def as_keras_metric(method):
    import functools
    from keras import backend as K
    import tensorflow as tf
    @functools.wraps(method)
    def wrapper(self, args, **kwargs):
        """ Wrapper for turning tensorflow metrics into keras metrics """
        value, update_op = method(self, args, **kwargs)
        K.get_session().run(tf.local_variables_initializer())
        with tf.control_dependencies([update_op]):
            value = tf.identity(value)
        return value
    return wrapper

@as_keras_metric
def bmac_metric(Y_true, Y_pred):
    return tf.metrics.mean_per_class_accuracy(tf.argmax(Y_true, axis=1), tf.argmax(Y_pred, axis=1), 3)