def setUp(self):
super(TrainTest, self).setUp()
self.hparams = train_lib.HParams(batch_size=BATCH_SIZE,
train_log_dir=self.get_temp_dir(),
max_number_of_steps=1,
gan_type='unconditional',
grid_size=1,
noise_dims=64)
def setUp(self):
super(TrainTest, self).setUp()
self.hparams = train_lib.HParams(
batch_size=32,
train_log_dir='/tmp/tfgan_logdir/mnist',
max_number_of_steps=20000,
gan_type='unconditional',
grid_size=5,
noise_dims=64)
def main(_):
hparams = train_lib.HParams(FLAGS.batch_size, FLAGS.train_log_dir,
FLAGS.max_number_of_steps, FLAGS.gan_type,
FLAGS.grid_size, FLAGS.noise_dims)
train_lib.train(hparams)