<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def export_model(model, model_type, export_dir, model_column_fn):
 """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. """

  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)