import tensorflow as tf

            params.vocabulary["char"],
            control_symbols
        )
    }

    return params


def get_initializer(params):
    if params.initializer == "xavier":
        return tf.contrib.layers.xavier_initializer()
    elif params.initializer == "uniform":
        max_val = params.initializer_gain
        return tf.random_uniform_initializer(-max_val, max_val)
    elif params.initializer == "normal":
        return tf.random_normal_initializer(0.0, params.initializer_gain)
    elif params.initializer == "normal_unit_scaling":
        return tf.variance_scaling_initializer(params.initializer_gain,
                                               mode="fan_avg",
                                               distribution="normal")
