def test_actnorm(self):
"""Test that actnorm provides activations with zero channel-mean."""
with tf.Graph().as_default():
x_t = tf.random_normal((16, 32, 32, 3), mean=50.0, stddev=2.0)
x_act = glow_ops.actnorm("actnorm", x_t, init=True)
with tf.Session() as session:
x_act_np, _ = session.run(x_act)
channel_mean = np.mean(x_act_np, axis=(0, 1, 2))
channel_var = np.var(x_act_np, axis=(0, 1, 2))
self.assertTrue(np.allclose(channel_mean, 0.0, atol=1e-3))
self.assertTrue(np.allclose(channel_var, 1.0, atol=1e-3))
def test_actnorm(self):
"""Test that actnorm provides activations with zero channel-mean."""
with tf.Graph().as_default():
x_t = tf.random_normal((16, 32, 32, 3), mean=50.0, stddev=2.0)
x_act = glow_ops.actnorm("actnorm", x_t, init=True)
with tf.Session() as session:
x_act_np, _ = session.run(x_act)
channel_mean = np.mean(x_act_np, axis=(0, 1, 2))
channel_var = np.var(x_act_np, axis=(0, 1, 2))
self.assertTrue(np.allclose(channel_mean, 0.0, atol=1e-3))
self.assertTrue(np.allclose(channel_var, 1.0, atol=1e-3))
