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#!/usr/bin/env python
from collections import Counter
import logging
import optparse
import os
import os.path
import sys
import extract
LOG = logging.getLogger(__name__)
def get_pruned_vocab(corpus, prune):
counts = Counter()
LOG.info("Reading vocabulary from %s" % corpus)
lines = 0
for line in open(corpus):
for token in line[:-1].split():
counts[token] += 1
lines += 1
if lines % 1000 == 0:
sys.stderr.write(".")
if lines % 50000 == 0:
sys.stderr.write(" [%d]\n" % lines)
sys.stderr.write("\n")
counts[extract.BOS] += lines
counts[extract.EOS] += lines
LOG.info("Vocabulary size: %d" % len(counts))
if prune:
return Counter(dict(counts.most_common(prune)))
else:
return counts
def save_vocab(directory, filename, vocab):
fh = open(directory + "/" + filename, "w")
for word in vocab:
print>>fh, word
def main():
logging.basicConfig(
format='%(asctime)s %(levelname)s: %(message)s',
datefmt='%Y-%m-%d %H:%M:%S', level=logging.DEBUG)
parser = optparse.OptionParser("%prog [options]")
parser.add_option(
"-e", "--target-language", type="string", dest="target_language")
parser.add_option(
"-f", "--source-language", type="string", dest="source_language")
parser.add_option("-c", "--corpus", type="string", dest="corpus_stem")
parser.add_option(
"-t", "--tagged-corpus", type="string", dest="tagged_stem")
parser.add_option("-a", "--align", type="string", dest="align_file")
parser.add_option("-w", "--working-dir", type="string", dest="working_dir")
parser.add_option("-n", "--target-context", type="int", dest="n")
parser.add_option("-m", "--source-context", type="int", dest="m")
parser.add_option("-s", "--prune-source-vocab", type="int", dest="sprune")
parser.add_option("-p", "--prune-target-vocab", type="int", dest="tprune")
parser.set_defaults(
target_language="en",
source_language="de",
corpus_stem="train.10k",
align_file="train.10k.align",
n=5,
m=4,
working_dir="working",
sprune=16000,
tprune=16000
)
options, args = parser.parse_args(sys.argv)
if not os.path.exists(options.working_dir):
os.makedirs(options.working_dir)
else:
LOG.warn("Directory %s already exists, re-using" % options.working_dir)
info_file = options.working_dir + "/info"
if os.path.exists(info_file):
for line in open(info_file):
name, value = line[:-1].split()
n_mismatch = (name == 'n' and int(value) != options.n)
m_mismatch = (name == 'm' and int(value) != options.m)
if n_mismatch or m_mismatch:
LOG.error(
"info file exists, but parameters do not match. "
"Delete working directory and rerun.")
sys.exit(1)
else:
ifh = open(info_file, "w")
print>>ifh, "m", options.m
print>>ifh, "n", options.n
ifh.close()
scorpus = options.corpus_stem + "." + options.source_language
tcorpus = options.corpus_stem + "." + options.target_language
tvocab, svocab = None, None
# Extract vocabulary, and prune, if required.
svocab = get_pruned_vocab(scorpus, options.sprune)
tvocab = get_pruned_vocab(tcorpus, options.tprune)
file_stem = os.path.basename(options.corpus_stem)
ngram_file = options.working_dir + "/" + file_stem + ".ngrams"
ofh = open(ngram_file, "w")
tags = extract.get_ngrams(
options.corpus_stem,
options.align_file,
options.tagged_stem,
svocab,
tvocab,
options.source_language,
options.target_language,
options.m,
options.n,
ofh)
# Save vocabularies.
del svocab["<null>"]
del tvocab["<null>"]
del svocab["<unk>"]
del tvocab["<unk>"]
svocab_list = [item[0] for item in svocab.most_common()]
tvocab_list = [item[0] for item in tvocab.most_common()]
# UNK is always the first vocabulary element. Make sure
# it appears in position 0
# We need to use <null> token in the chart decoder in order
# to correctly estimate the probabilities of incomplete subphrases
# that are not sentence initial.
tvocab_list.insert(0, "<null>")
tvocab_list.insert(0, "<unk>")
svocab_list.insert(0, "<unk>")
# Get tags:
tag_list = [item[0] for item in tags.most_common()]
svocab_list = svocab_list + tag_list
tvocab_list = tvocab_list + tag_list
save_vocab(options.working_dir, "vocab.source", svocab_list)
save_vocab(options.working_dir, "vocab.target", tvocab_list)
# Create vocab dictionaries that map word to ID.
tvocab_idmap = {}
for i in range(len(tvocab_list)):
tvocab_idmap[tvocab_list[i]] = i
svocab_idmap = {}
for i in range(len(svocab_list)):
svocab_idmap[svocab_list[i]] = i + len(tvocab_idmap)
numberized_file = options.working_dir + "/" + file_stem + ".numberized"
ngrams_file_handle = open(ngram_file, 'r')
numberized_file_handle = open(numberized_file, 'w')
# Numberize the file.
for line in ngrams_file_handle:
numberized_file_handle.write(
extract.numberize(
line, options.m, options.n, svocab_idmap, tvocab_idmap))
numberized_file_handle.close()
ngrams_file_handle.close()
if __name__ == "__main__":
main()
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