def test_batch_splitting_doesnt_change_value(self):
for num_batches in [1, 2, 4, 8]:
mscore = util.mnist_score(
tf.concat([real_digit()] * 4 + [fake_digit()] * 4, 0),
num_batches=num_batches)
with self.test_session():
self.assertNear(1.649209, mscore.eval(), 1e-6)
def test_batch_splitting_doesnt_change_value(self):
for num_batches in [1, 2, 4, 8]:
mscore = util.mnist_score(
tf.concat([real_digit()] * 4 + [fake_digit()] * 4, 0),
num_batches=num_batches)
with self.test_session():
self.assertNear(1.649209, mscore.eval(), 1e-6)
def test_any_batch_size(self):
inputs = tf.placeholder(tf.float32, shape=[None, 28, 28, 1])
mscore = util.mnist_score(inputs)
for batch_size in [4, 16, 30]:
with self.test_session() as sess:
sess.run(mscore,
feed_dict={inputs: np.zeros([batch_size, 28, 28, 1])})
def test_deterministic(self):
m_score = util.mnist_score(real_digit())
with self.test_session():
m_score1 = m_score.eval()
m_score2 = m_score.eval()
self.assertEqual(m_score1, m_score2)
with self.test_session():
m_score3 = m_score.eval()
self.assertEqual(m_score1, m_score3)
def test_deterministic(self):
m_score = util.mnist_score(real_digit())
with self.test_session():
m_score1 = m_score.eval()
m_score2 = m_score.eval()
self.assertEqual(m_score1, m_score2)
with self.test_session():
m_score3 = m_score.eval()
self.assertEqual(m_score1, m_score3)
def test_minibatch_correct(self):
mscore = util.mnist_score(
tf.concat([real_digit(), real_digit(), fake_digit()], 0))
with self.test_session():
self.assertNear(1.612828, mscore.eval(), 1e-6)
def test_single_example_correct(self):
real_score = util.mnist_score(real_digit())
fake_score = util.mnist_score(fake_digit())
with self.test_session():
self.assertNear(1.0, real_score.eval(), 1e-6)
self.assertNear(1.0, fake_score.eval(), 1e-6)
def test_any_batch_size(self):
inputs = tf.placeholder(tf.float32, shape=[None, 28, 28, 1])
mscore = util.mnist_score(inputs)
for batch_size in [4, 16, 30]:
with self.test_session() as sess:
sess.run(mscore, feed_dict={inputs: np.zeros([batch_size, 28, 28, 1])})
def test_minibatch_correct(self):
mscore = util.mnist_score(
tf.concat([real_digit(), real_digit(), fake_digit()], 0))
with self.test_session():
self.assertNear(1.612828, mscore.eval(), 1e-6)
def test_single_example_correct(self):
real_score = util.mnist_score(real_digit())
fake_score = util.mnist_score(fake_digit())
with self.test_session():
self.assertNear(1.0, real_score.eval(), 1e-6)
self.assertNear(1.0, fake_score.eval(), 1e-6)
