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local LMRecurrent = nerv.class('nerv.LMAffineRecurrentLayer', 'nerv.AffineRecurrentLayer') --breaks at sentence end, when </s> is met, input will be set to zero
--id: string
--global_conf: table
--layer_conf: table
--Get Parameters
function LMRecurrent:__init(id, global_conf, layer_conf)
nerv.AffineRecurrentLayer.__init(self, id, global_conf, layer_conf)
self.break_id = layer_conf.break_id --int, breaks recurrent input when the input (word) is break_id
self.independent = layer_conf.independent --bool, whether break
end
function LMRecurrent:propagate(input, output)
output[1]:mul(input[1], self.ltp_ih.trans, 1.0, 0.0, 'N', 'N')
if (self.independent == true) then
for i = 1, input[1]:nrow() do
if (input[1][i - 1][self.break_id - 1] > 0.1) then --here is sentence break
input[2][i - 1]:fill(0)
end
end
end
output[1]:mul(input[2], self.ltp_hh.trans, 1.0, 1.0, 'N', 'N')
output[1]:add_row(self.bp.trans, 1.0)
end
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