code: def dense_image_warp_annotated(
      image: types.TensorLike, flow: types.TensorLike
  ) -> tf.Tensor:
      """Similar to dense_image_warp but annotated with experimental_implements.
  
      IMPORTANT: This is a temporary function and will be removed after TensorFlow's
      next release.
  
      This annotation make the serialized function detectable by the TFLite MLIR
      converter and allow the converter to convert it to corresponding TFLite op.
  
      However, with the annotation, this function cannot be used with backprop
      under `tf.GradientTape` objects.
      """
      return dense_image_warp(image, flow)
  
file_path: addons/tensorflow_addons/image/dense_image_warp.py
imports: import tensorflow
  from tensorflow_addons.utils import types
  from typing import Optional
label_desc: Use image node_id 6 for calling a global function with example usage: dense_image_warp_annotated(image, flow) and returns: dense_image_warp