import argparse

parser = argparse.ArgumentParser()

parser.add_argument('--save', type=str, default='../garage/pems08/2/')

parser.add_argument('--remote', action='store_true', help='the code run on a server')

parser.add_argument('--num-gpu', type=int, default=0, help='the number of the gpu to use')

parser.add_argument('--epochs', type=int, default=200, help='train epochs')

parser.add_argument('--seed', type=int, default=100, help='seed')

parser.add_argument('--batch-size', type=int, default=64, help='batch size')

# parser.add_argument('--lr_decay_steps', type=int, nargs='+',default=[50,105,145], help='lr_decay_steps')

parser.add_argument('--lr_decay_steps', type=int, nargs='+',default=[15,50,105,145], help='lr_decay_steps')

parser.add_argument('--lr_decay_rate', type=float, default=0.13, help='lr_decay_rate')

parser.add_argument('--filename', type=str, default='pems08')

parser.add_argument('--train-ratio', type=float, default=0.6, help='the ratio of training dataset')

parser.add_argument('--valid-ratio', type=float, default=0.2, help='the ratio of validating dataset')

parser.add_argument('--his-length', type=int, default=12, help='the length of history time series of input')

parser.add_argument('--pred-length', type=int, default=12, help='the length of target time series for prediction')

parser.add_argument('--sigma1', type=float, default=0.1, help='sigma for the semantic matrix')

parser.add_argument('--sigma2', type=float, default=10, help='sigma for the spatial matrix')

parser.add_argument('--thres1', type=float, default=0.6, help='the threshold for the semantic matrix')

parser.add_argument('--thres2', type=float, default=0.5, help='the threshold for the spatial matrix')

parser.add_argument('--lr', type=float, default=2e-4, help='learning rate')

parser.add_argument('--log', action='store_true', help='if write log to files')

args = parser.parse_args()