Rooba
/
spaCy
mirror of https://github.com/explosion/spaCy.git
1
1
Fork 0
Code Issues Packages Projects Releases Wiki Activity

* Wire up beam-width command line argument

This commit is contained in:
Matthew Honnibal 2015-06-02 00:54:12 +02:00
parent 7c29362d60
commit a3de20118e
1 changed files with 5 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

8
bin/parser/train.py
View File

@ -159,7 +159,8 @@ def train(Language, gold_tuples, model_dir, n_iter=15, feat_set=u'basic',
setup_model_dir(sorted(POS_TAGS.keys()), POS_TAGS, POS_TEMPLATES, pos_model_dir) setup_model_dir(sorted(POS_TAGS.keys()), POS_TAGS, POS_TEMPLATES, pos_model_dir)
Config.write(dep_model_dir, 'config', features=feat_set, seed=seed, Config.write(dep_model_dir, 'config', features=feat_set, seed=seed,
labels=Language.ParserTransitionSystem.get_labels(gold_tuples)) labels=Language.ParserTransitionSystem.get_labels(gold_tuples),
beam_width=16)
Config.write(ner_model_dir, 'config', features='ner', seed=seed, Config.write(ner_model_dir, 'config', features='ner', seed=seed,
labels=Language.EntityTransitionSystem.get_labels(gold_tuples)) labels=Language.EntityTransitionSystem.get_labels(gold_tuples))
@ -248,11 +249,12 @@ def write_parses(Language, dev_loc, model_dir, out_loc):
out_loc=("Out location", "option", "o", str), out_loc=("Out location", "option", "o", str),
n_sents=("Number of training sentences", "option", "n", int), n_sents=("Number of training sentences", "option", "n", int),
n_iter=("Number of training iterations", "option", "i", int), n_iter=("Number of training iterations", "option", "i", int),
beam_width=("Number of candidates to maintain in the beam", "option", "k", int),
verbose=("Verbose error reporting", "flag", "v", bool), verbose=("Verbose error reporting", "flag", "v", bool),
debug=("Debug mode", "flag", "d", bool) debug=("Debug mode", "flag", "d", bool)
) )
def main(train_loc, dev_loc, model_dir, n_sents=0, n_iter=15, out_loc="", verbose=False, def main(train_loc, dev_loc, model_dir, n_sents=0, n_iter=15, out_loc="", verbose=False,
debug=False, corruption_level=0.0, gold_preproc=False): debug=False, corruption_level=0.0, gold_preproc=False, beam_width=1):
gold_train = list(read_json_file(train_loc)) gold_train = list(read_json_file(train_loc))
#taggings = get_train_tags(English, model_dir, gold_train, gold_preproc) #taggings = get_train_tags(English, model_dir, gold_train, gold_preproc)
taggings = None taggings = None
@ -260,7 +262,7 @@ def main(train_loc, dev_loc, model_dir, n_sents=0, n_iter=15, out_loc="", verbos
feat_set='basic' if not debug else 'debug', feat_set='basic' if not debug else 'debug',
gold_preproc=gold_preproc, n_sents=n_sents, gold_preproc=gold_preproc, n_sents=n_sents,
corruption_level=corruption_level, n_iter=n_iter, corruption_level=corruption_level, n_iter=n_iter,
train_tags=taggings) train_tags=taggings, beam_width=beam_width)
if out_loc: if out_loc:
write_parses(English, dev_loc, model_dir, out_loc) write_parses(English, dev_loc, model_dir, out_loc)
scorer = evaluate(English, list(read_json_file(dev_loc)), scorer = evaluate(English, list(read_json_file(dev_loc)),