def main(_): pp.pprint(flags.FLAGS.__flags) if not os.path.exists(FLAGS.checkpoint_dir): os.makedirs(FLAGS.checkpoint_dir) if not os.path.exists(FLAGS.sample_dir): os.makedirs(FLAGS.sample_dir) with tf.Session() as sess: if FLAGS.dataset == 'mnist': dcgan = DCGAN(sess, image_size=FLAGS.image_size, batch_size=FLAGS.batch_size, y_dim=10, dataset_name=FLAGS.dataset, is_crop=FLAGS.is_crop, checkpoint_dir=FLAGS.checkpoint_dir) else: dcgan = DCGAN(sess, image_size=FLAGS.image_size, batch_size=FLAGS.batch_size, dataset_name=FLAGS.dataset, is_crop=FLAGS.is_crop, checkpoint_dir=FLAGS.checkpoint_dir) if FLAGS.is_train: dcgan.train(FLAGS) else: if FLAGS.is_single: dcgan.single_test(FLAGS.checkpoint_dir, FLAGS.file_name) elif FLAGS.is_small: dcgan.batch_test2(FLAGS.checkpoint_dir) else: dcgan.batch_test(FLAGS.checkpoint_dir, FLAGS.file_name) # dcgan.load(FLAGS.checkpoint_dir) # dcgan.single_test(FLAGS.checkpoint_dir) # dcgan.batch_test(FLAGS.checkpoint_dir) """