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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def export_model(module_spec, class_count, saved_model_dir):
 """Exports model for serving. Args: module_spec: The hub.ModuleSpec for the image module being used. class_count: The number of classes. saved_model_dir: Directory in which to save exported model and variables. """

  # The SavedModel should hold the eval graph.
  sess, in_image, _, _, _, _ = build_eval_session(module_spec, class_count)
  with sess.graph.as_default() as graph:
    tf.saved_model.simple_save(
        sess,
        saved_model_dir,
        inputs={'image': in_image},
        outputs={'prediction': graph.get_tensor_by_name('final_result:0')},
        legacy_init_op=tf.group(tf.tables_initializer(), name='legacy_init_op')
    )