code: def reflect(
      vector: TensorLike,
      normal: TensorLike,
      axis: int = -1,
      name: str = "vector_reflect",
  ) -> TensorLike:
      r"""Computes the reflection direction for an incident vector.
  
      For an incident vector \\(\mathbf{v}\\) and normal $$\mathbf{n}$$ this
      function computes the reflected vector as
      \\(\mathbf{r} = \mathbf{v} - 2(\mathbf{n}^T\mathbf{v})\mathbf{n}\\).
  
      Note:
        In the following, A1 to An are optional batch dimensions, which should be
        broadcast compatible.
  
      Args:
        vector: A tensor of shape `[A1, ..., Ai, ..., An]`, where the dimension i =
          axis represents a vector.
        normal: A tensor of shape `[A1, ..., Ai, ..., An]`, where the dimension i =
          axis represents a normal around which the vector needs to be reflected.
          The normal vector needs to be normalized.
        axis: The dimension along which to compute the reflection.
        name: A name for this op which defaults to "vector_reflect".
  
      Returns:
        A tensor of shape `[A1, ..., Ai, ..., An]`, where the dimension i = axis
        represents a reflected vector.
      """
      with tf.name_scope(name):
          vector = tf.convert_to_tensor(value=vector)
          normal = tf.convert_to_tensor(value=normal)
  
          shape.compare_dimensions(
              tensors=(vector, normal),
              axes=axis,
              tensor_names=("vector", "normal"),
          )
          shape.compare_batch_dimensions(
              tensors=(vector, normal),
              last_axes=-1,
              broadcast_compatible=True,
          )
          normal = asserts.assert_normalized(normal, axis=axis)
  
          dot_product = dot(vector, normal, axis=axis)
          return vector - 2.0 * dot_product * normal
  
file_path: graphics/tensorflow_graphics/math/vector.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tensorflow_graphics.util import asserts
  from tensorflow_graphics.util import export_api
  from tensorflow_graphics.util import shape
  from tensorflow_graphics.util.type_alias import TensorLike
label_desc: Use image node_id 3 for calling a global function with example usage: reflect(vector, normal, axis, name) and returns: unknown