def test_bad_norm_raise_error(self):
reg_vals = np.array([1, 2, 3, 4, 5])
with self.assertRaisesRegex(ValueError,
'(?i)Unrecognized.*bad_norm_name'):
_ = utils.apply_regularization_loss('bad_norm_name', reg_vals)
def test_lpnorm_2_equal_to_l2norm(self):
reg_vals = np.array([1, 2, 3, 4, 5])
reg_loss_l2 = utils.apply_regularization_loss('l2_norm', reg_vals)
reg_loss_lp = utils.apply_regularization_loss('lp_norm', reg_vals, 2)
self.assertEqual(reg_loss_l2, reg_loss_lp)
def test_apply_lpnorm_5(self):
reg_vals = np.array([1, 2, 3, 4, 5])
reg_loss = utils.apply_regularization_loss('lp_norm', reg_vals, 5)
self.assertAlmostEqual(reg_loss, 5.36022, delta=1e-5)
def test_lpnorm_1_equal_to_l1norm(self):
reg_vals = np.array([1, 2, 3, 4, 5])
reg_loss_l1 = utils.apply_regularization_loss('l1_norm', reg_vals)
reg_loss_lp = utils.apply_regularization_loss('lp_norm', reg_vals, 1)
self.assertEqual(reg_loss_l1, reg_loss_lp)
def test_apply_l2norm(self):
reg_vals = np.array([1, 2, 3, 4, 5])
reg_loss = utils.apply_regularization_loss('l2_norm', reg_vals)
self.assertEqual(reg_loss, np.sqrt(55))