code: def get_wit_knowledge():
      """Concat title passage and document together to form knowledge."""
  
      def get_wit_knowledge_fn(data):
          """Prepare Knowledge by concating hierarchy, passage and first-paragraph."""
  
          knowledges = [
              data["hierarchical_section_title"],
              data["context_section_description"],
              data["context_page_description"],
          ]
          data["knowledge"] = tf.strings.join(
              knowledges, separator=" <extra_id_99> "
          )
  
          caption = data["caption_reference_description_canonicalized"]
          if tf.strings.length(caption) < 1:
              caption = data[
                  "caption_alt_text_description_canonicalized"
              ]
          if tf.strings.length(caption) < 1:
              caption = tf.strings.regex_replace(
                  data["caption_attribution_description_canonicalized"],
                  "^english ",
                  "",
              )
          data["caption"] = caption
          return data
  
      return get_wit_knowledge_fn
  
imports: import functools
  from typing import Optional
  from absl import logging
  from flax import jax_utils
  import jax
  import jax.numpy
  import ml_collections
  import numpy
  from scenic.dataset_lib import dataset_utils
  from scenic.dataset_lib import datasets
  from scenic.dataset_lib.big_transfer import builder
  from scenic.dataset_lib.big_transfer import registry
  from scenic.dataset_lib import web_image_text_dataset
  from scenic.projects.knowledge_visual_language.data import data_utils
  import tensorflow
label_desc: Use image node_id 1 for calling a global function with example usage: get_wit_knowledge() and returns: get_wit_knowledge_fn, data