code: def conjugate(
      dual_quaternion: type_alias.TensorLike,
      name: str = "dual_quaternion_conjugate",
  ) -> tf.Tensor:
      """Computes the conjugate of a dual quaternion.
  
      Note:
        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.conjugate(quaternion_real),
                  quaternion.conjugate(quaternion_dual),
              ),
              axis=-1,
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import Tuple
  import tensorflow
  from tensorflow_graphics.geometry.transformation import quaternion
  from tensorflow_graphics.math import vector
  from tensorflow_graphics.util import export_api
  from tensorflow_graphics.util import safe_ops
  from tensorflow_graphics.util import shape
  from tensorflow_graphics.util import type_alias
label_desc: Use image node_id 1 for calling a global function with example usage: conjugate(dual_quaternion, name) and returns: tf