def test_raw_spectral_norm(self):
with tf.Graph().as_default():
ones_weight = 4 * tf.eye(8, 8)
sigma = spectral_normalization.spectral_norm(ones_weight)['sigma']
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
_, sigma_v = sess.run([ones_weight, sigma])
self.assertLess(abs(4.0 - sigma_v), _ACCEPTABLE_ERROR)
def test_spectral_norm_creates_variables(self):
with tf.Graph().as_default():
ones_weight = 4 * tf.eye(8, 8)
pre_spec_norm_vars = tf.global_variables()
_ = spectral_normalization.spectral_norm(ones_weight)
post_spec_norm_vars = tf.global_variables()
self.assertEmpty(pre_spec_norm_vars)
self.assertLen(post_spec_norm_vars, 1)
self.assertEqual(post_spec_norm_vars[0].name.split('/')[-1],
'u0:0')