def METHOD_NAME(path):
    """
    Load the KerasImageClassifierPyfunc model.
    """
    with open(os.path.join(path, "conf.yaml")) as f:
        conf = yaml.safe_load(f)
    keras_model_path = os.path.join(path, "keras_model")
    domain = conf["domain"].split("/")
    image_dims = np.array([int(x) for x in conf["image_dims"].split("/")], dtype=np.int32)
    # NOTE: TensorFlow based models depend on global state (Graph and Session) given by the context.
    # To make sure we score the model in the same session as we loaded it in, we create a new
    # session and a new graph here and store them with the model.
    with tf.Graph().as_default() as g:
        with tf.Session().as_default() as sess:
            keras.backend.set_session(sess)
            keras_model = mlflow.tensorflow.load_model(keras_model_path)
    return KerasImageClassifierPyfunc(g, sess, keras_model, image_dims, domain=domain)