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Towards-Implicit-Content-Introducing-for-Generative-Short-Text-Conversation-Systems
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build_dictionary.py
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import numpy
import cPickle as pkl
import sys
import fileinput
from collections import OrderedDict
def main():
for filename in sys.argv[1:]:
print 'Processing', filename
word_freqs = OrderedDict()
with open(filename, 'r') as f:
for line in f:
words_in = line.strip().split()
for w in words_in:
if w not in word_freqs:
word_freqs[w] = 0
word_freqs[w] += 1
words = word_freqs.keys()
freqs = word_freqs.values()
sorted_idx = numpy.argsort(freqs)
sorted_words = [words[ii] for ii in sorted_idx[::-1]]
worddict = OrderedDict()
worddict['eos'] = 0
worddict['UNK'] = 1
worddict['bos'] = 2
for ii, ww in enumerate(sorted_words):
worddict[ww] = ii+3
with open('%s.pkl'%filename, 'wb') as f:
pkl.dump(worddict, f)
print 'Word dict length: ', len(worddict)
print 'Done'
if __name__ == '__main__':
main()