code: def _preprocessing_fn_with_control_dependency(inputs):
      with tf.init_scope():
          initializer = tf.lookup.KeyValueTensorInitializer(
              ["foo", "bar"], [0, 1]
          )
          table = tf.lookup.StaticHashTable(
              initializer, default_value=-1
          )
      # The table created here will add an automatic control dependency.
      s_int = table.lookup(inputs["s"]) + 1
  
      # Perform some TF Ops to ensure x is part of the graph of dependencies for the
      # outputs.
      x_abs = tf.math.abs(inputs["x"])
      y_centered = tf.sparse.add(
          tf.cast(inputs["y"], tf.float32), -analyzers.mean(inputs["y"])
      )
      return {"s_int": s_int, "x_abs": x_abs, "y_centered": y_centered}
  
file_path: transform/tensorflow_transform/inspect_preprocessing_fn_test.py
imports: import tensorflow
  from tensorflow_transform import analyzers
  from tensorflow_transform import inspect_preprocessing_fn
  from tensorflow_transform import mappers
  from tensorflow_transform import test_case
label_desc: Use image node_id 8 for calling a global function with example usage: _preprocessing_fn_with_control_dependency(inputs) and returns: dict