MEDfl package

Subpackages

• MEDfl.LearningManager package
  • Submodules
  • MEDfl.LearningManager.client module
    • FlowerClient
      • FlowerClient.cid
      • FlowerClient.local_model
      • FlowerClient.trainloader
      • FlowerClient.valloader
      • FlowerClient.diff_priv
      • FlowerClient.__init__()
      • FlowerClient.context
      • FlowerClient.evaluate()
      • FlowerClient.fit()
      • FlowerClient.get_parameters()
      • FlowerClient.validate()
  • MEDfl.LearningManager.dynamicModal module
    • DynamicModel
      • DynamicModel.create_binary_classifier()
      • DynamicModel.create_convolutional_neural_network()
      • DynamicModel.create_linear_regressor()
      • DynamicModel.create_logistic_regressor()
      • DynamicModel.create_lstm_network()
      • DynamicModel.create_model()
      • DynamicModel.create_multiclass_classifier()
      • DynamicModel.create_recurrent_neural_network()
  • MEDfl.LearningManager.federated_dataset module
    • FederatedDataset
      • FederatedDataset.__init__()
      • FederatedDataset.create()
      • FederatedDataset.update()
  • MEDfl.LearningManager.flpipeline module
    • FLpipeline
      • FLpipeline.name
      • FLpipeline.description
      • FLpipeline.server
      • FLpipeline.auto_test()
      • FLpipeline.create()
      • FLpipeline.delete()
      • FLpipeline.test_by_node()
      • FLpipeline.validate()
    • create_query()
  • MEDfl.LearningManager.model module
    • Model
      • Model.model
      • Model.optimizer
      • Model.criterion
      • Model.__init__()
      • Model.evaluate()
      • Model.get_parameters()
      • Model.load_model()
      • Model.save_model()
      • Model.set_parameters()
      • Model.train()
      • Model.validate()
  • MEDfl.LearningManager.plot module
    • AccuracyLossPlotter
      • AccuracyLossPlotter.results_dict
      • AccuracyLossPlotter.parameters
      • AccuracyLossPlotter.metrics
      • AccuracyLossPlotter.iterations
      • AccuracyLossPlotter.__init__()
      • AccuracyLossPlotter.plot_accuracy_loss()
      • AccuracyLossPlotter.plot_classification_report()
      • AccuracyLossPlotter.plot_confusion_Matrix_by_node()
      • AccuracyLossPlotter.plot_global_confusion_matrix()
    • results_dict
  • MEDfl.LearningManager.server module
    • FlowerServer
      • FlowerServer.global_model
      • FlowerServer.strategy
      • FlowerServer.num_rounds
      • FlowerServer.num_clients
      • FlowerServer.fed_dataset
      • FlowerServer.diff_priv
      • FlowerServer.accuracies
      • FlowerServer.losses
      • FlowerServer.flower_clients
      • FlowerServer.__init__()
      • FlowerServer.client_fn()
      • FlowerServer.evaluate()
      • FlowerServer.run()
      • FlowerServer.validate()
  <<<<<<< HEAD
  • Medfl.LearningManager.strategy module
    • Strategy
      • Strategy.name
      • Strategy.fraction_fit
      • Strategy.fraction_evaluate
      • Strategy.min_fit_clients
      • Strategy.min_evaluate_clients
      • Strategy.min_available_clients
      • Strategy.initial_parameters
      • Strategy.__init__()
      • Strategy.create_strategy()
      • Strategy.get_strategy_by_name()
      • Strategy.optuna_fed_optimization()
      =======
      • MEDfl.LearningManager.strategy module
        • Strategy
          • Strategy.name
          • Strategy.fraction_fit
          • Strategy.fraction_evaluate
          • Strategy.min_fit_clients
          • Strategy.min_evaluate_clients
          • Strategy.min_available_clients
          • Strategy.initial_parameters
          • Strategy.__init__()
          >>>>>>> 58b1e52fd8ab5e97505682e684fd63c00521021e
      • MEDfl.LearningManager.utils module
        • custom_classification_report()
        • empty_db()
        • get_node_confusion_matrix()
        • get_pipeline_confusion_matrix()
        • get_pipeline_from_name()
        • get_pipeline_result()
        • test()
      • Module contents
    • MEDfl.NetManager package
      • Submodules
      • MEDfl.NetManager.dataset module
        • DataSet
          • DataSet.__init__()
          • DataSet.delete_dataset()
          • DataSet.list_alldatasets()
          • DataSet.update_data()
          • DataSet.upload_dataset()
          • DataSet.validate()
      • MEDfl.NetManager.flsetup module
        • FLsetup
          • FLsetup.__init__()
          • FLsetup.create()
          • FLsetup.create_dataloader_from_node()
          • FLsetup.create_federated_dataset()
          • FLsetup.create_nodes_from_master_dataset()
          • FLsetup.delete()
          • FLsetup.get_flDataSet()
          • FLsetup.list_allsetups()
          • FLsetup.read_setup()
          • FLsetup.validate()
      • MEDfl.NetManager.net_helper module
        • get_feddataset_id_from_name()
        • get_flpipeline_from_name()
        • get_flsetupid_from_name()
        • get_netid_from_name()
        • get_nodeid_from_name()
        • is_str()
        • master_table_exists()
        • process_data_after_reading()
        • process_eicu()
      • MEDfl.NetManager.net_manager_queries module
      • MEDfl.NetManager.network module
        • Network
          • Network.name
          • Network.mtable_exists
          • Network.__init__()
          • Network.add_node()
          • Network.create_master_dataset()
          • Network.create_network()
          • Network.delete_network()
          • Network.list_allnetworks()
          • Network.list_allnodes()
          • Network.update_network()
          • Network.use_network()
          • Network.validate()
      • MEDfl.NetManager.node module
        • Node
          • Node.name
          • Node.train
          • Node.test_fraction
          • Node.__init__()
          • Node.assign_dataset()
          • Node.check_dataset_compatibility()
          • Node.create_node()
          • Node.delete_node()
          • Node.get_dataset()
          • Node.list_alldatasets()
          • Node.list_allnodes()
          • Node.unassign_dataset()
          • Node.update_node()
          • Node.upload_dataset()
          • Node.validate()
      • Module contents

Module contents