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