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test_all_vector.py
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test_all_vector.py
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import pre_deal
from nltk import tokenize
import KMP
from bert_serving.client import BertClient
import numpy as np
def create_1000_case_test():
li = []
bc = BertClient(ip='222.19.197.230', port=5555, port_out=5556, check_version=False)
test_text = pre_deal.get_test_textVector()
zero_vector = np.zeros((500, 768))
for i in range(0, len(test_text)):
x = tokenize.word_tokenize(test_text[i])
if (len(x) >502):
index = KMP.KMP_algorithm(test_text[i], x[500] + " " + x[501])
if (index != -1):
list = []
sentence_1 = test_text[i][0:index]
sentence_2 = test_text[i][index:]
list.append(sentence_1)
list.append(sentence_2)
vector = bc.encode(list)
ve = np.concatenate((vector[0], vector[1]), axis=0)
li.append(ve.tolist())
else:
list = []
list.append(test_text[i])
vector = bc.encode(list)
ve = np.concatenate((vector[0], zero_vector), axis=0)
li.append(ve.tolist())
else:
list = []
list.append(test_text[i])
vector = bc.encode(list)
ve = np.concatenate((vector[0], zero_vector), axis=0)
li.append(ve.tolist())
li_vector = np.array(li)
np.save("test_case_1000.npy", li_vector)