local RNNLayer = nerv.class('nerv.RNNLayer', 'nerv.GraphLayer')

function RNNLayer:__init(id, global_conf, layer_conf)
    nerv.Layer.__init(self, id, global_conf, layer_conf)
    self:check_dim_len(-1, 1)
    if #self.dim_in == 0 then
        nerv.error('RNN layer %s has no input', self.id)
    end

    local din = layer_conf.dim_in
    local dout = layer_conf.dim_out[1]

    local pr = layer_conf.pr
    if pr == nil then
        pr = nerv.ParamRepo({}, self.loc_type)
    end

    local layers = {
        ['nerv.AffineLayer'] = {
            main = {dim_in = table.connect(din, {dout}), dim_out = {dout}, pr = pr, activation = layer_conf.activation},
        },
        ['nerv.DuplicateLayer'] = {
            duplicate = {dim_in = {dout}, dim_out = {dout, dout}},
        },
    }

    local connections = {
        {'main[1]', 'duplicate[1]', 0},
        {'duplicate[1]', 'main[' .. (#din + 1) .. ']', 1},
        {'duplicate[2]', '<output>[1]', 0},
    }
    for i = 1, #din do
        table.insert(connections, {'<input>[' .. i .. ']', 'main[' .. i .. ']', 0})
    end

    self:add_prefix(layers, connections)
    local layer_repo = nerv.LayerRepo(layers, pr, global_conf)
    self.lrepo = layer_repo
    self:graph_init(layer_repo, connections)
end