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def main():
args = _parse_args()
if args.tsv:
data, discrete_columns = read_tsv(args.data, args.metadata)
else:
data, discrete_columns = read_csv(
args.data, args.metadata, args.header, args.discrete)
gen_dims = [int(x) for x in args.gen_dims.split(',')]
dis_dims = [int(x) for x in args.dis_dims.split(',')]
model = CTGANSynthesizer(
z_dim=args.z_dim, gen_dims=gen_dims, dis_dims=dis_dims,
gen_lr=args.gen_lr, gen_decay=args.gen_decay,
dis_lr=args.dis_lr, dis_decay=args.dis_decay,
batch_size=args.bs)
model.fit(data, discrete_columns, args.epochs)
num_samples = args.num_samples or len(data)
sampled = model.sample(num_samples)
if args.tsv:
write_tsv(sampled, args.metadata, args.output)