code: def make_ragged_densify_layer():
      """Creates a keras layer that densifies a RaggedTensor.
  
      The layer takes a RaggedTensor as input and outputs a dense tensor.
      The dense tensor will have the same rank as the input RaggedTensor, and
      the size of each dimension will equal to the bounding size of the
      corresponding dimension of the input RaggedTensor. 0 will be used to fill
      the gaps.
  
  
      Returns:
        A Keras Layer.
      """
      return tf.keras.layers.Lambda(lambda x: x.to_tensor())
  
file_path: tfx/tfx/examples/ranking/struct2tensor_parsing_utils.py
imports: import itertools
  from typing import Dict, List, Optional, Union
  from struct2tensor import calculate
  from struct2tensor import calculate_options
  from struct2tensor import path
  from struct2tensor import prensor_util
  from struct2tensor.expression_impl import proto
  import tensorflow
  from tfx_bsl.public import tfxio
  from tensorflow_serving.apis import input_pb2
label_desc: Use image node_id 3 for calling a global function with example usage: make_ragged_densify_layer() and returns: tf