def test_oracle_connects_france_and_paris(): query = 'what are the major cities in france?' target = [u'Paris'] dataset = [(query, target)] oracle = OracleSystem(dataset) result = oracle.execute(query) oracle.connector.related.save_cache() assert list(result) == target
def test_oracle_finds_chinese_language(): query = "what is the official language of china 2010?" target = [u"Chinese language"] dataset = [(query, target)] oracle = OracleSystem(dataset) result = oracle.execute(query) oracle.connector.related.save_cache() assert len(set(result) & set(target)) > 0
def test_timeout(): query, target = "what characters does trey parker voice?", [u"Eric Cartman", u"Fosse McDonald"] dataset = [(query, target)] oracle = OracleSystem(dataset) result = oracle.execute(query) oracle.connector.related.save_cache() assert len(set(result) & set(target)) > 0
def test_oracle_finds_chers_son(): query, target = "what is cher's son's name?", [u"Elijah Blue Allman", u"Chaz Bono"] dataset = [(query, target)] oracle = OracleSystem(dataset) result = oracle.execute(query) oracle.connector.related.save_cache() assert len(set(result) & set(target)) > 0
def test_oracle_finds_jamaican_dollar(): query = "what kind of money should i take to jamaica?" target = [u"Jamaican dollar"] dataset = [(query, target)] oracle = OracleSystem(dataset) result = oracle.execute(query) oracle.connector.related.save_cache() assert list(result) == target
def test_oracle_finds_ishmael(): query = "who was ishmael's mom?" target = [u'Hagar'] dataset = [(query, target)] oracle = OracleSystem(dataset) result = oracle.execute(query) oracle.connector.related.save_cache() assert len(set(result) & set(target)) > 0
def test_oracle_finds_time_zone(): query = "what time zone am i in cleveland ohio?" target = [u"Eastern Time Zone"] dataset = [(query, target)] oracle = OracleSystem(dataset) result = oracle.execute(query) oracle.connector.related.save_cache() assert len(set(result) & set(target)) > 0
def test_expression(): query, target = "what character did natalie portman play in star wars?", [u"Padm\u00e9 Amidala"] dataset = [(query, target)] oracle = OracleSystem(dataset) result = oracle.execute(query) oracle.connector.related.save_cache() print result assert result == set(target)
def test_oracle_finds_chers_son(): query, target = "what is cher's son's name?", [ u"Elijah Blue Allman", u"Chaz Bono" ] dataset = [(query, target)] oracle = OracleSystem(dataset) result = oracle.execute(query) oracle.connector.related.save_cache() assert len(set(result) & set(target)) > 0
def test_timeout(): query, target = "what characters does trey parker voice?", [ u"Eric Cartman", u"Fosse McDonald" ] dataset = [(query, target)] oracle = OracleSystem(dataset) result = oracle.execute(query) oracle.connector.related.save_cache() assert len(set(result) & set(target)) > 0
def test_expression(): query, target = "what character did natalie portman play in star wars?", [ u"Padm\u00e9 Amidala" ] dataset = [(query, target)] oracle = OracleSystem(dataset) result = oracle.execute(query) oracle.connector.related.save_cache() print result assert result == set(target)
def get_cache_oracle_data(dataset): oracle = OracleSystem(dataset) i = 0 for query, target_entities in dataset: results, expressions = oracle.get_best_results_and_expressions(query) yield { 'query': query, 'results': results, 'expressions': expressions, 'target': target_entities, } i += 1 logger.info("Completed: %d", i) if i % 10 == 0: logger.info("Saving caches") oracle.connector.save_cache() logger.info("Saving complete")
from fbsearch.dataset import get_dataset from fbsearch import settings from random import Random # from log import logger random = Random(1) with open('nones.json') as nones_file: dataset = [json.loads(row) for row in nones_file] # nones = set(open('nones.txt').read().split('\n')) # dataset_file = open(settings.DATASET_PATH) # dataset = get_dataset(dataset_file) # dataset = [row for row in dataset if row[0] in nones] print dataset # logger.info("Training") # train_set = dataset[:2500] # system = TensorSystem(CachedOracleSystem) # system.train(train_set) dataset = dataset[:100] system = OracleSystem(dataset) #logger.info("Testing") # test_set = dataset[2500:] results = get_target_and_predicted_values(dataset, system) save(results, 'nones-output.json') analyse('nones-output.json')