-- Modification from the codebase of scott's icml16

-- please check https://github.com/reedscot/icml2016 for details

require 'image'

require 'nn'

require 'nngraph'

require 'cunn'

require 'cutorch'

require 'cudnn'

require 'lfs'

require 'torch'

torch.setdefaulttensortype('torch.FloatTensor')

local alphabet = "abcdefghijklmnopqrstuvwxyz0123456789-,;.!?:'\"/\\|_@#$%^&*~`+-=<>()[]{} "

local dict = {}

for i = 1,#alphabet do

dict[alphabet:sub(i,i)] = i

end

ivocab = {}

for k,v in pairs(dict) do

ivocab[v] = k

end

opt = {

filenames = '',

doc_length = 201,

queries = 'cub_queries.txt',

net_txt = '',

}

for k,v in pairs(opt) do opt[k] = tonumber(os.getenv(k)) or os.getenv(k) or opt[k] end

print(opt)

net_txt = torch.load(opt.net_txt)

if net_txt.protos ~=nil then net_txt = net_txt.protos.enc_doc end

net_txt:evaluate()

-- Extract all text features.

local fea_txt = {}

-- Decode text for sanity check.

local raw_txt = {}

local raw_img = {}

for query_str in io.lines(opt.queries) do

local txt = torch.zeros(1,opt.doc_length,#alphabet)

for t = 1,opt.doc_length do

local ch = query_str:sub(t,t)

local ix = dict[ch]

if ix ~= 0 and ix ~= nil then

txt[{1,t,ix}] = 1

end

end

raw_txt[#raw_txt+1] = query_str

txt = txt:cuda()

fea_txt[#fea_txt+1] = net_txt:forward(txt):clone()

end

torch.save(opt.filenames, {raw_txt=raw_txt, fea_txt=fea_txt})