Files
gf-core/src/runtime/python/examples/translation_pipeline.py
2016-09-19 08:32:08 +00:00

422 lines
16 KiB
Python

#!/usr/bin/env python
# Python 2 and 3 compatible
from __future__ import print_function
"""
"""
import argparse, codecs, copy, itertools, logging, math, operator, os, os.path, re, string, sys, time;
try:
from itertools import imap as map;
from itertools import ifilter as filter;
except ImportError:
pass;
import xml.etree.ElementTree as etree;
import pgf;
import gf_utils;
# http://snipplr.com/view/25657/indent-xml-using-elementtree/
def indentXMLNodes(elem, level=0):
i = "\n" + level*" "
if len(elem):
if not elem.text or not elem.text.strip():
elem.text = i + " "
if not elem.tail or not elem.tail.strip():
elem.tail = i
for elem in elem:
indentXMLNodes(elem, level+1)
if not elem.tail or not elem.tail.strip():
elem.tail = i
else:
if level and (not elem.tail or not elem.tail.strip()):
elem.tail = i
def readTranslationPipelineOptions(propsfile, default_namespace):
with codecs.open(propsfile, 'r', 'utf-8') as infile:
for line in infile:
if not line.strip():
continue;
key, value = line.strip().split('=', 1);
key, value = key.strip(), value.strip();
if key == 'srclang':
default_namespace.srclang = value;
elif key == 'tgtlangs':
default_namespace.tgtlangs = [val.strip() for val in ','.split(value)];
elif key == 'input':
default_namespace.input = value;
elif key == 'format':
default_namespace.format = value;
elif key == 'exp_directory':
default_namespace.exp_directory = value;
else:
logging.warning("Unknown option-%s found in props file. Ignoring and proceeding." %(key));
continue;
return default_namespace;
def sgmReader(sgmDoc):
root = sgmDoc.getroot();
for element in root.iter():
if element.text is not None and element.text.strip():
yield element.text.strip().encode('utf-8');
def addToSgm(sgmDoc, strItem):
for node in sgmDoc.findall('.//seg'):
if not node.text.strip():
strItem = strItem.decode('utf-8');
node.text = ' %s ' %(strItem if strItem.strip() else 'EMPTY');
return;
logging.error("No more nodes available for adding content");
return;
def sgmWriter(sgmDoc):
indentXMLNodes( sgmDoc.getroot() );
return etree.tostring(sgmDoc.getroot(), encoding='utf-8', method='xml');
def getXMLSkeleton(sgmDoc, tgtlang):
skeletonDoc = copy.deepcopy(sgmDoc);
root = skeletonDoc.getroot();
root.tag = 'tstset';
root.attrib['trlang'] = tgtlang[-3:];
root.find('doc').attrib['sysid'] = tgtlang[:-3];
for node in root.findall('.//seg'):
node.text = '';
return skeletonDoc;
def pipeline_lexer(sentence):
tokens = sentence.strip().split();
#tokens = filter(None, re.split('(\W+)', sentence.strip()));
n = len(tokens);
idx = len(tokens)-1;
while idx >= 0:
if tokens[idx] in ".?!)":
idx -= 1;
else:
break;
tokens = tokens[:idx+1];
idx = 0;
while idx < len(tokens):
if tokens[idx] in "'\"(":
idx += 1;
else:
break;
tokens = tokens[idx:];
return ' '.join(tokens);
def clean_gfstrings(sentence):
absFuncName = re.compile('\[[^]]+?\]');
untranslatedEntries = {};
for entry in re.findall(absFuncName, sentence):
untranslatedEntries[entry] = untranslatedEntries.setdefault(entry, 0)+1;
for entry in untranslatedEntries:
while untranslatedEntries[entry] > 1:
sentence = sentence.replace(entry, '', 1);
untranslatedEntries[entry] -= 1;
sentence = sentence.replace(entry, \
' '.join(entry[1:-1].split('_')[:-1]) if entry.find('_') != -1 \
else '');
return ' '.join( sentence.split() );
def parseNames(grammar, language, sentence):
def callback(lin_idx, start):
moving_start, end, eot = start, len(sentence), True;
if moving_start < end and (not sentence[moving_start].isupper()):
return None;
while moving_start < end:
if sentence[moving_start] in string.whitespace:
eot = True;
elif eot and sentence[moving_start].isupper():
eot = False;
elif eot and (not sentence[moving_start].isupper()):
end = moving_start-1;
break;
moving_start += 1;
possible_name = sentence[start:end].strip();
if possible_name:
if language.endswith('Eng') and \
(possible_name == "I" or possible_name == "I'm"):
return None;
elif language.endswith('Eng') and possible_name.endswith("'s"):
end_idx = possible_name.rfind("'s");
if end_idx != -1:
possible_name = possible_name[:end_idx].strip();
end -= 2;
if not possible_name:
return None;
expr, prob = None, None;
for analysis in grammar.languages[language].lookupMorpho(possible_name):
category = grammar.functionType(analysis[0]).cat;
if prob < analysis[-1]:
if category == "PN":
expr, prob = pgf.Expr(analysis[0], []), analysis[-1];
elif category == "Weekday":
expr, prob = pgf.Expr("weekdayPN", \
[pgf.Expr(analysis[0], [])]), analysis[-1];
elif category == "Month":
expr, prob = pgf.Expr("monthPN", \
[pgf.Expr(analysis[0], [])]), analysis[-1];
elif category == "Language":
return None;
# generic named entity
if expr == None:
expr = pgf.Expr(possible_name);
expr = pgf.Expr("MkSymb", [expr]);
expr = pgf.Expr("SymbPN", [expr]);
return (expr, 0, end);
return None;
return callback;
def parseUnknown(grammar, language, sentence):
def callback(lin_idx, start):
moving_start, end, eot = start, len(sentence), True;
# -- added to deal with segmentation errors like may => ma_N + Symb y
isNewToken = (moving_start == 0) or \
(moving_start > 1 and sentence[moving_start-1].isspace())
if moving_start < end and (not sentence[moving_start].isupper()):
while moving_start < end:
if sentence[moving_start] in string.whitespace:
end = moving_start;
break;
moving_start += 1;
unknown_word = sentence[start:end].strip();
if unknown_word and isNewToken:
count = 0;
for analysis in grammar.languages[language].lookupMorpho(unknown_word):
count += 1;
if not count:
expr = pgf.Expr("MkSymb", [pgf.Expr(unknown_word)]);
return (expr, 0, end);
return None;
return callback;
def parseTester(grammar, language, sentence):
def callback(lin_idx, start):
if start < len(sentence):
return (pgf.Expr(sentence[start]), 0, start+1);
return None;
return callback;
def translateWordsAsChunks(grammar, language, tgtlanguages, word):
parser = grammar.languages[language].parse;
linearizersList = dict((lang, grammar.languages[lang].linearize) \
for lang in tgtlanguages);
translations = [];
try:
for parseidx, parse in enumerate( parser(word) ):
for lang in tgtlanguages:
trans = linearizersList[lang](parse[1]);
translations.append((lang, gf_utils.postprocessor(\
trans.strip() if trans else '')));
break;
except pgf.ParseError as err:
return [];
return translations;
def translateWord(grammar, language, tgtlanguages, word):
possible_translations = translateWordsAsChunks(grammar, language, \
tgtlanguages, word);
if len(possible_translations):
return possible_translations;
lowerword = word.lower();
try:
partialExprList = grammar.languages[language].parse(word, cat='Chunk');
for expr in partialExprList:
return [(lang, gf_utils.gf_postprocessor(\
grammar.languages[lang].linearize(expr[1]))) \
for lang in tgtlanguages];
except pgf.ParseError:
morphAnalysis = grammar.languages[language].lookupMorpho(word) +\
grammar.languages[language].lookupMorpho(lowerword);
for morph in morphAnalysis:
countPositiveLanguages = list(filter(None, \
[grammar.languages[lang].hasLinearization(morph[0]) \
for lang in tgtlanguages]));
if len(countPositiveLanguages) > 0.5*len(tgtlanguages):
return [(lang, \
gf_utils.gf_postprocessor(grammar.languages[lang].linearize(pgf.readExpr(morph[0])))) \
for lang in tgtlanguages];
return [(lang, word) for lang in tgtlanguages];
def translationByLookup(grammar, language, tgtlanguages, sentence):
parser = grammar.languages[language].parse;
linearizersList = dict([(lang, grammar.languages[lang].linearize) \
for lang in tgtlanguages]);
queue = [sentence.strip().split()];
transChunks = {};
while len(queue):
head = queue[0];
if not len(head):
pass;
elif len(head) == 1 and head[0].strip():
for lang, wordchoice in translateWord(grammar, language, \
tgtlanguages, head[0]):
transChunks.setdefault(lang, []).append(\
gf_utils.postprocessor(wordchoice));
else:
try:
for parseidx, parse in enumerate(parser(' '.join(head))):
for lang in tgtlanguages:
if linearizersList[lang](parse[1]) == None:
transChunks.setdefault(lang, []).append(' ');
else:
transChunks.setdefault(lang, []).append(\
gf_utils.postprocessor(linearizersList[lang](parse[1]).strip()));
break;
except pgf.ParseError as err:
#unseenToken = re.findall('"[^"]+?"', err.message)[0][1:-1];
unseenToken = err.message.strip().split()[-1][1:-1];
idx = head.index(unseenToken);
queue.insert(1, head[:idx] );
queue.insert(2, [head[idx]] );
queue.insert(3, head[idx+1:] );
del queue[0];
for lang in tgtlanguages:
yield (lang, ' '.join(transChunks[lang]));
def pipelineParsing(grammar, language, sentences, K=20):
#buf = [sent for sent in sentences];
buf, sentences = itertools.tee(sentences, 2);
parser = gf_utils.getKBestParses(grammar, language, K);
for sent, (time, parsesBlock) in zip(buf, map(parser, sentences)):
yield (sent, parsesBlock);
def translation_pipeline(props):
if props.propsfile:
props = readTranslationPipelineOptions(props.propsfile, props);
# UGLY HACK FOR K-best translation: if K-best translation output format is only txt
if props.bestK != 1:
props.format = 'txt';
if not os.path.isdir( props.exp_directory ):
logging.info("Creating output directory: %s" %(props.exp_directory));
os.makedirs(props.exp_directory);
if not props.srclang:
logging.critical("Mandatory option source-lang missing. Can not determine source language.");
sys.exit(1);
grammar = pgf.readPGF(props.pgffile);
sourceLanguage = filter(None, [lang if lang[-3:] == props.srclang else '' for lang in grammar.languages.keys()]);
sourceLanguage = list(sourceLanguage)[0];
logging.info("Translating from %s" %(sourceLanguage));
if len(props.tgtlangs):
target_langs = props.tgtlangs;
else:
target_langs = filter(None, [lang[-3:] if lang != sourceLanguage \
else '' for lang in grammar.languages.keys()]);
targetLanguages = filter(None, [lang if lang[-3:] in target_langs \
else '' for lang in grammar.languages.keys()]);
targetLanguages = list(targetLanguages);
logging.info("Translating into the following languages: %s" %(','.join(targetLanguages)));
K = props.bestK if props.bestK != 1 else 20; # by default we look for 20 best parses
bestK = props.bestK;
if not props.input:
logging.info( "Input file name missing. Reading input from stdin." );
inputStream = sys.stdin;
outputPrefix = os.getpid();
else:
inputStream = codecs.open(props.input, 'r');
outputPrefix = os.path.splitext( os.path.split(props.input)[1] )[0];
if props.format == 'sgm':
inputDoc = etree.parse(inputStream);
reader = sgmReader;
skeletonDoc = getXMLSkeleton;
addItem = addToSgm;
writer = sgmWriter;
elif props.format == 'txt':
logging.info("Input format is txt. Assuming one-sentence-per-line format.");
inputDoc = inputStream;
reader = lambda X: X;
skeletonDoc = lambda X, lang: list();
addItem = lambda X, y: list.append(X, y);
writer = lambda X: ('\n'.join(X) if bestK == 1 else \
'\n'.join(map(gf_utils.printMosesNbestFormat, X)));
translationBlocks = {};
for tgtlang in targetLanguages+['abstract']:
translationBlocks[tgtlang] = skeletonDoc(inputDoc, tgtlang);
preprocessor = pipeline_lexer;
postprocessor = clean_gfstrings;
logging.info( "Parsing text in %s" %(sourceLanguage) );
# 1. Get Abstract Trees for sentences in source language.
tokenized_sentences = map(preprocessor, reader(inputDoc));
web_lexer = gf_utils.Lexer('Web', grammar, sourceLanguage).tokenize;
absParses = [parsesBlock for parsesBlock in \
pipelineParsing(grammar, sourceLanguage, \
map(web_lexer, tokenized_sentences), K)];
logging.info( "Linearizing into %s" %(','.join(targetLanguages)) );
# 2. Linearize in all target Languages
for idx, parsesBlock in enumerate( map(operator.itemgetter(1), absParses) ):
translationBuffer = {};
if not len(parsesBlock):
# failed to parse;
# translate using lookup
for tgtlang, translation in translationByLookup(grammar, sourceLanguage,\
targetLanguages, absParses[idx][0]):
if bestK == 1:
addItem(translationBlocks[tgtlang], postprocessor(translation));
else:
addItem(translationBlocks[tgtlang], [((0,), postprocessor(translation))]);
addItem(translationBlocks['abstract'], '');
else:
bestTranslationIdx = 0;
for tgtlang in targetLanguages:
translationBuffer[tgtlang] = next(gf_utils.getKLinearizations(grammar, \
tgtlang, [parsesBlock], K=bestK));
if bestK == 1:
for tidx, translation in enumerate(translationBuffer[tgtlang]):
if postprocessor(translation[1]).strip():
if tidx > bestTranslationIdx:
bestTranslationIdx = tidx;
break;
for tgtlang in targetLanguages:
if bestK == 1:
translation = postprocessor(translationBuffer[tgtlang][bestTranslationIdx][1]) \
if len(translationBuffer[tgtlang]) > bestTranslationIdx \
else ((None,), '');
abstract = str(parsesBlock[bestTranslationIdx][1]);
else:
translation = translationBuffer[tgtlang] \
if len(translationBuffer[tgtlang]) \
else [];
abstract = parsesBlock;
addItem(translationBlocks[tgtlang], translation);
addItem(translationBlocks['abstract'], abstract);
for tgtlang in targetLanguages+['abstract']:
outputFile = os.path.join( props.exp_directory, '%s-%s.%s' %(outputPrefix, tgtlang[-3:] \
if tgtlang!='abstract' \
else 'abstract', props.format) );
logging.info( "Writing translations for %s to %s" %(tgtlang, outputFile) );
with codecs.open(outputFile, 'w', encoding='utf-8') as outputStream:
print(writer(translationBlocks[tgtlang]), file=outputStream);
return;
def cmdLineParser():
argparser = argparse.ArgumentParser(prog='translation_pipeline.py', description='Run the GF translation pipeline on standard test-sets');
argparser.add_argument('-g', '--pgf', dest='pgffile', required=True, help='PGF grammar file to run the pipeline');
argparser.add_argument('-s', '--source', dest='srclang', default='', help='Source language of input sentences');
argparser.add_argument('-t', '--target', dest='tgtlangs', nargs='*', default=[], help='Target languages to linearize (default is all other languages)');
argparser.add_argument('-i', '--input', dest='input', default='', help='input file (default will accept STDIN)');
argparser.add_argument('-e', '--exp', dest='exp_directory', default=os.getcwd(), help='experiement directory to write translation files');
argparser.add_argument('-f', '--format', dest='format', default='txt', choices=['txt', 'sgm'], help='input file format (output files will be written in the same format)');
argparser.add_argument('-p', '--props', dest='propsfile', default='', help='properties file for the translation pipeline (specify the above arguments in a file)');
argparser.add_argument('-K', dest='bestK', type=int, default=1, help='K value for K-best translation');
return argparser;
if __name__ == '__main__':
logging.basicConfig(level='INFO');
pipelineEnv = cmdLineParser().parse_args(sys.argv[1:]);
translation_pipeline(pipelineEnv);