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if #arg < 1 then
return
end
dofile(arg[1])
gconf.mmat_type = nerv.MMatrixFloat
gconf.cumat_type = nerv.CuMatrixFloat
local scp_file = gconf.tr_scp
local loc_type = nerv.ParamRepo.LOC_TYPES.ON_HOST
local reader_spec = make_readers(scp_file)[1]
local reader = reader_spec.reader
local width = reader_spec.data['main_scp']
local mean = gconf.mmat_type(1, width)
local std = gconf.mmat_type(1, width)
local colsum = gconf.mmat_type(1, width)
local total = 0.0
local EPS = 1e-7
mean:fill(0)
std:fill(0)
local cnt = 0
while (true) do
ret = reader:get_data()
if ret == nil then
break
end
local utt = ret['main_scp']
colsum = utt:colsum()
mean:add(mean, colsum, 1, 1)
utt:mul_elem(utt, utt)
colsum = utt:colsum()
std:add(std, colsum, 1, 1)
total = total + utt:nrow()
cnt = cnt + 1
if cnt == 1000 then
nerv.info("accumulated %d utterances", cnt)
cnt = 0
end
end
local bparam = nerv.BiasParam("bias0", gconf)
bparam.trans = gconf.mmat_type(1, width)
mean:add(mean,mean, -1.0 / total, 0) -- -E(X)
bparam.trans:copy_fromh(mean)
mean:mul_elem(mean, mean) -- E^2(X)
std:add(std, mean, 1 / total, -1) -- sigma ^ 2
for i = 0, width - 1 do
std[0][i] = math.sqrt(std[0][i] + EPS)
std[0][i] = 1 / (std[0][i] + EPS)
end
local wparam = nerv.BiasParam("window0", gconf)
wparam.trans = std
local pr = nerv.ParamRepo({bparam, wparam}, loc_type)
pr:export("global_transf.nerv", nil)
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