def main():
buzzer = RNNBuzzer()
# setup questions
questions = list(QuestionDatabase().all_questions().values())
dev_questions = [x for x in questions if x.fold == 'dev']
# setup machine agent
gspec = AbstractGuesser.list_enabled_guessers()[0]
guesser_dir = AbstractGuesser.output_path(gspec.guesser_module,
gspec.guesser_class, '')
guesser = ElasticSearchWikidataGuesser.load(guesser_dir)
guesser = ESGuesserWrapper(guesser)
machine_agent = GuesserBuzzerAgent(guesser, buzzer)
# setup human agent
human_agent = HumanAgent()
# setup hook
hooks = []
hooks.append(hook.NotifyBuzzingHook)
hooks.append(hook.GameInterfaceHook)
hooks.append(hook.VisualizeGuesserBuzzerHook(machine_agent))
hooks.append(hook.HighlightHook)
# setup game
game = Game(dev_questions, [human_agent, machine_agent], hooks)
game.run(10)
def test():
gspec = AbstractGuesser.list_enabled_guessers()[0]
guesser_dir = AbstractGuesser.output_path(gspec.guesser_module,
gspec.guesser_class, '')
guesser = ElasticSearchWikidataGuesser.load(guesser_dir)
torch.cuda.set_device(0)
predictor = Predictor()
predictor.cuda()
dataset = BonusPairsDataset()
examples = [x for x in dataset.examples if x['start'] != -1]
guesses = []
for example in tqdm(examples):
document = example['content']
question = example['query']
answer = example['answer']
predictions = predictor.predict(document, question, top_n=1)
prediction = predictions[0][0]
gs = guesser.guess_single(example['query'])
gs = sorted(gs.items(), key=lambda x: x[1])[::-1]
guess = gs[0][0].replace('_', ' ')
guesses.append((prediction, guess, example['answer']))
with open('results.pkl', 'wb') as f:
pickle.dump(guesses, f)
def __init__(self, buzzer_model_dir='data/neo_0.npz'):
gspec = AbstractGuesser.list_enabled_guessers()[0]
guesser_dir = 'data/guesser'
self.guesser = ElasticSearchWikidataGuesser.load(guesser_dir)
if chainer.cuda.available:
self.buzzer = RNNBuzzer(model_dir=buzzer_model_dir,
word_skip=conf['buzzer_word_skip'])
else:
self.buzzer = StupidBuzzer()
self.ok_to_buzz = True
self.answer = ''
self.guesses = []
self.evidence = dict()
def test_buzzer():
questions = QuestionDatabase().all_questions()
buzzer = RNNBuzzer(word_skip=conf['buzzer_word_skip'])
# setup machine agent
gspec = AbstractGuesser.list_enabled_guessers()[0]
guesser_dir = AbstractGuesser.output_path(gspec.guesser_module,
gspec.guesser_class, '')
guesser = ElasticSearchWikidataGuesser.load(guesser_dir)
guesser = ESGuesserWrapper(guesser)
key = list(questions.keys())[4]
question = questions[key].flatten_text().split()
for i, word in enumerate(question):
clue = ' '.join(question[:i])
guesses = guesser.guess(clue)
buzz = buzzer.buzz(guesses)
print(buzz)
import random
import pickle
from qanta.config import conf
from qanta.util.io import safe_path
from qanta.util.multiprocess import _multiprocess
from qanta.guesser.abstract import AbstractGuesser
from qanta.datasets.quiz_bowl import QuizBowlDataset, Question
from qanta.guesser.experimental.elasticsearch_instance_of import ElasticSearchWikidataGuesser
'''Randomly shuffle the word order and see if it changes the guesses.
'''
gspec = AbstractGuesser.list_enabled_guessers()[0]
guesser_dir = AbstractGuesser.output_path(gspec.guesser_module,
gspec.guesser_class, '')
guesser = ElasticSearchWikidataGuesser.load(guesser_dir)
def main():
fold = 'guessdev'
db = QuizBowlDataset(1, guesser_train=True, buzzer_train=True)
questions = db.questions_in_folds([fold])
first_n = lambda x: len(x)
print(guesser.guess_single(' '.join(questions[0].text.values())))
'''
s = [0, 0, 0, 0, 0]
for q in questions:
sents = list(q.text.values())
text_before = ' '.join(sents[:first_n(sents)])
words = text.split()
from tqdm import tqdm
from elasticsearch_dsl.connections import connections
from elasticsearch_dsl import DocType, Text, Keyword, Search, Index
from qanta.util.constants import GUESSER_DEV_FOLD
from qanta.guesser.abstract import AbstractGuesser
from qanta.datasets.quiz_bowl import QuizBowlDataset
from qanta.guesser.experimental.elasticsearch_instance_of import ElasticSearchWikidataGuesser
from qanta.guesser.experimental.elasticsearch_instance_of import ElasticSearchIndex
INDEX_NAME = 'qb_ir_instance_of'
gspec = AbstractGuesser.list_enabled_guessers()[0]
guesser_dir = AbstractGuesser.output_path(gspec.guesser_module,
gspec.guesser_class, '')
guesser = ElasticSearchWikidataGuesser.load(guesser_dir)
es_index = ElasticSearchIndex()
def recursive_guess(question, k=0):
p_class, p_prob = guesser.test_instance_of([question])[0]
first_guesses = search_not(question, p_class)
print('First round')
for x in first_guesses:
print(x)
print()
print('Second round')
new_guesses = []
for i in range(k):
guess = first_guesses[i][0]
question += ' ' + ' '.join(guess.split('_'))
guesses = es_index.search(question, p_class, p_prob, 0.6)