code: def _preprocessing_fn_with_table(inputs):
      x = inputs["x"]
      x_vocab = tft.vocabulary(x, name="x")
      initializer = tf.lookup.TextFileInitializer(
          x_vocab,
          key_dtype=tf.string,
          key_index=tf.lookup.TextFileIndex.WHOLE_LINE,
          value_dtype=tf.int64,
          value_index=tf.lookup.TextFileIndex.LINE_NUMBER,
      )
      table = tf.lookup.StaticHashTable(initializer, default_value=-1)
      x_integerized = table.lookup(x)
      return {"x_integerized": x_integerized}
  
imports: import os
  import tensorflow
  import tensorflow_transform
  from tensorflow_transform import analyzer_nodes
  from tensorflow_transform import impl_helper
  from tensorflow_transform import nodes
  from tensorflow_transform import tf2_utils
  from tensorflow_transform.beam import analysis_graph_builder
  from tensorflow_transform.beam import analyzer_cache
  from tensorflow_transform.beam import tft_unit
  from tfx_bsl.types import tfx_namedtuple
label_desc: Use image node_id 3 for calling a global function with example usage: _preprocessing_fn_with_table(inputs) and returns: dict