From 3f2cc751d1f2655aa0ff14ca735da648899edc40 Mon Sep 17 00:00:00 2001 From: Victor Chahuneau Date: Fri, 10 Aug 2012 19:03:38 -0400 Subject: [python] Examples directory including Rampion --- python/examples/rampion.py | 77 ++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 77 insertions(+) create mode 100644 python/examples/rampion.py (limited to 'python/examples/rampion.py') diff --git a/python/examples/rampion.py b/python/examples/rampion.py new file mode 100644 index 00000000..66d89a61 --- /dev/null +++ b/python/examples/rampion.py @@ -0,0 +1,77 @@ +import argparse +import logging +from itertools import izip +import cdec, cdec.score + +def evaluate(hyp, ref): + """ Compute BLEU score for a set of hypotheses+references """ + return sum(cdec.score.BLEU(r).evaluate(h) for h, r in izip(hyp, ref)).score + +T1, T2, T3 = 5, 10, 20 # number of iterations (global, CCCP, SSD) +K = 500 # k-best list size +C = 1 # regularization coefficient +eta = 1e-4 # step size +cost = lambda c: 10 * (1 - c.score) # cost definition + +def rampion(decoder, sources, references): + # Empty k-best lists + cs = [cdec.score.BLEU(refs).candidate_set() for refs in references] + # Weight vector -> sparse + w = decoder.weights.tosparse() + w0 = w.copy() + + N = len(sources) + for t in range(T1): + logging.info('Iteration {0}: translating...'.format(t+1)) + # Get the hypergraphs and extend the k-best lists + hgs = [] + for src, candidates in izip(sources, cs): + hg = decoder.translate(src) + hgs.append(hg) + candidates.add_kbest(hg, K) + # BLEU score for the previous iteration + score = evaluate((hg.viterbi() for hg in hgs), references) + logging.info('BLEU: {:.2f}'.format(100 * score)) + logging.info('Optimizing...') + for _ in range(T2): + # y_i^+, h_i^+; i=1..N + plus = [max(candidates, key=lambda c: w.dot(c.fmap) - cost(c)).fmap + for candidates in cs] + for _ in range(T3): + for fp, candidates in izip(plus, cs): + # y^-, h^- + fm = max(candidates, key=lambda c: w.dot(c.fmap) + cost(c)).fmap + # update weights (line 11-12) + w += eta * ((fp - fm) - C/N * (w - w0)) + logging.info('Updated weight vector: {0}'.format(dict(w))) + # Update decoder weights + for fname, fval in w: + decoder.weights[fname] = fval + +def main(): + logging.basicConfig(level=logging.INFO, format='%(message)s') + + parser = argparse.ArgumentParser() + parser.add_argument('-c', '--config', help='cdec config', required=True) + parser.add_argument('-w', '--weights', help='initial weights', required=True) + parser.add_argument('-r', '--reference', help='reference file', required=True) + parser.add_argument('-s', '--source', help='source file', required=True) + args = parser.parse_args() + + with open(args.config) as fp: + config = fp.read() + + decoder = cdec.Decoder(config) + decoder.read_weights(args.weights) + with open(args.reference) as fp: + references = fp.readlines() + with open(args.source) as fp: + sources = fp.readlines() + assert len(references) == len(sources) + rampion(decoder, sources, references) + + for fname, fval in sorted(dict(decoder.weights).iteritems()): + print('{0}\t{1}'.format(fname, fval)) + +if __name__ == '__main__': + main() -- cgit v1.2.3 From 38c38f707e58960f80a8dc216673ae0bb0796ade Mon Sep 17 00:00:00 2001 From: Victor Chahuneau Date: Tue, 4 Sep 2012 10:21:25 +0100 Subject: Multi-processing grammar extraction + various surface fixes --- .gitignore | 1 + python/examples/rampion.py | 11 +++++------ python/pkg/cdec/sa/extract.py | 45 ++++++++++++++++++++++++++++++++----------- python/src/hypergraph.pxd | 2 +- 4 files changed, 41 insertions(+), 18 deletions(-) (limited to 'python/examples/rampion.py') diff --git a/.gitignore b/.gitignore index 6f674f35..aa2e64eb 100644 --- a/.gitignore +++ b/.gitignore @@ -117,6 +117,7 @@ phrasinator/gibbs_train_plm_notables previous.sh pro-train/mr_pro_map pro-train/mr_pro_reduce +python/setup.py rampion/rampion_cccp rst_parser/mst_train rst_parser/random_tree diff --git a/python/examples/rampion.py b/python/examples/rampion.py index 66d89a61..30244cf7 100644 --- a/python/examples/rampion.py +++ b/python/examples/rampion.py @@ -15,7 +15,7 @@ cost = lambda c: 10 * (1 - c.score) # cost definition def rampion(decoder, sources, references): # Empty k-best lists - cs = [cdec.score.BLEU(refs).candidate_set() for refs in references] + candidate_sets = [cdec.score.BLEU(refs).candidate_set() for refs in references] # Weight vector -> sparse w = decoder.weights.tosparse() w0 = w.copy() @@ -25,7 +25,7 @@ def rampion(decoder, sources, references): logging.info('Iteration {0}: translating...'.format(t+1)) # Get the hypergraphs and extend the k-best lists hgs = [] - for src, candidates in izip(sources, cs): + for src, candidates in izip(sources, candidate_sets): hg = decoder.translate(src) hgs.append(hg) candidates.add_kbest(hg, K) @@ -36,17 +36,16 @@ def rampion(decoder, sources, references): for _ in range(T2): # y_i^+, h_i^+; i=1..N plus = [max(candidates, key=lambda c: w.dot(c.fmap) - cost(c)).fmap - for candidates in cs] + for candidates in candidate_sets] for _ in range(T3): - for fp, candidates in izip(plus, cs): + for fp, candidates in izip(plus, candidate_sets): # y^-, h^- fm = max(candidates, key=lambda c: w.dot(c.fmap) + cost(c)).fmap # update weights (line 11-12) w += eta * ((fp - fm) - C/N * (w - w0)) logging.info('Updated weight vector: {0}'.format(dict(w))) # Update decoder weights - for fname, fval in w: - decoder.weights[fname] = fval + decoder.weights = w def main(): logging.basicConfig(level=logging.INFO, format='%(message)s') diff --git a/python/pkg/cdec/sa/extract.py b/python/pkg/cdec/sa/extract.py index 875bf42e..39eac824 100644 --- a/python/pkg/cdec/sa/extract.py +++ b/python/pkg/cdec/sa/extract.py @@ -3,29 +3,52 @@ import sys import os import argparse import logging +import multiprocessing as mp +import signal import cdec.sa +extractor, prefix = None, None +def make_extractor(config, grammars): + global extractor, prefix + signal.signal(signal.SIGINT, signal.SIG_IGN) # Let parent process catch Ctrl+C + extractor = cdec.sa.GrammarExtractor(config) + prefix = grammars + +def extract(inp): + global extractor, prefix + i, sentence = inp + sentence = sentence[:-1] + grammar_file = os.path.join(prefix, '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) + return '{2}'.format(grammar_file, i, sentence) + + 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') + help='extractor configuration') parser.add_argument('-g', '--grammars', required=True, - help='Grammar output path') + 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') args = parser.parse_args() if not os.path.exists(args.grammars): os.mkdir(args.grammars) - extractor = cdec.sa.GrammarExtractor(args.config) - 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('{2}'.format(grammar_file, i, sentence)) + logging.info('Starting %d workers; chunk size: %d', args.jobs, args.chunksize) + pool = mp.Pool(args.jobs, make_extractor, (args.config, args.grammars)) + try: + for output in pool.imap(extract, enumerate(sys.stdin), args.chunksize): + print(output) + except KeyboardInterrupt: + pool.terminate() if __name__ == '__main__': main() diff --git a/python/src/hypergraph.pxd b/python/src/hypergraph.pxd index acab7244..dd3d39cc 100644 --- a/python/src/hypergraph.pxd +++ b/python/src/hypergraph.pxd @@ -38,7 +38,7 @@ cdef extern from "decoder/hg.h": int GoalNode() double NumberOfPaths() void Reweight(vector[weight_t]& weights) nogil - void Reweight(FastSparseVector& weights) nogil + void Reweight(FastSparseVector[weight_t]& weights) nogil bint PruneInsideOutside(double beam_alpha, double density, EdgeMask* preserve_mask, -- cgit v1.2.3