1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
|
#!/usr/bin/env python
import argparse
import collections
import logging
import os
import shutil
import sys
import subprocess
import tempfile
import time
import cdec
import aligner
import decoder
import util
class RealtimeDecoder:
def __init__(self, configdir, tmpdir='/tmp', cache_size=5, norm=False):
cdec_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
# Temporary work dir
self.tmp = tempfile.mkdtemp(dir=tmpdir, prefix='realtime.')
logging.info('Using temp dir {}'.format(self.tmp))
# Normalization
self.norm = norm
if self.norm:
self.tokenizer = util.popen_io([os.path.join(cdec_root, 'corpus', 'tokenize-anything.sh'), '-u'])
self.detokenizer = util.popen_io([os.path.join(cdec_root, 'corpus', 'untok.pl')])
# Word aligner
fwd_params = os.path.join(configdir, 'a.fwd_params')
fwd_err = os.path.join(configdir, 'a.fwd_err')
rev_params = os.path.join(configdir, 'a.rev_params')
rev_err = os.path.join(configdir, 'a.rev_err')
self.aligner = aligner.ForceAligner(fwd_params, fwd_err, rev_params, rev_err)
# Grammar extractor
sa_config = cdec.configobj.ConfigObj(os.path.join(configdir, 'sa.ini'), unrepr=True)
sa_config.filename = os.path.join(self.tmp, 'sa.ini')
util.sa_ini_for_realtime(sa_config, os.path.abspath(configdir))
sa_config.write()
self.extractor = cdec.sa.GrammarExtractor(sa_config.filename, online=True)
self.grammar_files = collections.deque()
self.grammar_dict = {}
self.cache_size = cache_size
# HPYPLM reference stream
ref_fifo_file = os.path.join(self.tmp, 'ref.fifo')
os.mkfifo(ref_fifo_file)
self.ref_fifo = open(ref_fifo_file, 'w+')
# Start with empty line (do not learn prior to first input)
self.ref_fifo.write('\n')
self.ref_fifo.flush()
# Decoder
decoder_config = [[f.strip() for f in line.split('=')] for line in open(os.path.join(configdir, 'cdec.ini'))]
util.cdec_ini_for_realtime(decoder_config, os.path.abspath(configdir), ref_fifo_file)
decoder_config_file = os.path.join(self.tmp, 'cdec.ini')
with open(decoder_config_file, 'w') as output:
for (k, v) in decoder_config:
output.write('{}={}\n'.format(k, v))
decoder_weights = os.path.join(configdir, 'weights.final')
self.decoder = decoder.MIRADecoder(decoder_config_file, decoder_weights)
def close(self):
logging.info('Closing processes')
self.aligner.close()
self.decoder.close()
self.ref_fifo.close()
if self.norm:
self.tokenizer.stdin.close()
self.detokenizer.stdin.close()
logging.info('Deleting {}'.format(self.tmp))
shutil.rmtree(self.tmp)
def grammar(self, sentence):
grammar_file = self.grammar_dict.get(sentence, None)
# Cache hit
if grammar_file:
logging.info('Grammar cache hit')
return grammar_file
# Extract and cache
grammar_file = tempfile.mkstemp(dir=self.tmp, prefix='grammar.')[1]
with open(grammar_file, 'w') as output:
for rule in self.extractor.grammar(sentence):
output.write('{}\n'.format(str(rule)))
if len(self.grammar_files) == self.cache_size:
rm_sent = self.grammar_files.popleft()
# If not already removed by learn method
if rm_sent in self.grammar_dict:
rm_grammar = self.grammar_dict.pop(rm_sent)
os.remove(rm_grammar)
self.grammar_files.append(sentence)
self.grammar_dict[sentence] = grammar_file
return grammar_file
def decode(self, sentence):
# Empty in, empty out
if sentence.strip() == '':
return ''
if self.norm:
sentence = self.tokenize(sentence)
logging.info('Normalized input: {}'.format(sentence))
grammar_file = self.grammar(sentence)
start_time = time.time()
hyp = self.decoder.decode(sentence, grammar_file)
stop_time = time.time()
logging.info('Translation time: {} seconds'.format(stop_time - start_time))
# Empty reference: HPYPLM does not learn prior to next translation
self.ref_fifo.write('\n')
self.ref_fifo.flush()
if self.norm:
logging.info('Normalized translation: {}'.format(hyp))
hyp = self.detokenize(hyp)
return hyp
def tokenize(self, line):
self.tokenizer.stdin.write('{}\n'.format(line))
return self.tokenizer.stdout.readline().strip()
def detokenize(self, line):
self.detokenizer.stdin.write('{}\n'.format(line))
return self.detokenizer.stdout.readline().strip()
def learn(self, source, target):
if '' in (source.strip(), target.strip()):
logging.info('Error empty source or target: {} ||| {}'.format(source, target))
return
if self.norm:
source = self.tokenize(source)
target = self.tokenize(target)
# MIRA update before adding data to grammar extractor
grammar_file = self.grammar(source)
mira_log = self.decoder.update(source, grammar_file, target)
logging.info('MIRA: {}'.format(mira_log))
# Add aligned sentence pair to grammar extractor
alignment = self.aligner.align(source, target)
logging.info('Adding instance: {} ||| {} ||| {}'.format(source, target, alignment))
self.extractor.add_instance(source, target, alignment)
# Clear (old) cached grammar
rm_grammar = self.grammar_dict.pop(source)
os.remove(rm_grammar)
# Add to HPYPLM by writing to fifo (read on next translation)
logging.info('Adding to HPYPLM: {}'.format(target))
self.ref_fifo.write('{}\n'.format(target))
self.ref_fifo.flush()
|
