import tensorflow.contrib.layers as layers

        return out


def simple_model_w_feat_eng(img_in, num_actions, scope, reuse=False):
    with tf.variable_scope(scope, reuse=reuse):
        out = img_in
        out = layers.flatten(out)
        # stddev = 1/n, where n = number of inputs
        gauss_initializer = initializers.xavier_initializer(uniform=False)
        with tf.variable_scope("action_value"):
            out = layers.fully_connected(
                out,
