code: def export_model(model, model_type, export_dir, model_column_fn):
    
    wide_columns, deep_columns = model_column_fn()
    if model_type == 'wide':
      columns = wide_columns
    elif model_type == 'deep':
      columns = deep_columns
    else:
      columns = wide_columns + deep_columns
    feature_spec = tf.feature_column.make_parse_example_spec(columns)
    example_input_fn = (
        tf.estimator.export.build_parsing_serving_input_receiver_fn(feature_spec))
    model.export_savedmodel(export_dir, example_input_fn,
                            strip_default_attrs=True)
docs: Export to SavedModel format.
  
    Args:
      model: Estimator object
      model_type: string indicating model type. "wide", "deep" or "wide_deep"
      export_dir: directory to export the model.
      model_column_fn: Function to generate model feature columns.