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Diffstat (limited to 'python')
| -rwxr-xr-x | python/src/sa/online_extractor.py | 285 |
1 files changed, 285 insertions, 0 deletions
diff --git a/python/src/sa/online_extractor.py b/python/src/sa/online_extractor.py new file mode 100755 index 00000000..06eb5357 --- /dev/null +++ b/python/src/sa/online_extractor.py @@ -0,0 +1,285 @@ +#!/usr/bin/env python + +import collections, sys + +import cdec.configobj + +CAT = '[X]' # Default non-terminal +MAX_SIZE = 15 # Max span of a grammar rule (source) +MAX_LEN = 5 # Max number of terminals and non-terminals in a rule (source) +MAX_NT = 2 # Max number of non-terminals in a rule +MIN_GAP = 1 # Min number of terminals between non-terminals (source) + +# Spans are _inclusive_ on both ends [i, j] +# TODO: Replace all of this with bit vectors? +def span_check(vec, i, j): + k = i + while k <= j: + if vec[k]: + return False + k += 1 + return True + +def span_flip(vec, i, j): + k = i + while k <= j: + vec[k] = ~vec[k] + k += 1 + +# Next non-terminal +def next_nt(nt): + if not nt: + return 1 + return nt[-1][0] + 1 + +# Create a rule from source, target, non-terminals, and alignments +def form_rule(f_i, e_i, f_span, e_span, nt, al): + + # This could be more efficient but is unlikely to be the bottleneck + + nt_inv = sorted(nt, cmp=lambda x, y: cmp(x[3], y[3])) + + f_sym = f_span[:] + off = f_i + for next_nt in nt: + nt_len = (next_nt[2] - next_nt[1]) + 1 + i = 0 + while i < nt_len: + f_sym.pop(next_nt[1] - off) + i += 1 + f_sym.insert(next_nt[1] - off, '[X,{0}]'.format(next_nt[0])) + off += (nt_len - 1) + + e_sym = e_span[:] + off = e_i + for next_nt in nt_inv: + nt_len = (next_nt[4] - next_nt[3]) + 1 + i = 0 + while i < nt_len: + e_sym.pop(next_nt[3] - off) + i += 1 + e_sym.insert(next_nt[3] - off, '[X,{0}]'.format(next_nt[0])) + off += (nt_len - 1) + + # Adjusting alignment links takes some doing + links = [list(link) for sub in al for link in sub] + links_len = len(links) + nt_len = len(nt) + nt_i = 0 + off = f_i + i = 0 + while i < links_len: + while nt_i < nt_len and links[i][0] > nt[nt_i][1]: + off += (nt[nt_i][2] - nt[nt_i][1]) + nt_i += 1 + links[i][0] -= off + i += 1 + nt_i = 0 + off = e_i + i = 0 + while i < links_len: + while nt_i < nt_len and links[i][1] > nt_inv[nt_i][3]: + off += (nt_inv[nt_i][4] - nt_inv[nt_i][3]) + nt_i += 1 + links[i][1] -= off + i += 1 + a_str = ' '.join('{0}-{1}'.format(i, j) for (i, j) in links) + + return '[X] ||| {0} ||| {1} ||| {2}'.format(' '.join(f_sym), ' '.join(e_sym), a_str) + +class OnlineGrammarExtractor: + + def __init__(self, config=None): + if isinstance(config, str) or isinstance(config, unicode): + if not os.path.exists(config): + raise IOError('cannot read configuration from {0}'.format(config)) + config = cdec.configobj.ConfigObj(config, unrepr=True) + elif not config: + config = collections.defaultdict(lambda: None) + self.category = CAT + self.max_size = MAX_SIZE + self.max_length = config['max_len'] or MAX_LEN + self.max_nonterminals = config['max_nt'] or MAX_NT + self.min_gap_size = MIN_GAP + # Hard coded: require at least one aligned word + # Hard coded: require tight phrases + + # Phrase counts + self.phrases_f = collections.defaultdict(lambda: 0) + self.phrases_e = collections.defaultdict(lambda: 0) + self.phrases_fe = collections.defaultdict(lambda: collections.defaultdict(lambda: 0)) + + # Bilexical counts + self.bilex_f = collections.defaultdict(lambda: 0) + self.bilex_e = collections.defaultdict(lambda: 0) + self.bilex_fe = collections.defaultdict(lambda: collections.defaultdict(lambda: 0)) + + # Aggregate bilexical counts + def aggr_bilex(self, f_words, e_words): + + for e_w in e_words: + self.bilex_e[e_w] += 1 + + for f_w in f_words: + self.bilex_f[f_w] += 1 + for e_w in e_words: + self.bilex_fe[f_w][e_w] += 1 + + # Aggregate stats from a training instance: + # Extract hierarchical phrase pairs + # Update bilexical counts + def add_instance(self, f_words, e_words, alignment): + + # Bilexical counts + self.aggr_bilex(f_words, e_words) + + # Phrase pairs extracted from this instance + phrases = set() + + f_len = len(f_words) + + # Pre-compute alignment info + al = [[] for i in range(f_len)] + al_span = [[f_len + 1, -1] for i in range(f_len)] + for (f, e) in alignment: + al[f].append(e) + al_span[f][0] = min(al_span[f][0], e) + al_span[f][1] = max(al_span[f][1], e) + + # Target side word coverage + # TODO: Does Cython do bit vectors? + cover = [0] * f_len + + # Extract all possible hierarchical phrases starting at a source index + # f_ i and j are current, e_ i and j are previous + def extract(f_i, f_j, e_i, e_j, wc, links, nt, nt_open): + # Phrase extraction limits + if wc > self.max_length or (f_j + 1) >= f_len or \ + (f_j - f_i) + 1 > self.max_size: + return + # Unaligned word + if not al[f_j]: + # Open non-terminal: extend + if nt_open: + nt[-1][2] += 1 + extract(f_i, f_j + 1, e_i, e_j, wc, links, nt, True) + nt[-1][2] -= 1 + # No open non-terminal: extend with word + else: + extract(f_i, f_j + 1, e_i, e_j, wc + 1, links, nt, False) + return + # Aligned word + link_i = al_span[f_j][0] + link_j = al_span[f_j][1] + new_e_i = min(link_i, e_i) + new_e_j = max(link_j, e_j) + # Open non-terminal: close, extract, extend + if nt_open: + # Close non-terminal, checking for collisions + old_last_nt = nt[-1][:] + nt[-1][2] = f_j + if link_i < nt[-1][3]: + if not span_check(cover, link_i, nt[-1][3] - 1): + nt[-1] = old_last_nt + return + span_flip(cover, link_i, nt[-1][3] - 1) + nt[-1][3] = link_i + if link_j > nt[-1][4]: + if not span_check(cover, nt[-1][4] + 1, link_j): + nt[-1] = old_last_nt + return + span_flip(cover, nt[-1][4] + 1, link_j) + nt[-1][4] = link_j + phrases.add(form_rule(f_i, new_e_i, f_words[f_i:f_j + 1], e_words[new_e_i:new_e_j + 1], nt, links)) + extract(f_i, f_j + 1, new_e_i, new_e_j, wc, links, nt, False) + nt[-1] = old_last_nt + if link_i < nt[-1][3]: + span_flip(cover, link_i, nt[-1][3] - 1) + if link_j > nt[-1][4]: + span_flip(cover, nt[-1][4] + 1, link_j) + return + # No open non-terminal + # Extract, extend with word + collision = False + for link in al[f_j]: + if cover[link]: + collision = True + # Collisions block extraction and extension, but may be okay for + # continuing non-terminals + if not collision: + plus_links = [] + for link in al[f_j]: + plus_links.append((f_j, link)) + cover[link] = ~cover[link] + links.append(plus_links) + phrases.add(form_rule(f_i, new_e_i, f_words[f_i:f_j + 1], e_words[new_e_i:new_e_j + 1], nt, links)) + extract(f_i, f_j + 1, new_e_i, new_e_j, wc + 1, links, nt, False) + links.pop() + for link in al[f_j]: + cover[link] = ~cover[link] + # Try to add a word to a (closed) non-terminal, extract, extend + if nt and nt[-1][2] == f_j - 1: + # Add to non-terminal, checking for collisions + old_last_nt = nt[-1][:] + nt[-1][2] = f_j + if link_i < nt[-1][3]: + if not span_check(cover, link_i, nt[-1][3] - 1): + nt[-1] = old_last_nt + return + span_flip(cover, link_i, nt[-1][3] - 1) + nt[-1][3] = link_i + if link_j > nt[-1][4]: + if not span_check(cover, nt[-1][4] + 1, link_j): + nt[-1] = old_last_nt + return + span_flip(cover, nt[-1][4] + 1, link_j) + nt[-1][4] = link_j + # Require at least one word in phrase + if links: + phrases.add(form_rule(f_i, new_e_i, f_words[f_i:f_j + 1], e_words[new_e_i:new_e_j + 1], nt, links)) + extract(f_i, f_j + 1, new_e_i, new_e_j, wc, links, nt, False) + nt[-1] = old_last_nt + if new_e_i < nt[-1][3]: + span_flip(cover, link_i, nt[-1][3] - 1) + if link_j > nt[-1][4]: + span_flip(cover, nt[-1][4] + 1, link_j) + # Try to start a new non-terminal, extract, extend + if (not nt or f_j - nt[-1][2] > 1) and len(nt) < self.max_nonterminals: + # Check for collisions + if not span_check(cover, link_i, link_j): + return + span_flip(cover, link_i, link_j) + nt.append([next_nt(nt), f_j, f_j, link_i, link_j]) + # Require at least one word in phrase + if links: + phrases.add(form_rule(f_i, new_e_i, f_words[f_i:f_j + 1], e_words[new_e_i:new_e_j + 1], nt, links)) + extract(f_i, f_j + 1, new_e_i, new_e_j, wc, links, nt, False) + nt.pop() + span_flip(cover, link_i, link_j) + # TODO: try adding NT to start, end, both + # check: one aligned word on boundary that is not part of a NT + + # Try to extract phrases from every f index + f_i = 0 + while f_i < f_len: + # Skip if phrases won't be tight on left side + if not al[f_i]: + f_i += 1 + continue + extract(f_i, f_i, f_len + 1, -1, 1, [], [], False) + f_i += 1 + + for rule in sorted(phrases): + print rule + +def main(argv): + + extractor = OnlineGrammarExtractor() + + for line in sys.stdin: + f_words, e_words, a_str = (x.split() for x in line.split('|||')) + alignment = sorted(tuple(int(y) for y in x.split('-')) for x in a_str) + extractor.add_instance(f_words, e_words, alignment) + +if __name__ == '__main__': + main(sys.argv)
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