def start(self):
"""
Prepares the internal information to start predicting.
"""
self.rule_regexes = [
(compile_rule(rule, self.relation), rule.answer) for rule in self.rules
]
def run_from_command_line():
opts = docopt(__doc__, version=iepy.__version__)
relation_name = opts.get("<relation>")
limit = opts.get("--limit")
rule_name = opts.get("--rule")
shuffle = opts.get("--shuffle")
create_evidences = opts.get("--create-evidences")
if limit is None:
limit = -1
try:
limit = int(limit)
except ValueError:
logging.error("Invalid limit value, it must be a number")
sys.exit(1)
try:
relation = models.Relation.objects.get(name=relation_name)
except ObjectDoesNotExist:
logging.error("Relation {!r} not found".format(relation_name))
sys.exit(1)
# Load rules
rules = get_rules(rule_name)
rule_regexes = [(rule.__name__, compile_rule(rule, relation), rule.answer)
for rule in rules]
# Load evidences
if EvidenceCandidate.objects.all().count() == 0:
create_evidences = True
evidences = CandidateEvidenceManager.candidates_for_relation(
relation, create_evidences, seg_limit=limit, shuffle_segs=shuffle)
conflict_solver = CandidateEvidenceManager.conflict_resolution_newest_wins
answers = CandidateEvidenceManager.labels_for(relation, evidences,
conflict_solver)
run_tests(rule_regexes, evidences, answers)
def inner(evidence):
regex = compile_rule(rule_feature, relation)
tokens_to_match = generate_tokens_to_match(evidence)
return int(bool(refo.match(regex, tokens_to_match)))
def inner(evidence):
regex = compile_rule(rule_feature, relation)
tokens_to_match = generate_tokens_to_match(evidence)
return int(bool(refo.match(regex, tokens_to_match)))
