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Diffstat (limited to 'python/cdec/sa/extractor.py')
| -rw-r--r-- | python/cdec/sa/extractor.py | 78 |
1 files changed, 0 insertions, 78 deletions
diff --git a/python/cdec/sa/extractor.py b/python/cdec/sa/extractor.py deleted file mode 100644 index bb912e16..00000000 --- a/python/cdec/sa/extractor.py +++ /dev/null @@ -1,78 +0,0 @@ -from itertools import chain -import os -import cdec.configobj -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): - 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) - 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) |