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)