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authorVictor Chahuneau <vchahune@cs.cmu.edu>2012-07-27 01:16:03 -0400
committerVictor Chahuneau <vchahune@cs.cmu.edu>2012-07-27 01:16:03 -0400
commitb2a8bccb2bd713d9ec081cf3dad0162c2cb492d8 (patch)
treec661044fd2a3943cf2ad12109b916fd7b56a519e /python/cdec/sa
parent148b1168c2b07abf0c7757a31141377c28ec3d91 (diff)
[python] Fork of the suffix-array extractor with surface improvements
Available as the cdec.sa module, with commande-line helpers: python -m cdec.sa.compile -f ... -e ... -a ... -o sa-out/ -c extract.ini python -m cdec.sa.extract -c extract.ini -g grammars-out/ < input.txt > input.sgml + renamed cdec.scfg -> cdec.sa + Python README
Diffstat (limited to 'python/cdec/sa')
-rw-r--r--python/cdec/sa/__init__.py4
-rw-r--r--python/cdec/sa/compile.py94
-rw-r--r--python/cdec/sa/extract.py32
-rw-r--r--python/cdec/sa/extractor.py73
-rw-r--r--python/cdec/sa/features.py60
5 files changed, 263 insertions, 0 deletions
diff --git a/python/cdec/sa/__init__.py b/python/cdec/sa/__init__.py
new file mode 100644
index 00000000..ddefa280
--- /dev/null
+++ b/python/cdec/sa/__init__.py
@@ -0,0 +1,4 @@
+from _cdec_sa import sym_tostring, sym_isvar, sym_fromstring,\
+ SuffixArray, DataArray, LCP, Precomputation, Alignment, BiLex,\
+ HieroCachingRuleFactory, Sampler
+from extractor import GrammarExtractor
diff --git a/python/cdec/sa/compile.py b/python/cdec/sa/compile.py
new file mode 100644
index 00000000..061cdab2
--- /dev/null
+++ b/python/cdec/sa/compile.py
@@ -0,0 +1,94 @@
+#!/usr/bin/env python
+import argparse
+import os
+import logging
+import configobj
+import cdec.sa
+
+MAX_PHRASE_LENGTH = 4
+def precompute(f_sa, max_len, max_nt, max_size, min_gap, rank1, rank2):
+ lcp = cdec.sa.LCP(f_sa)
+ stats = sorted(lcp.compute_stats(MAX_PHRASE_LENGTH), reverse=True)
+ precomp = cdec.sa.Precomputation(from_stats=stats,
+ fsarray=f_sa,
+ precompute_rank=rank1,
+ precompute_secondary_rank=rank2,
+ max_length=max_len,
+ max_nonterminals=max_nt,
+ train_max_initial_size=max_size,
+ train_min_gap_size=min_gap)
+ return precomp
+
+def main():
+ logging.basicConfig(level=logging.INFO)
+ logger = logging.getLogger('cdec.sa.compile')
+ parser = argparse.ArgumentParser(description='Compile a corpus into a suffix array.')
+ parser.add_argument('--maxnt', '-n', type=int, default=2,
+ help='Maximum number of non-terminal symbols')
+ parser.add_argument('--maxlen', '-l', type=int, default=5,
+ help='Maximum number of terminals')
+ parser.add_argument('--maxsize', '-s', type=int, default=15,
+ help='Maximum rule span')
+ parser.add_argument('--mingap', '-g', type=int, default=1,
+ help='Minimum gap size')
+ parser.add_argument('--rank1', '-r1', type=int, default=100,
+ help='Number of pre-computed frequent patterns')
+ parser.add_argument('--rank2', '-r2', type=int, default=10,
+ help='Number of pre-computed super-frequent patterns)')
+ parser.add_argument('-c', '--config', default='/dev/stdout',
+ help='Output configuration')
+ parser.add_argument('-o', '--output', required=True,
+ help='Output path')
+ parser.add_argument('-f', '--source', required=True,
+ help='Source language corpus')
+ parser.add_argument('-e', '--target', required=True,
+ help='Target language corpus')
+ parser.add_argument('-a', '--alignment', required=True,
+ help='Bitext word alignment')
+ args = parser.parse_args()
+
+ param_names = ("max_len", "max_nt", "max_size", "min_gap", "rank1", "rank2")
+ params = (args.maxlen, args.maxnt, args.maxsize, args.mingap, args.rank1, args.rank2)
+
+ if not os.path.exists(args.output):
+ os.mkdir(args.output)
+
+ f_sa_bin = os.path.join(args.output, 'f.sa.bin')
+ e_bin = os.path.join(args.output, 'e.bin')
+ precomp_file = 'precomp.{0}.{1}.{2}.{3}.{4}.{5}.bin'.format(*params)
+ precomp_bin = os.path.join(args.output, precomp_file)
+ a_bin = os.path.join(args.output, 'a.bin')
+ lex_bin = os.path.join(args.output, 'lex.bin')
+
+ logger.info('Compiling source suffix array')
+ f_sa = cdec.sa.SuffixArray(from_text=args.source)
+ f_sa.write_binary(f_sa_bin)
+
+ logger.info('Compiling target data array')
+ e = cdec.sa.DataArray(from_text=args.target)
+ e.write_binary(e_bin)
+
+ logger.info('Precomputing frequent phrases')
+ precompute(f_sa, *params).write_binary(precomp_bin)
+
+ logger.info('Compiling alignment')
+ a = cdec.sa.Alignment(from_text=args.alignment)
+ a.write_binary(a_bin)
+
+ logger.info('Compiling bilexical dictionary')
+ lex = cdec.sa.BiLex(from_data=True, alignment=a, earray=e, fsarray=f_sa)
+ lex.write_binary(lex_bin)
+
+ # Write configuration
+ config = configobj.ConfigObj(args.config, unrepr=True)
+ config['f_sa_file'] = f_sa_bin
+ config['e_file'] = e_bin
+ config['a_file'] = a_bin
+ config['lex_file'] = lex_bin
+ config['precompute_file'] = precomp_bin
+ for name, value in zip(param_names, params):
+ config[name] = value
+ config.write()
+
+if __name__ == '__main__':
+ main()
diff --git a/python/cdec/sa/extract.py b/python/cdec/sa/extract.py
new file mode 100644
index 00000000..c6da5e9d
--- /dev/null
+++ b/python/cdec/sa/extract.py
@@ -0,0 +1,32 @@
+#!/usr/bin/env python
+import sys
+import os
+import argparse
+import logging
+import configobj
+import cdec.sa
+
+def main():
+ 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', required=True,
+ help='Grammar output path')
+ args = parser.parse_args()
+
+ if not os.path.exists(args.grammars):
+ os.mkdir(args.grammars)
+
+ extractor = cdec.sa.GrammarExtractor(configobj.ConfigObj(args.config, unrepr=True))
+ for i, sentence in enumerate(sys.stdin):
+ sentence = sentence[:-1]
+ grammar_file = os.path.join(args.grammars, 'grammar.{0}'.format(i))
+ with open(grammar_file, 'w') as output:
+ for rule in extractor.grammar(sentence):
+ output.write(str(rule)+'\n')
+ grammar_file = os.path.abspath(grammar_file)
+ print('<seg grammar="{0}">{1}</seg>'.format(grammar_file, sentence))
+
+if __name__ == '__main__':
+ main()
diff --git a/python/cdec/sa/extractor.py b/python/cdec/sa/extractor.py
new file mode 100644
index 00000000..c97b3c6f
--- /dev/null
+++ b/python/cdec/sa/extractor.py
@@ -0,0 +1,73 @@
+from itertools import chain
+from cdec.sa.features import EgivenFCoherent, SampleCountF, CountEF,\
+ MaxLexEgivenF, MaxLexFgivenE, IsSingletonF, IsSingletonFE
+import cdec.sa
+
+# maximum span of a grammar rule in TEST DATA
+MAX_INITIAL_SIZE = 15
+
+class GrammarExtractor:
+ def __init__(self, config):
+ # TODO if str, read config
+ alignment = cdec.sa.Alignment(from_binary=config['a_file'])
+ self.factory = cdec.sa.HieroCachingRuleFactory(
+ # compiled alignment object (REQUIRED)
+ alignment,
+ # name of generic nonterminal used by Hiero
+ category="[X]",
+ # maximum number of contiguous chunks of terminal symbols in RHS of a rule
+ max_chunks=config['max_nt']+1,
+ # maximum span of a grammar rule in TEST DATA
+ max_initial_size=MAX_INITIAL_SIZE,
+ # maximum number of symbols (both T and NT) allowed in a rule
+ max_length=config['max_len'],
+ # maximum number of nonterminals allowed in a rule (set >2 at your own risk)
+ max_nonterminals=config['max_nt'],
+ # maximum number of contiguous chunks of terminal symbols
+ # in target-side RHS of a rule.
+ max_target_chunks=config['max_nt']+1,
+ # maximum number of target side symbols (both T and NT) allowed in a rule.
+ max_target_length=MAX_INITIAL_SIZE,
+ # minimum span of a nonterminal in the RHS of a rule in TEST DATA
+ min_gap_size=1,
+ # filename of file containing precomputed collocations
+ precompute_file=config['precompute_file'],
+ # maximum frequency rank of patterns used to compute triples (< 20)
+ precompute_secondary_rank=config['rank2'],
+ # maximum frequency rank of patterns used to compute collocations (< 300)
+ precompute_rank=config['rank1'],
+ # require extracted rules to have at least one aligned word
+ require_aligned_terminal=True,
+ # require each contiguous chunk of extracted rules
+ # to have at least one aligned word
+ require_aligned_chunks=False,
+ # maximum span of a grammar rule extracted from TRAINING DATA
+ train_max_initial_size=config['max_size'],
+ # minimum span of an RHS nonterminal in a rule extracted from TRAINING DATA
+ train_min_gap_size=config['min_gap'],
+ # True if phrases should be tight, False otherwise (better but slower)
+ tight_phrases=True,
+ )
+
+ # lexical weighting tables
+ tt = cdec.sa.BiLex(from_binary=config['lex_file'])
+
+ self.models = (EgivenFCoherent, SampleCountF, CountEF,
+ MaxLexFgivenE(tt), MaxLexEgivenF(tt), IsSingletonF, IsSingletonFE)
+
+ fsarray = cdec.sa.SuffixArray(from_binary=config['f_sa_file'])
+ edarray = cdec.sa.DataArray(from_binary=config['e_file'])
+
+ # lower=faster, higher=better; improvements level off above 200-300 range,
+ # -1 = don't sample, use all data (VERY SLOW!)
+ sampler = cdec.sa.Sampler(300, fsarray)
+
+ self.factory.configure(fsarray, edarray, sampler)
+
+ def grammar(self, sentence):
+ if isinstance(sentence, unicode):
+ sentence = sentence.encode('utf8')
+ cnet = chain(('<s>',), sentence.split(), ('</s>',))
+ cnet = (cdec.sa.sym_fromstring(word, terminal=True) for word in cnet)
+ cnet = tuple(((word, None, 1), ) for word in cnet)
+ return self.factory.input(cnet, self.models)
diff --git a/python/cdec/sa/features.py b/python/cdec/sa/features.py
new file mode 100644
index 00000000..8d35d8e6
--- /dev/null
+++ b/python/cdec/sa/features.py
@@ -0,0 +1,60 @@
+from __future__ import division
+import math
+import cdec.sa
+
+MAXSCORE = 99
+
+def EgivenF(fphrase, ephrase, paircount, fcount, fsample_count): # p(e|f)
+ return -math.log10(paircount/fcount)
+
+def CountEF(fphrase, ephrase, paircount, fcount, fsample_count):
+ return math.log10(1 + paircount)
+
+def SampleCountF(fphrase, ephrase, paircount, fcount, fsample_count):
+ return math.log10(1 + fsample_count)
+
+def EgivenFCoherent(fphrase, ephrase, paircount, fcount, fsample_count):
+ prob = paircount/fsample_count
+ return -math.log10(prob) if prob > 0 else MAXSCORE
+
+def CoherenceProb(fphrase, ephrase, paircount, fcount, fsample_count):
+ return -math.log10(fcount/fsample_count)
+
+def MaxLexEgivenF(ttable):
+ def feature(fphrase, ephrase, paircount, fcount, fsample_count):
+ fwords = [cdec.sa.sym_tostring(w) for w in fphrase if not cdec.sa.sym_isvar(w)]
+ fwords.append('NULL')
+ ewords = (cdec.sa.sym_tostring(w) for w in ephrase if not cdec.sa.sym_isvar(w))
+ def score():
+ for e in ewords:
+ maxScore = max(ttable.get_score(f, e, 0) for f in fwords)
+ yield -math.log10(maxScore) if maxScore > 0 else MAXSCORE
+ return sum(score())
+ return feature
+
+def MaxLexFgivenE(ttable):
+ def feature(fphrase, ephrase, paircount, fcount, fsample_count):
+ fwords = (cdec.sa.sym_tostring(w) for w in fphrase if not cdec.sa.sym_isvar(w))
+ ewords = [cdec.sa.sym_tostring(w) for w in ephrase if not cdec.sa.sym_isvar(w)]
+ ewords.append('NULL')
+ def score():
+ for f in fwords:
+ maxScore = max(ttable.get_score(f, e, 1) for e in ewords)
+ yield -math.log10(maxScore) if maxScore > 0 else MAXSCORE
+ return sum(score())
+ return feature
+
+def IsSingletonF(fphrase, ephrase, paircount, fcount, fsample_count):
+ return (fcount == 1)
+
+def IsSingletonFE(fphrase, ephrase, paircount, fcount, fsample_count):
+ return (paircount == 1)
+
+def IsNotSingletonF(fphrase, ephrase, paircount, fcount, fsample_count):
+ return (fcount > 1)
+
+def IsNotSingletonFE(fphrase, ephrase, paircount, fcount, fsample_count):
+ return (paircount > 1)
+
+def IsFEGreaterThanZero(fphrase, ephrase, paircount, fcount, fsample_count):
+ return (paircount > 0.01)