code: def _preprocessing_fn(inputs):
      """Preprocess input columns into transformed columns."""
      x = inputs["x"]
      y = inputs["y"]
      s = inputs["s"]
      x_centered = x - tft.mean(x)
      y_normalized = tft.scale_to_0_1(y)
      s_integerized = tft.compute_and_apply_vocabulary(s)
      x_centered_times_y_normalized = x_centered * y_normalized
      return {
          "x_centered": x_centered,
          "y_normalized": y_normalized,
          "x_centered_times_y_normalized": x_centered_times_y_normalized,
          "s_integerized": s_integerized,
      }
  
imports: import pprint
  import tempfile
  import tensorflow
  import tensorflow_transform
  import tensorflow_transform.beam
label_desc: Use image node_id 1 for calling a global function with example usage: _preprocessing_fn(inputs) and returns: dict