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local SoftmaxLayer = nerv.class("nerv.SoftmaxLayer", "nerv.Layer")
function SoftmaxLayer:__init(id, global_conf, layer_conf)
nerv.Layer.__init(self, id, global_conf, layer_conf)
self:check_dim_len(1, 1) -- two inputs: nn output and label
end
function SoftmaxLayer:bind_params()
-- do nothing
end
function SoftmaxLayer:init(batch_size)
if self.dim_in[1] ~= self.dim_out[1] then
nerv.error("mismatching dimensions of input and output")
end
end
function SoftmaxLayer:batch_resize(batch_size)
-- do nothing
end
function SoftmaxLayer:update(bp_err, input, output)
-- no params, therefore do nothing
end
function SoftmaxLayer:propagate(input, output)
output[1]:softmax(input[1])
end
function SoftmaxLayer:back_propagate(bp_err, next_bp_err, input, output)
local nbe = next_bp_err[1]
nbe:mul_elem(bp_err[1], output[1])
local offset = nbe:rowsum()
nbe:copy_from(bp_err[1])
nbe:add_row(offset, -1.0)
nbe:mul_elem(nbe, output[1])
end
function SoftmaxLayer:get_params()
return nerv.ParamRepo({}, self.loc_type)
end
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