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)