# TODO CHECK SOMEWHERE ELSE
if len(gold_list) == 0:
# print("name " + str(names) + " does not match anything, discarding")
if not skip:
yield example
continue
gold_list = np.array(gold_list).astype(np.int32)
# print(example["neighborhood"].entity_vertices.shape[0])
# print("projected " + str(example["gold_entities"]) + " to " + str(gold_list))
example["gold_entities"] = gold_list
yield example
epoch_iterator = train_file_iterator.iterate()
epoch_iterator = candidate_generator.enrich(epoch_iterator)
epoch_iterator = project_from_name_wrapper(epoch_iterator)
all_seen_paths = defaultdict(int)
for example in epoch_iterator:
example_seen = {}
for g in example["gold_entities"]:
paths = example["neighborhood"].get_paths_to_neighboring_centroid(g)
for path in paths:
if len(path) == 4:
label = path[1] + path[2]
else:
label = path[1] + path[2] + path[4] + path[5]
from helpers.read_conll_files import ConllReader
import random
reader = ConllReader(
"/home/michael/Projects/QuestionAnswering/GCNQA/data/webquestions/train.internal.conll"
)
sentences = []
for line in reader.iterate():
sentence = " ".join([w[1] for w in line["sentence"]])
sentences.append(sentence)
subset = random.sample(sentences, 50)
counter = {}
for example in subset:
print(example)
classification = input()
if classification not in counter:
counter[classification] = 0
counter[classification] += 1
total = sum([v for k, v in counter.items()])
print("class\tcount\t%")
for k, v in counter.items():
print(str(k) + ": \t" + str(v) + " \t" + str(v / total * 100))