docs: def export_fun(args):
    """Define/export a single-node TF graph for inferencing"""
    # Input placeholder for inferencing
    x = tf.placeholder(tf.float32, [None, IMAGE_PIXELS * IMAGE_PIXELS], name="x")
  
    # Variables of the hidden layer
    hid_w = tf.Variable(tf.truncated_normal([IMAGE_PIXELS * IMAGE_PIXELS, hidden_units],
                        stddev=1.0 / IMAGE_PIXELS), name="hid_w")
    hid_b = tf.Variable(tf.zeros([hidden_units]), name="hid_b")
    tf.summary.histogram("hidden_weights", hid_w)
  
    # Variables of the softmax layer
    sm_w = tf.Variable(tf.truncated_normal([hidden_units, 10],
                       stddev=1.0 / math.sqrt(hidden_units)), name="sm_w")
    sm_b = tf.Variable(tf.zeros([10]), name="sm_b")
  
    hid_lin = tf.nn.xw_plus_b(x, hid_w, hid_b)
    hid = tf.nn.relu(hid_lin)
    y = tf.nn.softmax(tf.nn.xw_plus_b(hid, sm_w, sm_b))
    prediction = tf.argmax(y, 1, name="prediction")
  
    saver = tf.train.Saver()
  
    with tf.Session() as sess:
      # load graph from a checkpoint
      logging.info("model path: {}".format(args.model_dir))
      ckpt = tf.train.get_checkpoint_state(args.model_dir)
      logging.info("ckpt: {}".format(ckpt))
      assert ckpt and ckpt.model_checkpoint_path, "Invalid model checkpoint path: {}".format(args.model_dir)
      saver.restore(sess, ckpt.model_checkpoint_path)
  
      logging.info("Exporting saved_model to: {}".format(args.export_dir))
      # exported signatures defined in code
      signatures = {
        tf.saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY: {
          'inputs': {'image': x},
          'outputs': {'prediction': prediction},
          'method_name': tf.saved_model.signature_constants.PREDICT_METHOD_NAME
        },
        'featurize': {
          'inputs': {'image': x},
          'outputs': {'features': hid},
          'method_name': 'featurize'
        }
      }
      TFNode.export_saved_model(sess,
                                args.export_dir,
                                tf.saved_model.tag_constants.SERVING,
                                signatures)
      logging.info("Exported saved_model")