def test_extract_eventualities():
client = ASERClient(port=ASER_PORT)
print("=" * 50)
print("Testing extract struct...")
ans1 = json.dumps(client.extract_eventualities(s1))
ans2 = json.dumps(client.extract_eventualities(s2))
client.close()
results_list = []
n_workers = 10
n_iter = 50
pool = Pool(n_workers)
for i in range(n_workers // 2):
r = pool.apply_async(fn1,
args=(
s1,
n_iter,
ans1,
"`ext_eventuality_1`({})".format(i),
))
results_list.append(r)
r = pool.apply_async(fn1,
args=(
s2,
n_iter,
ans2,
"`ext_eventuality_2`({})".format(i),
))
results_list.append(r)
pool.close()
pool.join()
avg_t = np.mean([r.get() for r in results_list]) / n_workers
print("`ext_eventuality_struct` {:.2f} ms / call in average".format(avg_t))
def test_all_apis():
client = ASERClient(port=ASER_PORT)
eventuality_info_1 = client.extract_eventualities(s1)
eventuality1 = eventuality_info_1["eventualities"][0]
eventuality_info_2 = client.extract_eventualities(s2)
eventuality2 = eventuality_info_2["eventualities"][0]
eventuality_info_3 = client.extract_eventualities(s3)
eventuality3 = eventuality_info_3["eventualities"][0]
rel1 = client.predict_relation(eventuality1, eventuality2)
rel2 = client.predict_relation(eventuality1, eventuality3)
related_events1 = client.fetch_related_eventualities(eventuality1)
related_events2 = client.fetch_related_eventualities(eventuality2)
client.close()
st = time.time()
n_workers = 10
n_iter = 50
pool = Pool(n_workers)
pool.apply_async(fn1,
args=(s1, n_iter, json.dumps(eventuality_info_1),
"`ext_eventuality_0`"))
pool.apply_async(fn1,
args=(s2, n_iter, json.dumps(eventuality_info_2),
"`ext_eventuality_1`"))
pool.apply_async(fn2,
args=(eventuality1, eventuality2, n_iter,
json.dumps(rel1), "`match_relation_2`"))
pool.apply_async(fn2,
args=(eventuality1, eventuality3, n_iter,
json.dumps(rel2), "`match_relation_3`"))
pool.apply_async(fn3,
args=(eventuality1, n_iter, json.dumps(related_events1),
"`get_related_events_4`"))
pool.apply_async(fn3,
args=(eventuality2, n_iter, json.dumps(related_events2),
"`get_related_events_5`"))
pool.close()
pool.join()
end = time.time()
print("Overall duration: {:.2f} s".format(end - st))
def fn3(e, n_iter, ans, prefix):
client = ASERClient(port=ASER_PORT)
st = time.time()
for _ in range(n_iter):
try:
tmp = client.fetch_related_eventualities(e)
assert json.dumps(tmp) == ans, "[{}] Wrong answer".format(prefix)
except Exception:
print("[{}] Wrong answer".format(prefix))
print(traceback.format_exc())
client.close()
return
end = time.time()
print("[{}] passed, {} ms / call".format(prefix,
(end - st) / n_iter * 1000))
client.close()
return (end - st) / n_iter * 1000
def fn1(s, n_iter, ans, prefix):
client = ASERClient(port=ASER_PORT)
st = time.time()
for _ in range(n_iter):
try:
tmp = client.extract_eventualities(s)
assert json.dumps(tmp) == ans, "[{}] Wrong answer".format(prefix)
except Exception:
print("[{}] Wrong answer".format(prefix))
print(traceback.format_exc())
client.close()
return
end = time.time()
duration = (end - st) / n_iter * 1000
print("[{}] passed, {:.2f} ms / call".format(prefix, duration))
client.close()
return (end - st) / n_iter * 1000
def test_predict_relation():
client = ASERClient(port=ASER_PORT)
print("=" * 50)
print("Testing match relation...")
eventuality1 = client.extract_eventualities(s1, only_eventualities=True)[0]
eventuality2 = client.extract_eventualities(s2, only_eventualities=True)[0]
eventuality3 = client.extract_eventualities(s3, only_eventualities=True)[0]
ans1 = json.dumps(client.predict_relation(eventuality1, eventuality2))
ans2 = json.dumps(client.predict_relation(eventuality1, eventuality3))
client.close()
results_list = []
n_workers = 10
n_iter = 50
pool = Pool(n_workers)
for i in range(n_workers // 2):
r = pool.apply_async(fn2,
args=(
eventuality1,
eventuality2,
n_iter,
ans1,
"`predict_relation_1`({})".format(i),
))
results_list.append(r)
r = pool.apply_async(fn2,
args=(
eventuality1,
eventuality3,
n_iter,
ans2,
"`predict_relation_2`({})".format(i),
))
results_list.append(r)
pool.close()
pool.join()
avg_t = np.mean([r.get() for r in results_list]) / n_workers
print("`match_relation` {:.2f} ms / call in average".format(avg_t))
from aser.client import ASERClient
from pprint import pprint as print
if __name__ == "__main__":
client = ASERClient(port=20097, port_out=20098)
# s1 = 'they yucca look leggy. they african violet refuse to flower'
# s2 = 'they african violet refuse to flower'
s1 = 'I am hungry'
s2 = 'Evert said'
eventuality1 = client.extract_eventualities(s1)
eventuality2 = client.extract_eventualities(s2)
print("Event 1: ")
print(eventuality1)
# print(eventuality1[0][0].to_dict())
print("Event 2: ")
print(eventuality2)
print("Relation: ")
rel = client.predict_relation(eventuality1[0][0], eventuality2[0][0])
print(rel)
#
print("Related events: ")
related_events = client.fetch_related_eventualities(eventuality1[0][0])
print(related_events)
def fn1(s, iter_num):
client = ASERClient(port=8000)
for i in range(iter_num):
client.extract_eventualities(s)
client.close()
def fn3(e, iter_num):
client = ASERClient(port=8000)
for i in range(iter_num):
client.fetch_related_eventualities(e)
client.close()
def fn2(e1, e2, iter_num):
client = ASERClient(port=8000)
for i in range(iter_num):
client.predict_relation(e1, e2)
client.close()
def fn2(e1, e2, iter_num):
client = ASERClient(port=8000)
for i in range(iter_num):
client.predict_relation(e1, e2)
client.close()
def fn3(e, iter_num):
client = ASERClient(port=8000)
for i in range(iter_num):
client.fetch_related_eventualities(e)
client.close()
if __name__ == "__main__":
client = ASERClient(port=8000)
# s1 = 'they yucca look leggy'
# s2 = 'they african violet refuse to flower'
s1 = 'I am hungry'
s2 = 'I am in the kitchen'
e1 = client.extract_eventualities(s1, only_eventualities=True)[0]
e2 = client.extract_eventualities(s2, only_eventualities=True)[0]
client.close()
total_num = 10000
n_workers = 1
batch_size = total_num // n_workers
st = time.time()
pool = Pool(n_workers)
import gc
import time
from tqdm import tqdm
from aser.client import ASERClient
if __name__ == "__main__":
gc.collect()
client = ASERClient(port=8000)
# s1 = 'they yucca look leggy'
# s2 = 'they african violet refuse to flower'
s1 = 'I am hungry'
s2 = 'I am in the kitchen'
eventuality2 = client.extract_eventualities(s2, only_eventualities=True)[0]
gc.collect()
st = time.time()
for i in range(1000):
eventuality1 = client.extract_eventualities(s1,
only_eventualities=True)[0]
print("`extract_eventualities`: {:.2f}ms / call".format(
(time.time() - st)))
gc.collect()
st = time.time()
for i in range(1000):
rel = client.predict_relation(eventuality1, eventuality2)
print("`get_exact_match_relation`: {:.2f}ms / call".format(
(time.time() - st)))
gc.collect()