Adds the conjugate_dual function to the dual_quaternion module.

PiperOrigin-RevId: 412914740

Author: G4G

tensorflow_graphics/geometry/transformation/dual_quaternion.py

@@ -393,5 +393,41 @@ def from_axis_angle_translation(axis: type_alias.TensorLike,
     return tf.concat((quaternion_rotation, dual_quaternion_dual_part), axis=-1)
 
 
+def conjugate_dual(
+    dual_quaternion: type_alias.TensorLike,
+    name: str = "dual_quaternion_conjugate") -> tf.Tensor:
+  """Computes the conjugate (of dual numbers) in a dual quaternion.
+
+  Note:
+    For a dual quaternion q = q_0 + epsilon q_e, the dual conjugate is defined
+    as q = q_0 - epsilon q_e.
+    In the following, A1 to An are optional batch dimensions.
+
+  Args:
+    dual_quaternion: A TensorLike of shape `[A1, ..., An, 8]`, where the last
+      dimension represents a normalized dual quaternion.
+    name: A name for this op that defaults to "dual_quaternion_conjugate".
+
+  Returns:
+    A tensor of shape `[A1, ..., An, 8]`, where the last dimension represents
+    a normalized dual quaternion.
+
+  Raises:
+    ValueError: If the shape of `dual_quaternion` is not supported.
+  """
+  with tf.name_scope(name):
+    dual_quaternion = tf.convert_to_tensor(value=dual_quaternion)
+
+    shape.check_static(
+        tensor=dual_quaternion,
+        tensor_name="dual_quaternion",
+        has_dim_equals=(-1, 8))
+
+    quaternion_real, quaternion_dual = tf.split(
+        dual_quaternion, (4, 4), axis=-1)
+
+    return tf.concat((quaternion_real, -quaternion_dual), axis=-1)
+
+
 # API contains all public functions and classes.
 __all__ = export_api.get_functions_and_classes()

tensorflow_graphics/geometry/transformation/tests/dual_quaternion_test.py

@@ -330,6 +330,43 @@ def test_from_axis_angle_translation_random(self):
     self.assertAllClose(rotation_gt, rotation)
     self.assertAllClose(translation_gt, translation)
 
+  @parameterized.parameters(
+      ((8,),),
+      ((None, 8),),
+  )
+  def test_conjugate_dual_exception_not_raised(self, *shape):
+    self.assert_exception_is_not_raised(dual_quaternion.conjugate_dual, shape)
+
+  @parameterized.parameters(
+      ("must have exactly 8 dimensions", (3,)),)
+  def test_conjugate_dual_exception_raised(self, error_msg, *shape):
+    self.assert_exception_is_raised(
+        dual_quaternion.conjugate_dual,
+        error_msg, shape)
+
+  @flagsaver.flagsaver(tfg_add_asserts_to_graph=False)
+  def test_conjugate_dual_jacobian_preset(self):
+    x_init = test_helpers.generate_preset_test_dual_quaternions()
+    self.assert_jacobian_is_correct_fn(dual_quaternion.conjugate_dual, [x_init])
+
+  @flagsaver.flagsaver(tfg_add_asserts_to_graph=False)
+  def test_conjugate_dual_jacobian_random(self):
+    x_init = test_helpers.generate_random_test_dual_quaternions()
+    self.assert_jacobian_is_correct_fn(dual_quaternion.conjugate_dual, [x_init])
+
+  @flagsaver.flagsaver(tfg_add_asserts_to_graph=False)
+  def test_conjugate_dual_preset(self):
+    x_init = test_helpers.generate_preset_test_dual_quaternions()
+    x = tf.convert_to_tensor(value=x_init)
+    y = tf.convert_to_tensor(value=x_init)
+
+    x = dual_quaternion.conjugate_dual(x)
+    x_real, x_dual = tf.split(x, (4, 4), axis=-1)
+    y_real, y_dual = tf.split(y, (4, 4), axis=-1)
+
+    self.assertAllEqual(x_real, y_real)
+    self.assertAllEqual(x_dual, -y_dual)
+
 
 if __name__ == "__main__":
   test_case.main()