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)
