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dataset_options.py
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dataset_options.py
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import argparse
def get_dataset_options(dataset_name):
"""Not used datasets"""
"""if dataset_name == 'cascaded_tank':
dataset_parser = argparse.ArgumentParser(description='dynamic system parameter: cascaded tank')
dataset_parser.add_argument('--y_dim', type=int, default=1, help='dimension of y')
dataset_parser.add_argument('--u_dim', type=int, default=1, help='dimension of u')
dataset_parser.add_argument('--seq_len_train', type=int, default=128, help='training sequence length')
dataset_parser.add_argument('--seq_len_test', type=int, default=None, help='test sequence length')
dataset_parser.add_argument('--seq_len_val', type=int, default=128, help='validation sequence length')
dataset_options = dataset_parser.parse_args()
elif dataset_name == 'f16gvt':
dataset_parser = argparse.ArgumentParser(description='dynamic system parameter: f-16')
dataset_parser.add_argument('--y_dim', type=int, default=3, help='dimension of y')
dataset_parser.add_argument('--u_dim', type=int, default=1, help='dimension of u')
dataset_parser.add_argument('--seq_len_train', type=int, default=2048, help='training sequence length')
dataset_parser.add_argument('--seq_len_test', type=int, default=2048, help='test sequence length')
dataset_parser.add_argument('--seq_len_val', type=int, default=2048, help='validation sequence length')
dataset_options = dataset_parser.parse_args()"""
if dataset_name == 'narendra_li':
dataset_parser = argparse.ArgumentParser(description='dynamic system parameter: narendra li')
dataset_parser.add_argument('--y_dim', type=int, default=1, help='dimension of y')
dataset_parser.add_argument('--u_dim', type=int, default=1, help='dimension of u')
dataset_parser.add_argument('--seq_len_train', type=int, default=2000, help='training sequence length')
dataset_parser.add_argument('--seq_len_test', type=int, default=None, help='test sequence length')
dataset_parser.add_argument('--seq_len_val', type=int, default=2000, help='validation sequence length') # 512
dataset_options = dataset_parser.parse_args()
elif dataset_name == 'toy_lgssm':
dataset_parser = argparse.ArgumentParser(description='dynamic system parameter: lgssm')
dataset_parser.add_argument('--y_dim', type=int, default=1, help='dimension of y')
dataset_parser.add_argument('--u_dim', type=int, default=1, help='dimension of u')
dataset_parser.add_argument('--seq_len_train', type=int, default=64, help='training sequence length')
dataset_parser.add_argument('--seq_len_test', type=int, default=None, help='test sequence length')
dataset_parser.add_argument('--seq_len_val', type=int, default=64, help='validation sequence length') # 512
dataset_options = dataset_parser.parse_args()
elif dataset_name == 'wiener_hammerstein':
dataset_parser = argparse.ArgumentParser(description='dynamic system parameter: wiener hammerstein')
dataset_parser.add_argument('--y_dim', type=int, default=1, help='dimension of y')
dataset_parser.add_argument('--u_dim', type=int, default=1, help='dimension of u')
dataset_parser.add_argument('--seq_len_train', type=int, default=2048, help='training sequence length')
dataset_parser.add_argument('--seq_len_test', type=int, default=None, help='test sequence length')
dataset_parser.add_argument('--seq_len_val', type=int, default=2048, help='validation sequence length')
dataset_options = dataset_parser.parse_args()
return dataset_options