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import argparse
clr_tasks = {'bbbp': 1, 'hiv': 1, 'bace': 1, 'tox21': 12, 'clintox': 2, 'sider': 27, 'muv': 17, 'toxcast': 617, 'pcba': 128,
'esol': 1, 'freesolv': 1, 'lipophilicity': 1, 'malaria': 1, 'cep': 1, 'qm7': 1, 'qm8': 12, 'qm9': 12}
dataset = "sider"
parser = argparse.ArgumentParser()
parser.add_argument('--path', default='data/down_task/', help='down_task orginal data for input')
parser.add_argument('--feature_dim', default=256, type=int, help='Feature dim for latent vector')
parser.add_argument('--temperature', default=0.1, type=float, help='Temperature used in softmax')
parser.add_argument('--pooling', default="attention", type=str, help='[max, mean, set2set, attention]')
# parser.add_argument('--num_workers', type=int, default=4, help='number of workers for dataset loading')
parser.add_argument('--num_workers', type=int, default=4, help='number of workers for dataset loading')
parser.add_argument('--gnn_type', default="gat", type=str, help='GNN type')
parser.add_argument('--dropout_pre', default=0.0, type=float, help='Dropout rate')
def bace_params():
parser.add_argument('--task', default="bace", type=str, help='Task')
parser.add_argument('--batch_size', default=64, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=50, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.5, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.0005, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=1e-5, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.0, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=False, type=bool, help='normalizer')
args = parser.parse_args()
return args
def bbbp_params():
parser.add_argument('--task', default="bbbp", type=str, help='Task')
parser.add_argument('--batch_size', default=64, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=50, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.0, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.0005, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=1e-7, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.0, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=False, type=bool, help='normalizer')
args = parser.parse_args()
return args
def clintox_params():
parser.add_argument('--task', default="clintox", type=str, help='Task')
parser.add_argument('--batch_size', default=32, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=100, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.0, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.0002, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=1e-7, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.0, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=False, type=bool, help='normalizer')
args = parser.parse_args()
return args
def hiv_params():
parser.add_argument('--task', default="hiv", type=str, help='Task')
parser.add_argument('--batch_size', default=256, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=30, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.1, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.00005, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=1e-7, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.1, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=False, type=bool, help='normalizer')
args = parser.parse_args()
return args
def muv_params():
parser.add_argument('--task', default="muv", type=str, help='Task')
parser.add_argument('--batch_size', default=256, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=20, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.0, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.00001, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=1e-7, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.0, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=False, type=bool, help='normalizer')
args = parser.parse_args()
return args
def sider_params():
parser.add_argument('--task', default="sider", type=str, help='Task')
parser.add_argument('--batch_size', default=32, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=200, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.0, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.0005, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=1e-8, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.0, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=False, type=bool, help='normalizer')
args = parser.parse_args()
return args
def tox21_params():
parser.add_argument('--task', default="tox21", type=str, help='Task')
parser.add_argument('--batch_size', default=32, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=200, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.3, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.0008, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=1e-7, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.0, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=False, type=bool, help='normalizer')
args = parser.parse_args()
return args
def toxcast_params():
parser.add_argument('--task', default="toxcast", type=str, help='Task')
parser.add_argument('--batch_size', default=32, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=150, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.6, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.0004, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=1e-9, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.0, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=False, type=bool, help='normalizer')
args = parser.parse_args()
return args
def pcba_params():
parser.add_argument('--task', default="pcba", type=str, help='Task')
parser.add_argument('--batch_size', default=32, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=60, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.1, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.0008, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=0, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.0, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=False, type=bool, help='normalizer')
args = parser.parse_args()
return args
def esol_params():
parser.add_argument('--task', default="esol", type=str, help='Task')
parser.add_argument('--batch_size', default=64, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=200, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.0, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.0005, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=1e-6, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.0, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=True, type=bool, help='normalizer')
args = parser.parse_args()
return args
def freesolv_params():
parser.add_argument('--task', default="freesolv", type=str, help='Task')
parser.add_argument('--batch_size', default=128, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=100, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.2, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.0008, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=1e-7, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.0, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=True, type=bool, help='normalizer')
args = parser.parse_args()
return args
def lipophilicity_params():
parser.add_argument('--task', default="lipophilicity", type=str, help='Task')
parser.add_argument('--batch_size', default=32, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=100, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.0, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.0005, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=0, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.0, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=True, type=bool, help='normalizer')
args = parser.parse_args()
return args
def malaria_params():
parser.add_argument('--task', default="malaria", type=str, help='Task')
parser.add_argument('--batch_size', default=256, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=30, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.1, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.0005, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=1e-7, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.1, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=True, type=bool, help='normalizer')
args = parser.parse_args()
return args
def cep_params():
parser.add_argument('--task', default="cep", type=str, help='Task')
parser.add_argument('--batch_size', default=256, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=50, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.1, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.0001, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=1e-7, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.1, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=True, type=bool, help='normalizer')
args = parser.parse_args()
return args
def qm7_params():
parser.add_argument('--task', default="qm7", type=str, help='Task')
parser.add_argument('--batch_size', default=64, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=100, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.1, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.0005, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=1e-7, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.0, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=True, type=bool, help='normalizer')
args = parser.parse_args()
return args
def qm8_params():
parser.add_argument('--task', default="qm8", type=str, help='Task')
parser.add_argument('--batch_size', default=32, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=40, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.0, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.001, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=1e-7, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.0, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=True, type=bool, help='normalizer')
args = parser.parse_args()
return args
def qm9_params():
parser.add_argument('--task', default="qm9", type=str, help='Task')
parser.add_argument('--batch_size', default=32, type=int, help='Number of images in each mini-batch')
parser.add_argument('--epochs', default=50, type=int, help='Number of sweeps over the dataset to train')
parser.add_argument('--dropout_gnn', default=0.0, type=float, help='Dropout rate')
parser.add_argument('--lr', default=0.0005, type=float, help='Learning rate')
parser.add_argument('--weight_decay', default=1e-7, type=float, help='weight_decay')
parser.add_argument('--warming_rate', default=0.0, type=float, help='Warming rate')
parser.add_argument('--normalizer', default=True, type=bool, help='normalizer')
args = parser.parse_args()
return args
def set_params():
if dataset == "bace":
args = bace_params()
elif dataset == "bbbp":
args = bbbp_params()
elif dataset == "clintox":
args = clintox_params()
elif dataset == "hiv":
args = hiv_params()
elif dataset == "muv":
args = muv_params()
elif dataset == "sider":
args = sider_params()
elif dataset == "tox21":
args = tox21_params()
elif dataset == "toxcast":
args = toxcast_params()
elif dataset == "pcba":
args = pcba_params()
elif dataset == "esol":
args = esol_params()
elif dataset == "freesolv":
args = freesolv_params()
elif dataset == "lipophilicity":
args = lipophilicity_params()
elif dataset == "malaria":
args = malaria_params()
elif dataset == "cep":
args = cep_params()
elif dataset == "qm7":
args = qm7_params()
elif dataset == "qm8":
args = qm8_params()
elif dataset == "qm9":
args = qm9_params()
return args