      • BaseAttack.attack_node_fraction
      • BaseAttack.model_path
      • BaseAttack._abc_impl
      • BaseAttack._check_dataset_compatibility()
      • BaseAttack._load_model()
      • BaseAttack._train_attack_model()
      • BaseAttack._train_target_model()
      • BaseAttack.attack()
      • BaseAttack.supported_api_types
      • BaseAttack.supported_datasets
  • Module contents
    • AdvMEA
      • AdvMEA._abc_impl
      • AdvMEA._load_model()
      • AdvMEA._to_cpu()
      • AdvMEA._train_target_model()
      • AdvMEA.attack()
      • AdvMEA.supported_api_types
    • CEGA
      • CEGA._abc_impl
      • CEGA.attack()
      • CEGA.supported_api_types
    • DFEATypeI
      • DFEATypeI._abc_impl
      • DFEATypeI.attack()
    • DFEATypeII
      • DFEATypeII._abc_impl
      • DFEATypeII.attack()
    • DFEATypeIII
      • DFEATypeIII._abc_impl
      • DFEATypeIII.attack()
    • ModelExtractionAttack0
      • ModelExtractionAttack0._abc_impl
      • ModelExtractionAttack0.attack()
      • ModelExtractionAttack0.get_nonzero_indices()
    • ModelExtractionAttack1
      • ModelExtractionAttack1._abc_impl
      • ModelExtractionAttack1.attack()
    • ModelExtractionAttack2
      • ModelExtractionAttack2._abc_impl
      • ModelExtractionAttack2.attack()
    • ModelExtractionAttack3
      • ModelExtractionAttack3._abc_impl
      • ModelExtractionAttack3.attack()
    • ModelExtractionAttack4
      • ModelExtractionAttack4._abc_impl
      • ModelExtractionAttack4.attack()
    • ModelExtractionAttack5
      • ModelExtractionAttack5._abc_impl
      • ModelExtractionAttack5.attack()
    • RealisticAttack
      • RealisticAttack._abc_impl
      • RealisticAttack.add_potential_edges()
      • RealisticAttack.attack()
      • RealisticAttack.compute_cosine_similarity()
      • RealisticAttack.evaluate_attack()
      • RealisticAttack.generate_candidate_edges()
      • RealisticAttack.simulate_target_model_queries()
      • RealisticAttack.supported_api_types
      • RealisticAttack.supported_datasets
      • RealisticAttack.train_edge_predictor()
      • RealisticAttack.train_surrogate_model()
• pygip.models.defense package
  • Subpackages
    • pygip.models.defense.atom package
      • Submodules
      • pygip.models.defense.atom.ATOM module
      • Module contents
  • Submodules
  • pygip.models.defense.BackdoorWM module
    • BackdoorWM
      • BackdoorWM._abc_impl
      • BackdoorWM._load_model()
      • BackdoorWM.defend()
      • BackdoorWM.evaluate_model()
      • BackdoorWM.inject_backdoor_trigger()
      • BackdoorWM.supported_api_types
      • BackdoorWM.train_target_model()
      • BackdoorWM.verify_backdoor()
  • pygip.models.defense.ImperceptibleWM module
    • ImperceptibleWM
      • ImperceptibleWM._abc_impl
      • ImperceptibleWM._load_model()
      • ImperceptibleWM._train_defense_model()
      • ImperceptibleWM._train_surrogate_model()
      • ImperceptibleWM._train_target_model()
      • ImperceptibleWM.defend()
      • ImperceptibleWM.supported_api_types
    • TriggerGenerator
      • TriggerGenerator.forward()
    • bi_level_optimization()
    • calculate_metrics()
    • generate_trigger_graph()
  • pygip.models.defense.ImperceptibleWM2 module
    • ImperceptibleWM2
      • ImperceptibleWM2._abc_impl
      • ImperceptibleWM2._calculate_embedding_loss()
      • ImperceptibleWM2._calculate_generation_loss_integrated()
      • ImperceptibleWM2._calculate_imperception_loss()
      • ImperceptibleWM2._calculate_regulation_loss()
      • ImperceptibleWM2._calculate_trigger_loss()
      • ImperceptibleWM2._construct_backdoor_graph()
      • ImperceptibleWM2._create_temp_trigger_graph()
      • ImperceptibleWM2._evaluate_model_on_graph()
      • ImperceptibleWM2._evaluate_with_metrics()
      • ImperceptibleWM2._generate_trigger_graph()
      • ImperceptibleWM2._inner_optimization()
      • ImperceptibleWM2._select_poisoning_nodes()
      • ImperceptibleWM2._train_defense_model()
      • ImperceptibleWM2._train_target_model()
      • ImperceptibleWM2.defend()
      • ImperceptibleWM2.verify_ownership()
    • TriggerGenerator
      • TriggerGenerator._create_template_graph()
      • TriggerGenerator.forward()
  • pygip.models.defense.RandomWM module
    • RandomWM
      • RandomWM._abc_impl
      • RandomWM._evaluate_attack_on_watermark()
      • RandomWM._evaluate_watermark()
      • RandomWM._generate_watermark_graph()
      • RandomWM._get_attack_class()
      • RandomWM._test_on_watermark()
      • RandomWM._train_defense_model()
      • RandomWM._train_target_model()
      • RandomWM.defend()
      • RandomWM.supported_api_types
  • pygip.models.defense.SurviveWM module
    • SurviveWM
      • SurviveWM._abc_impl
      • SurviveWM._load_model()
      • SurviveWM._to_cpu()
      • SurviveWM.combine_with_trigger()
      • SurviveWM.compute_metrics()
      • SurviveWM.defend()
      • SurviveWM.generate_key_graph()
      • SurviveWM.snn_loss()
      • SurviveWM.supported_api_types
      • SurviveWM.train_with_snnl()
      • SurviveWM.verify_watermark()
  • pygip.models.defense.SurviveWM2 module
    • KeyInputOptimizer
      • KeyInputOptimizer.optimize()
    • SAGEModel
      • SAGEModel.forward()
    • SNNLLoss
      • SNNLLoss.forward()
    • SurviveWM2
      • SurviveWM2._abc_impl
      • SurviveWM2._load_model()
      • SurviveWM2._train_defense_model()
      • SurviveWM2._train_surrogate_model()
      • SurviveWM2._train_target_model()
      • SurviveWM2.defend()
    • WatermarkGenerator
      • WatermarkGenerator._get_avg_num_nodes()
      • WatermarkGenerator._get_num_classes()
      • WatermarkGenerator.algorithm_1_key_input_topology_generation()
      • WatermarkGenerator.generate_watermark_set_with_clean_model()
    • evaluate_clean_accuracy()
    • evaluate_watermark_effectiveness()
    • train_clean_model()
    • train_watermarked_model_full()
  • pygip.models.defense.base module
    • BaseDefense
      • BaseDefense._abc_impl
      • BaseDefense._check_dataset_compatibility()
      • BaseDefense._load_model()
      • BaseDefense._train_defense_model()
      • BaseDefense._train_surrogate_model()
      • BaseDefense._train_target_model()
      • BaseDefense.defend()
      • BaseDefense.supported_api_types
      • BaseDefense.supported_datasets
  • Module contents
    • ATOM
      • ATOM._abc_impl
      • ATOM._load_data_and_model()
      • ATOM.defend()
      • ATOM.supported_api_types
      • ATOM.supported_datasets
    • BackdoorWM
      • BackdoorWM._abc_impl
      • BackdoorWM._load_model()
      • BackdoorWM.defend()
      • BackdoorWM.evaluate_model()
      • BackdoorWM.inject_backdoor_trigger()
      • BackdoorWM.supported_api_types
      • BackdoorWM.train_target_model()
      • BackdoorWM.verify_backdoor()
    • ImperceptibleWM
      • ImperceptibleWM._abc_impl
      • ImperceptibleWM._load_model()
      • ImperceptibleWM._train_defense_model()
      • ImperceptibleWM._train_surrogate_model()
      • ImperceptibleWM._train_target_model()
      • ImperceptibleWM.defend()
      • ImperceptibleWM.supported_api_types
    • ImperceptibleWM2
      • ImperceptibleWM2._abc_impl
      • ImperceptibleWM2._calculate_embedding_loss()
      • ImperceptibleWM2._calculate_generation_loss_integrated()
      • ImperceptibleWM2._calculate_imperception_loss()
      • ImperceptibleWM2._calculate_regulation_loss()
      • ImperceptibleWM2._calculate_trigger_loss()
      • ImperceptibleWM2._construct_backdoor_graph()
      • ImperceptibleWM2._create_temp_trigger_graph()
      • ImperceptibleWM2._evaluate_model_on_graph()
      • ImperceptibleWM2._evaluate_with_metrics()
      • ImperceptibleWM2._generate_trigger_graph()
      • ImperceptibleWM2._inner_optimization()
      • ImperceptibleWM2._select_poisoning_nodes()
      • ImperceptibleWM2._train_defense_model()
      • ImperceptibleWM2._train_target_model()
      • ImperceptibleWM2.defend()
      • ImperceptibleWM2.verify_ownership()
    • RandomWM
      • RandomWM._abc_impl
      • RandomWM._evaluate_attack_on_watermark()
      • RandomWM._evaluate_watermark()
      • RandomWM._generate_watermark_graph()
      • RandomWM._get_attack_class()
      • RandomWM._test_on_watermark()
      • RandomWM._train_defense_model()
      • RandomWM._train_target_model()
      • RandomWM.defend()
      • RandomWM.supported_api_types
    • SurviveWM
      • SurviveWM._abc_impl
      • SurviveWM._load_model()
      • SurviveWM._to_cpu()
      • SurviveWM.combine_with_trigger()
      • SurviveWM.compute_metrics()
      • SurviveWM.defend()
      • SurviveWM.generate_key_graph()
      • SurviveWM.snn_loss()
      • SurviveWM.supported_api_types
      • SurviveWM.train_with_snnl()
      • SurviveWM.verify_watermark()
    • SurviveWM2
      • SurviveWM2._abc_impl
      • SurviveWM2._load_model()
      • SurviveWM2._train_defense_model()
      • SurviveWM2._train_surrogate_model()
      • SurviveWM2._train_target_model()
      • SurviveWM2.defend()
• pygip.models.nn package
  • Submodules
  • pygip.models.nn.backbones module
    • AttackNet
      • AttackNet.forward()
    • GAT
      • GAT.forward()
    • GCN
      • GCN.forward()
    • GCN_PyG
      • GCN_PyG.forward()
    • GraphSAGE
      • GraphSAGE.forward()
    • ShadowNet
      • ShadowNet.forward()
  • Module contents

Module contents