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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
self.activation = layer_conf.activation
if self.activation == nil then
self.activation = 'nerv.SigmoidLayer'
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({dout}, din), dim_out = {dout}, pr = pr},
},
[self.activation] = {
activation = {dim_in = {dout}, dim_out = {dout}},
},
['nerv.DuplicateLayer'] = {
duplicate = {dim_in = {dout}, dim_out = {dout, dout}},
},
}
local connections = {
{'main[1]', 'activation[1]', 0},
{'activation[1]', 'duplicate[1]', 0},
{'duplicate[1]', 'main[1]', 1},
{'duplicate[2]', '<output>[1]', 0},
}
for i = 1, #din do
table.insert(connections, {'<input>[' .. i .. ']', 'main[' .. (i + 1) .. ']', 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
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