def test_any_batch_size(self):
inputs = tf.placeholder(tf.float32, shape=[None, 28, 28, 1])
fdistance = util.mnist_frechet_distance(inputs, inputs)
for batch_size in [4, 16, 30]:
with self.test_session() as sess:
sess.run(fdistance,
feed_dict={inputs: np.zeros([batch_size, 28, 28, 1])})
def test_any_batch_size(self):
inputs = tf.placeholder(tf.float32, shape=[None, 28, 28, 1])
fdistance = util.mnist_frechet_distance(inputs, inputs)
for batch_size in [4, 16, 30]:
with self.test_session() as sess:
sess.run(fdistance,
feed_dict={inputs: np.zeros([batch_size, 28, 28, 1])})
def test_batch_splitting_doesnt_change_value(self):
for num_batches in [1, 2, 4, 8]:
fdistance = util.mnist_frechet_distance(
tf.concat([real_digit()] * 6 + [fake_digit()] * 2, 0),
tf.concat([real_digit()] * 2 + [fake_digit()] * 6, 0),
num_batches=num_batches)
with self.test_session():
self.assertNear(97.8, fdistance.eval(), 2e-1)
def test_batch_splitting_doesnt_change_value(self):
for num_batches in [1, 2, 4, 8]:
fdistance = util.mnist_frechet_distance(
tf.concat([real_digit()] * 6 + [fake_digit()] * 2, 0),
tf.concat([real_digit()] * 2 + [fake_digit()] * 6, 0),
num_batches=num_batches)
with self.test_session():
self.assertNear(97.8, fdistance.eval(), 2e-1)
def test_minibatch_correct(self):
fdistance = util.mnist_frechet_distance(
tf.concat([real_digit(), real_digit(),
fake_digit()], 0),
tf.concat([real_digit(), fake_digit(),
fake_digit()], 0))
with self.test_session():
self.assertNear(43.5, fdistance.eval(), 2e-1)
def test_deterministic(self):
fdistance = util.mnist_frechet_distance(
tf.concat([real_digit()] * 2, 0), tf.concat([fake_digit()] * 2, 0))
with self.test_session():
fdistance1 = fdistance.eval()
fdistance2 = fdistance.eval()
self.assertNear(fdistance1, fdistance2, 2e-1)
with self.test_session():
fdistance3 = fdistance.eval()
self.assertNear(fdistance1, fdistance3, 2e-1)
def test_deterministic(self):
fdistance = util.mnist_frechet_distance(
tf.concat([real_digit()] * 2, 0),
tf.concat([fake_digit()] * 2, 0))
with self.test_session():
fdistance1 = fdistance.eval()
fdistance2 = fdistance.eval()
self.assertNear(fdistance1, fdistance2, 2e-1)
with self.test_session():
fdistance3 = fdistance.eval()
self.assertNear(fdistance1, fdistance3, 2e-1)
def test_minibatch_correct(self):
fdistance = util.mnist_frechet_distance(
tf.concat([real_digit(), real_digit(), fake_digit()], 0),
tf.concat([real_digit(), fake_digit(), fake_digit()], 0))
with self.test_session():
self.assertNear(43.5, fdistance.eval(), 2e-1)
def test_single_example_correct(self):
fdistance = util.mnist_frechet_distance(
tf.concat([real_digit()] * 2, 0),
tf.concat([real_digit()] * 2, 0))
with self.test_session():
self.assertNear(0.0, fdistance.eval(), 2e-1)
def test_single_example_correct(self):
fdistance = util.mnist_frechet_distance(
tf.concat([real_digit()] * 2, 0),
tf.concat([real_digit()] * 2, 0))
with self.test_session():
self.assertNear(0.0, fdistance.eval(), 2e-1)
