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.set_defaults(
target_language = "en",
source_language = "de",
corpus_stem = "test",
align_file = "test.align",
working_dir = "working",
)
options,args = parser.parse_args(sys.argv)
if not os.path.exists(options.working_dir):
LOG.error("Working directory '%s' not found" % working_dir)
sys.exit(1)
m,n = None,None
for line in open(options.working_dir + "/info"):
name,value = line[:-1].split()
if name == "m": m = int(value)
if name == "n": n = int(value)
if m == None or n == None:
LOG.error("info file is incomplete")
sys.exit(1)
tvocab, offset = read_vocab(options.working_dir + "/vocab.target")
svocab, offset = read_vocab(options.working_dir + "/vocab.source", offset+1)
file_stem = os.path.basename(options.corpus_stem)
ofh = open(options.working_dir + "/" + file_stem + ".ngrams", "w")
extract.get_ngrams(options.corpus_stem,
options.align_file,
options.tagged_stem,
svocab,
tvocab,
options.source_language,
options.target_language,
m,
n,
ofh)
numberized_file = options.working_dir + "/" + file_stem + ".numberized"
ngrams_file_handle = open(options.working_dir + "/" + file_stem + ".ngrams", 'r')
numberized_file_handle = open(numberized_file, 'w')
#Numberize the file
for line in ngrams_file_handle:
numberized_file_handle.write(extract.numberize(line, m, n, svocab, tvocab))
numberized_file_handle.close()
ngrams_file_handle.close()
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.set_defaults(target_language="en",
source_language="de",
corpus_stem="test",
align_file="test.align",
working_dir="working")
options, args = parser.parse_args(sys.argv)
if not os.path.exists(options.working_dir):
raise Exception("Working directory '%s' not found" %
options.working_dir)
m, n = None, None
for line in open(options.working_dir + "/info"):
name, value = line[:-1].split()
if name == "m":
m = int(value)
if name == "n":
n = int(value)
if m is None or n is None:
raise Exception("Info file is incomplete.")
tvocab, offset = read_vocab(options.working_dir + "/vocab.target")
svocab, offset = read_vocab(options.working_dir + "/vocab.source",
offset + 1)
file_stem = os.path.basename(options.corpus_stem)
ofh = open(options.working_dir + "/" + file_stem + ".ngrams", "w")
extract.get_ngrams(options.corpus_stem, options.align_file,
options.tagged_stem, svocab, tvocab,
options.source_language, options.target_language, m, n,
ofh)
numberized_file = options.working_dir + "/" + file_stem + ".numberized"
ngrams_file_handle = open(
os.path.join(options.working_dir, file_stem + ".ngrams"), 'r')
numberized_file_handle = open(numberized_file, 'w')
# Numberize the file.
for line in ngrams_file_handle:
numberized_file_handle.write(
extract.numberize(line, m, n, svocab, tvocab))
numberized_file_handle.close()
ngrams_file_handle.close()
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()
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()
if name == "n" and int(value) != options.n or \
name == "m" and int(value) != options.m:
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, m, n, tvocab_idmap, tvocab_idmap))
numberized_file_handle.close()
ngrams_file_handle.close()