code: def _preprocessing_fn_with_two_phases(inputs):
      x = inputs["x"]
      x_mean = tft.mean(x, name="x")
      x_square_deviations = tf.square(x - x_mean)
      x_var = tft.mean(x_square_deviations, name="x_square_deviations")
      x_normalized = (x - x_mean) / tf.sqrt(x_var)
      return {"x_normalized": x_normalized}
  
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 4 for calling a global function with example usage: _preprocessing_fn_with_two_phases(inputs) and returns: dict