code: def is_normalized(
      quaternion: type_alias.TensorLike,
      atol: type_alias.Float = 1e-3,
      name: str = "quaternion_is_normalized",
  ) -> tf.Tensor:
      """Determines if quaternion is normalized quaternion or not.
  
      Note:
        In the following, A1 to An are optional batch dimensions.
  
      Args:
        quaternion:  A tensor of shape `[A1, ..., An, 4]`, where the last dimension
          represents a quaternion.
        atol: The absolute tolerance parameter.
        name: A name for this op that defaults to "quaternion_is_normalized".
  
      Returns:
        A tensor of type `bool` and shape `[A1, ..., An, 1]`, where False indicates
        that the quaternion is not normalized.
  
      Raises:
        ValueError: If the shape of `quaternion` is not supported.
      """
      with tf.name_scope(name):
          quaternion = tf.convert_to_tensor(value=quaternion)
  
          shape.check_static(
              tensor=quaternion,
              tensor_name="quaternion",
              has_dim_equals=(-1, 4),
          )
  
          norms = tf.norm(tensor=quaternion, axis=-1, keepdims=True)
          return tf.where(
              tf.abs(norms - 1.0) < atol,
              tf.ones_like(norms, dtype=bool),
              tf.zeros_like(norms, dtype=bool),
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import List
  from six.moves import range
  import tensorflow
  from tensorflow_graphics.geometry.transformation import rotation_matrix_3d
  from tensorflow_graphics.math import vector
  from tensorflow_graphics.util import asserts
  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 9 for calling a global function with example usage: is_normalized(quaternion, atol, name) and returns: tf