def test_inverse_jacobian_random(self): """Test the Jacobian of the inverse function.""" x_axis_init, x_angle_init = test_helpers.generate_random_test_axis_angle( ) self.assert_jacobian_is_correct_fn( lambda x: axis_angle.inverse(x, x_angle_init)[0], [x_axis_init]) self.assert_jacobian_is_correct_fn( lambda x: axis_angle.inverse(x_axis_init, x)[1], [x_angle_init])
def test_inverse_jacobian_preset(self): """Test the Jacobian of the inverse function.""" x_axis_init, x_angle_init = test_helpers.generate_preset_test_axis_angle() if tf.executing_eagerly(): # Because axis is returned as is, gradient calculation fails in graph mode # but not in eager mode. This is a side effect of having a graph rather # than a problem of the function. with self.subTest("axis"): self.assert_jacobian_is_correct_fn( lambda x: axis_angle.inverse(x, x_angle_init)[0], [x_axis_init]) with self.subTest("angle"): self.assert_jacobian_is_correct_fn( lambda x: axis_angle.inverse(x_axis_init, x)[1], [x_angle_init])
def test_inverse_random(self): """Tests axis-angle inversion.""" random_axis, random_angle = test_helpers.generate_random_test_axis_angle() inverse_axis, inverse_angle = axis_angle.inverse(random_axis, random_angle) self.assertAllClose(inverse_axis, random_axis, rtol=1e-3) self.assertAllClose(inverse_angle, -random_angle, rtol=1e-3)
def test_inverse_normalized_random(self): """Tests that axis-angle inversion return a normalized axis-angle.""" random_axis, random_angle = test_helpers.generate_random_test_axis_angle() inverse_axis, inverse_angle = axis_angle.inverse(random_axis, random_angle) self.assertAllEqual( axis_angle.is_normalized(inverse_axis, inverse_angle), np.ones(random_angle.shape))
def test_inverse_jacobian_random(self): """Test the Jacobian of the inverse function.""" x_axis_init, x_angle_init = test_helpers.generate_random_test_axis_angle( ) x_axis = tf.convert_to_tensor(value=x_axis_init) x_angle = tf.convert_to_tensor(value=x_angle_init) y_axis, y_angle = axis_angle.inverse(x_axis, x_angle) self.assert_jacobian_is_correct(x_axis, x_axis_init, y_axis) self.assert_jacobian_is_correct(x_angle, x_angle_init, y_angle)