def main():
opt = Config()
if opt.if_real_data:
opt.max_seq_len, opt.vocab_size = text_process('data/' + opt.dataset +
'.txt')
opt.extend_vocab_size = len(load_test_dict(
opt.dataset)[0]) # init classifier vocab_size
inst = SeqGANInstructor(opt)
inst._run()
parser.add_argument('--signal_file', default=cfg.signal_file, type=str)
parser.add_argument('--tips', default=cfg.tips, type=str)
return parser
# MAIN
if __name__ == '__main__':
# Hyper Parameters
parser = argparse.ArgumentParser()
parser = program_config(parser)
opt = parser.parse_args()
if opt.if_real_data:
print("Real data is being used")
opt.max_seq_len, opt.vocab_size = text_process('dataset/' + opt.dataset + '.txt')
cfg.extend_vocab_size = len(load_test_dict(opt.dataset)[0]) # init classifier vocab_size
cfg.init_param(opt)
opt.save_root = cfg.save_root
opt.train_data = cfg.train_data
opt.test_data = cfg.test_data
# ===Dict===
if cfg.if_real_data:
from instructor.real_data.seqgan_instructor import SeqGANInstructor
from instructor.real_data.leakgan_instructor import LeakGANInstructor
from instructor.real_data.maligan_instructor import MaliGANInstructor
from instructor.real_data.jsdgan_instructor import JSDGANInstructor
from instructor.real_data.dpgan_instructor import DPGANInstructor
from instructor.real_data.sa_dpgan_instructor import SADPGANInstructor
from instructor.real_data.relgan_instructor import RelGANInstructor
