def main(_):
hparams = train_lib.HParams(FLAGS.batch_size, FLAGS.patch_size,
FLAGS.train_log_dir, FLAGS.generator_lr,
FLAGS.discriminator_lr,
FLAGS.max_number_of_steps, FLAGS.adam_beta1,
FLAGS.adam_beta2, FLAGS.gen_disc_step_ratio,
FLAGS.tf_master, FLAGS.ps_replicas, FLAGS.task)
train_lib.train(hparams)
def setUp(self):
super(TrainTest, self).setUp()
self.hparams = train_lib.HParams(
batch_size=6,
patch_size=128,
train_log_dir='/tmp/tfgan_logdir/stargan/',
generator_lr=1e-4,
discriminator_lr=1e-4,
max_number_of_steps=1000000,
adam_beta1=0.5,
adam_beta2=0.999,
gen_disc_step_ratio=0.2,
tf_master='',
ps_replicas=0,
task=0)
def setUp(self):
super(TrainTest, self).setUp()
# Force the TF lazy loading to kick in before mocking this out below.
_ = tf.train.get_or_create_global_step()
self.hparams = train_lib.HParams(
batch_size=6,
patch_size=128,
train_log_dir='/tmp/tfgan_logdir/stargan/',
generator_lr=1e-4,
discriminator_lr=1e-4,
max_number_of_steps=1000000,
adam_beta1=0.5,
adam_beta2=0.999,
gen_disc_step_ratio=0.2,
tf_master='',
ps_replicas=0,
task=0)