From 47566c65cddb8fa2d1103268cf82f45c02e700e9 Mon Sep 17 00:00:00 2001 From: Turningl <60030314+Turningl@users.noreply.github.com> Date: Tue, 3 Dec 2024 17:49:00 +0800 Subject: [PATCH] Update README.md --- README.md | 74 +++++++++++++++++++++++++++---------------------------- 1 file changed, 37 insertions(+), 37 deletions(-) diff --git a/README.md b/README.md index 2af85b8..9b3645b 100644 --- a/README.md +++ b/README.md @@ -55,17 +55,17 @@ All parameters of dataloader: usage: dataloader.py [--root] [--dataset] [--split] [--seed] [--device] optional arguments: - --root root directory for differernt molecular discovery databases: + --root --root directory for differernt molecular discovery databases: MoleculeNet, DrugBank, BIOSNAP, LITPCBA, CoCrystal - --dataset In different root directory, choose dataset of different databases + --dataset --In different root directory, choose dataset of different databases - --split split type for different root and dataset: + --split --split type for different root and dataset: smi, smi1, smi2 - --seed fixed data initialization and training seeds + --seed --fixed data initialization and training seeds - --device cuda or cpu + --device --cuda or cpu ``` ## Usage @@ -78,76 +78,76 @@ usage: main.py [--alg] [--root] [--dataset] [--node_size] [--bond_size] [--hidde [--weight_decay] [--eps] [constant] [--delta] [--dp] [--batch_size] [--device] [--save_dir] [--beta1] [--beta2] [--local_round] [--proj_dims] [--lanczos_iter] [--global_round] [--comm_optimization] [--lr] [--clip] optional arguments: - --alg federated learning algorithm: + --alg --federated learning algorithm: fedavg, fedprox, fedsgd, fedlg, fedadam, fedchem - --root root directory for differernt molecular discovery databases: + --root --root directory for differernt molecular discovery databases: MoleculeNet, DrugBank, BIOSNAP, LITPCBA, CoCrystal - --dataset In different root directory, choose dataset of different databases + --dataset --In different root directory, choose dataset of different databases - --node_size molecular node size + --node_size --molecular node size - --bond_size molecular bond size + --bond_size --molecular bond size --hidden_size hidden size - --extend_dim extend dim for neural network + --extend_dim --extend dim for neural network - --output_size output size + --output_size --output size - --model graph neural network: + --model --graph neural network: MPNN, GCN, GAT - --split split type for different root and dataset: + --split --split type for different root and dataset: smi, smi1, smi2 - --drooput dropout rate + --drooput --dropout rate - --message steps message step for graph neural network + --message steps --message step for graph neural network - --num_clients clients number, here we set the max clients number is up to 4 + --num_clients --clients number, here we set the max clients number is up to 4 - --alpha alpha for molecule dirichlet distribution + --alpha --alpha for molecule dirichlet distribution - --null_value null value + --null_value --null value - --seed fixed data initialization and training seed + --seed --fixed data initialization and training seed - --weight_decay weight decay for optimizer + --weight_decay --weight decay for optimizer - --eps epsilons distribution + --eps --epsilons distribution - --constant constant for local differently privacy + --constant --constant for local differently privacy - --delta differential privacy parameter + --delta --differential privacy parameter - --dp if True, use differential privacy + --dp --if True, use differential privacy - --batch_size batch size of the model training: + --batch_size --batch size of the model training: 32, 64 or 128 - --device cuda or cpu + --device --cuda or cpu - --save_dir results save directory, the model test results is saved to ./results/ + --save_dir --results save directory, the model test results is saved to ./results/ - --beta1 beta1 for Adam optimizer + --beta1 --beta1 for Adam optimizer - --beta2 beta2 for Adam optimizer + --beta2 --beta2 for Adam optimizer - --local_round local model training round + --local_round --local model training round - --proj_dims project dim of lanczos algorithm + --proj_dims --project dim of lanczos algorithm - --lanczos_iter the iterations of lanczos + --lanczos_iter --the iterations of lanczos - --global_round global model training round + --global_round --global model training round - --comm_optimization using Bayesian Optimization or not + --comm_optimization --using Bayesian Optimization or not - --lr the learning rate of graph model + --lr --the learning rate of graph model - --clip clip value for local differently privacy + --clip --clip value for local differently privacy ``` ## Bayesian optimization