local DuplicateLayer = nerv.class('nerv.DuplicateLayer', 'nerv.Layer')

function DuplicateLayer:__init(id, global_conf, layer_conf)
    self.id = id
    self.dim_in = layer_conf.dim_in
    self.dim_out = layer_conf.dim_out
    self.gconf = global_conf
    self:check_dim_len(1, -1)
    if #self.dim_out < 1 then
        nerv.error('no output specified')
    end
    for i = 1, #self.dim_out do
        if self.dim_out[i] ~= self.dim_in[1] then
            nerv.error('mismatching dimensions of outputs')
        end
    end
end

function DuplicateLayer:init(batch_size)
end

function DuplicateLayer:batch_resize(batch_size)
end

function DuplicateLayer:update(bp_err, input, output)
end

function DuplicateLayer:propagate(input, output)
    for i = 1, #self.dim_out do
        output[i]:copy_from(input[1])
        -- FIXME: use reference copy to speed up
    end
end

function DuplicateLayer:back_propagate(bp_err, next_bp_err, input, output)
    next_bp_err:copy_from(bp_err[1])
    for i = 2, #self.dim_out do
        next_bp_err:add(next_bp_err, bp_err[i], 1.0, 1.0)
    end
end