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local SigmoidLayer = nerv.class("nerv.SigmoidLayer", "nerv.Layer")
function SigmoidLayer:__init(id, global_conf, layer_conf)
self.id = id
self.gconf = global_conf
self.dim_in = layer_conf.dim_in
self.dim_out = layer_conf.dim_out
self:check_dim_len(1, 1)
end
function SigmoidLayer:init()
if self.dim_in[1] ~= self.dim_out[1] then
nerv.error("mismatching dimensions of input and output")
end
end
function SigmoidLayer:update(bp_err, input, output)
-- no params, therefore do nothing
end
function SigmoidLayer:propagate(input, output)
output[1]:sigmoid(input[1])
end
function SigmoidLayer:back_propagate(next_bp_err, bp_err, input, output)
next_bp_err[1]:sigmoid_grad(bp_err[1], output[1])
end
function SigmoidLayer:get_params()
return {}
end
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