def main(_):
config = tf.ConfigProto()
config.gpu_options.allow_growth = True
with tf.Session(config=config) as sess:
model = UNet(batch_size=args.batch_size)
model.register_session(sess)
model.build_model(is_training=False, inst_norm=args.inst_norm)
model.export_generator(save_dir=args.save_dir, model_dir=args.model_dir)
def main():
# Detect devices
use_cuda = torch.cuda.is_available() # check if GPU exists
device = torch.device("cuda" if use_cuda else "cpu") # use CPU or GPU
model = UNet(device,
input_width=args.image_size,
output_width=args.image_size,
inst_norm=args.inst_norm,
g_norm_type=args.g_norm_type).to(device)
model.export_generator(save_dir=args.save_dir, model_dir=args.model_dir)
