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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
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