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run_model.py
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29 lines (28 loc) · 1.99 KB
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import argparse
from libcity.pipeline import run_model
from libcity.utils import str2bool, add_general_args
# # Dataset: COVID01010401_SG_CTractFIPS_Hourly_Single_GP SG_CTractFIPS_Hourly_Single_GP
# model_list = ['MultiATGCN', 'AGCRN', 'ASTGCN', 'STGCN', 'MTGNN', 'GWNET', 'GMAN', 'STTN', "GRU", 'LSTM',
# 'RNN', 'Seq2Seq', 'FNN', 'TGCN', 'DCRNN']
model_list = ['MultiATGCN']
if __name__ == '__main__':
for model_name in model_list:
parser = argparse.ArgumentParser()
parser.add_argument('--task', type=str, default='traffic_state_pred', help='the name of task')
parser.add_argument('--model', type=str, default=model_name, help='the name of model')
parser.add_argument('--dataset', type=str, default='201901010601_DC_SG_CTractFIPS_Hourly_Single_GP',
help='the name of dataset')
parser.add_argument('--config_file', type=str, default='config_user', help='the file name of config file')
parser.add_argument('--saved_model', type=str2bool, default=True, help='whether save the trained model')
parser.add_argument('--train', type=str2bool, default=True, help='whether re-train if the model is trained')
parser.add_argument('--exp_id', type=str, default=None, help='id of experiment')
parser.add_argument('--seed', type=int, default=100, help='random seed')
parser.add_argument('--start_dim', type=int, default=0, help='start_dim')
parser.add_argument('--end_dim', type=int, default=1, help='end_dim')
add_general_args(parser)
args, unknown = parser.parse_known_args()
dict_args = vars(args)
other_args = {key: val for key, val in dict_args.items() if key not in
['task', 'model', 'dataset', 'config_file', 'saved_model', 'train'] and val is not None}
run_model(task=args.task, model_name=args.model, dataset_name=args.dataset, config_file=args.config_file,
saved_model=args.saved_model, train=args.train, other_args=other_args)