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#!/usr/bin/env python
import sys
import os
import re
import gzip
import argparse
import logging
import signal
import multiprocessing as mp
import cdec.sa
from cdec.sa._sa import monitor_cpu
extractor, prefix = None, None
online, compress = False, False
def make_extractor(args):
global extractor, prefix, online, compress
signal.signal(signal.SIGINT, signal.SIG_IGN) # Let parent process catch Ctrl+C
load_features(args.features)
extractor = cdec.sa.GrammarExtractor(args.config, online)
prefix = args.grammars
online = args.online
compress = args.compress
def load_features(features):
for featdef in features:
logging.info('Loading additional feature definitions from %s', featdef)
prefix = os.path.dirname(featdef)
sys.path.append(prefix)
__import__(os.path.basename(featdef).replace('.py', ''))
sys.path.remove(prefix)
def extract(inp):
global extractor, prefix, online, compress
i, sentence = inp
sentence = sentence[:-1]
fields = re.split('\s*\|\|\|\s*', sentence)
suffix = ''
# 3 fields for online mode, 1 for normal
if online:
if len(fields) < 3:
sys.stderr.write('Error: online mode requires references and alignments.'
' Not adding sentence to training data: {}\n'.format(sentence))
sentence = fields[0]
else:
sentence, reference, alignment = fields[0:3]
if len(fields) > 3:
suffix = ' ||| ' + ' ||| '.join(fields[3:])
else:
if len(fields) > 1:
sentence = fields[0]
suffix = ' ||| ' + ' ||| '.join(fields[1:])
grammar_file = os.path.join(prefix, 'grammar.'+str(i))
if compress: grammar_file += '.gz'
with (gzip.open if compress else open)(grammar_file, 'w') as output:
for rule in extractor.grammar(sentence):
output.write(str(rule)+'\n')
# Add training instance _after_ extracting grammars
if online:
extractor.add_instance(sentence, reference, alignment)
grammar_file = os.path.abspath(grammar_file)
return '<seg grammar="{}" id="{}">{}</seg>{}'.format(grammar_file, i, sentence, suffix)
def stream_extract():
global extractor, online, compress
while True:
line = sys.stdin.readline()
if not line:
break
fields = re.split('\s*\|\|\|\s*', line.strip())
# context ||| cmd
if len(fields) == 2:
(context, cmd) = fields
if cmd.lower() == 'drop':
if online:
extractor.drop_ctx(context)
sys.stdout.write('drop {}\n'.format(context))
else:
sys.stdout.write('Error: online mode not set. Skipping line: {}\n'.format(line.strip()))
# context ||| sentence ||| grammar_file
elif len(fields) == 3:
(context, sentence, grammar_file) = fields
with (gzip.open if compress else open)(grammar_file, 'w') as output:
for rule in extractor.grammar(sentence, context):
output.write(str(rule)+'\n')
sys.stdout.write('{}\n'.format(grammar_file))
# context ||| sentence ||| reference ||| alignment
elif len(fields) == 4:
(context, sentence, reference, alignment) = fields
if online:
extractor.add_instance(sentence, reference, alignment, context)
sys.stdout.write('learn {}\n'.format(context))
else:
sys.stdout.write('Error: online mode not set. Skipping line: {}\n'.format(line.strip()))
else:
sys.stdout.write('Error: see README.md for stream mode usage. Skipping line: {}\n'.format(line.strip()))
sys.stdout.flush()
def stream_extract2(url):
global extractor, online, compress
import nanomsg
from nanomsg import Socket, PAIR, PUB
socket = nanomsg.Socket(nanomsg.PAIR)
socket.bind(url)
sys.stderr.write("[extractor] sending hello ...\n")
socket.send("hello")
default_context = "default_context"
while True:
line = socket.recv()
if line.strip() == "shutdown":
sys.stderr.write("[extractor] shutting down\n")
break
if not line:
break
fields = re.split('\s*\|\|\|\s*', line.strip())
# error
if len(fields) == 1:
socket.send("[extractor] error: can't process input '{}'".format(line.strip()))
# context ||| cmd
if len(fields) == 2:
(context, cmd) = fields
assert(context == default_context)
if cmd.lower() == 'drop':
if online:
extractor.drop_ctx(context)
socket.send("[extractor] dropping context '{}'".format(context))
else:
socket.send("[extractor] error: online mode not set, skipping input: {}".format(line.strip()))
else:
socket.send("[extractor] don't know command '{}'".format(cmd))
# context ||| sentence ||| grammar_file
elif len(fields) == 3:
(context, sentence, grammar_file) = fields
assert(context == default_context)
with (gzip.open if compress else open)(grammar_file, 'w') as output:
for rule in extractor.grammar(sentence, context):
output.write(str(rule)+'\n')
socket.send('{}'.format(grammar_file))
# context ||| sentence ||| reference ||| alignment
elif len(fields) == 4:
(context, sentence, reference, alignment) = fields
assert(context == default_context)
extractor.add_instance(sentence, reference, alignment, context)
socket.send("[extractor] learning (context: '{}')".format(context))
else:
socket.send("[extractor] error, skipping input: '{}'".format(line.strip()))
socket.send("off")
socket.close()
def main():
global online
logging.basicConfig(level=logging.INFO)
parser = argparse.ArgumentParser(description='Extract grammars from a compiled corpus.')
parser.add_argument('-c', '--config', required=True,
help='extractor configuration')
parser.add_argument('-g', '--grammars',
help='grammar output path')
parser.add_argument('-j', '--jobs', type=int, default=1,
help='number of parallel extractors')
parser.add_argument('-s', '--chunksize', type=int, default=10,
help='number of sentences / chunk')
parser.add_argument('-f', '--features', nargs='*', default=[],
help='additional feature definitions')
parser.add_argument('-o', '--online', action='store_true',
help='online grammar extraction')
parser.add_argument('-z', '--compress', action='store_true',
help='compress grammars with gzip')
parser.add_argument('-t', '--stream', action='store_true',
help='stream mode (see README.md)')
parser.add_argument('-u', '--stream2', action='store_true',
help='stream2 mode')
parser.add_argument('-S', '--sock_url', default='tcp://127.0.0.1:8888',
help='socket url')
args = parser.parse_args()
if not (args.grammars or (args.stream or args.stream2)):
sys.stderr.write('Error: either -g/--grammars or -t/--stream required\n')
sys.exit(1)
if args.grammars and not os.path.exists(args.grammars):
os.mkdir(args.grammars)
for featdef in args.features:
if not featdef.endswith('.py'):
sys.stderr.write('Error: feature definition file <{}>'
' should be a python module\n'.format(featdef))
sys.exit(1)
online = args.online
stream = args.stream
stream2 = args.stream2
if stream2:
online = True
start_time = monitor_cpu()
if args.jobs > 1:
if stream:
sys.stderr.write('Error: stream mode incompatible with multiple jobs\n')
sys.exit(1)
logging.info('Starting %d workers; chunk size: %d', args.jobs, args.chunksize)
pool = mp.Pool(args.jobs, make_extractor, (args,))
try:
for output in pool.imap(extract, enumerate(sys.stdin), args.chunksize):
print(output)
except KeyboardInterrupt:
pool.terminate()
else:
make_extractor(args)
if stream:
stream_extract()
if stream2:
stream_extract2(args.sock_url)
else:
for output in map(extract, enumerate(sys.stdin)):
print(output)
stop_time = monitor_cpu()
logging.info("Overall extraction step took %f seconds", stop_time - start_time)
if __name__ == '__main__':
main()
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