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- require 'torch' -- torch
- require 'optim'
- require 'nn' -- provides a normalization operator
- function string:split(sep)
- local sep, fields = sep, {}
- local pattern = string.format("([^%s]+)", sep)
- self:gsub(pattern, function(substr) fields[#fields + 1] = substr end)
- return fields
- end
- local f_file = io.open(arg[1], 'r')
- local p_file = io.open(arg[2], 'w')
- local data = torch.Tensor(1, 351)
- local name = ''
- for line in f_file:lines('*l') do
- local l = line:split(',')
- first = true
- for key, val in ipairs(l) do
- if first == false then
- data[1][key] = val
- else data[1][key] = 0
- first = false
- name = val
- end
- end
- end
- local X = data[{{},{2,-1}}]
- print(X)
- model = torch.load('estimation_model.dat')
- local myPrediction = model:forward(X)
- p_file:write('NAME,F1,F2,F3,F4n')
- p_file:write(name..','..tostring(1000*myPrediction[1]
- [1])..','..tostring(1000*myPrediction[1]
- [2])..','..tostring(1000*myPrediction[1]
- [3])..','..tostring(1000*myPrediction[1][4])..'n')
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