def test_nets(self):
with self.test_session() as sess:
ae_shape = [10, 20, 30, 2]
ae = AutoEncoder(ae_shape, sess)
input_pl = tf.placeholder(tf.float32, shape=(100, 10))
with self.assertRaises(AssertionError):
ae.pretrain_net(input_pl, 0)
with self.assertRaises(AssertionError):
ae.pretrain_net(input_pl, 3)
net1 = ae.pretrain_net(input_pl, 1)
net2 = ae.pretrain_net(input_pl, 2)
self.assertEqual(net1.get_shape().dims[1].value, 10)
self.assertEqual(net2.get_shape().dims[1].value, 20)
net1_target = ae.pretrain_net(input_pl, 1, is_target=True)
self.assertEqual(net1_target.get_shape().dims[1].value, 10)
net2_target = ae.pretrain_net(input_pl, 2, is_target=True)
self.assertEqual(net2_target.get_shape().dims[1].value, 20)
sup_net = ae.supervised_net(input_pl)
self.assertEqual(sup_net.get_shape().dims[1].value, 2)
def test_nets(self):
with self.test_session() as sess:
ae_shape = [10, 20, 30, 2]
ae = AutoEncoder(ae_shape, sess)
input_pl = tf.placeholder(tf.float32, shape=(100, 10))
with self.assertRaises(AssertionError):
ae.pretrain_net(input_pl, 0)
with self.assertRaises(AssertionError):
ae.pretrain_net(input_pl, 3)
net1 = ae.pretrain_net(input_pl, 1)
net2 = ae.pretrain_net(input_pl, 2)
self.assertEqual(net1.get_shape().dims[1].value, 10)
self.assertEqual(net2.get_shape().dims[1].value, 20)
net1_target = ae.pretrain_net(input_pl, 1, is_target=True)
self.assertEqual(net1_target.get_shape().dims[1].value, 10)
net2_target = ae.pretrain_net(input_pl, 2, is_target=True)
self.assertEqual(net2_target.get_shape().dims[1].value, 20)
sup_net = ae.supervised_net(input_pl)
self.assertEqual(sup_net.get_shape().dims[1].value, 2)
