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)
"""
