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proc_data.py
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proc_data.py
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import numpy as np
import csv
import random
def proc_and_binarize(dir):
fid = open(dir+ "/train.tsv")
train= fid.read()
train = train.split("\n")[:-1]
fid = open(dir+ "/dev.tsv")
test = fid.read()
test = test.split("\n")[:-1]
topics = ["world","sports","business","science"]
true_test = []
false_test = []
true_train = []
false_train = []
range_arr = list(range(0,len(topics)))
for i in range(0,len(test)):
line = test[i].split('\t')
label = line[0]
if not(len(line) ==3):
print("skipping " +str(i))
continue
if label[0] =="\"":
label = label[1:-1]
label = int(label)-1
text = line[2]
if text[0] =="\"":
text = text[1:-1]
if text[0] == " ":
text = text[1:]
choice_array = range_arr[:label]+range_arr[label+1:]
ps_label = random.choice(choice_array)
true_ex = topics[label] + text
false_ex = topics[ps_label] + text
true_test.append(true_ex)
false_test.append(false_ex)
for i in range(0,len(train)):
line = train[i].split('\t')
if not(len(line) ==3):
print("skipping " +str(i))
continue
label = line[0]
if label[0] =="\"":
label = label[1:-1]
label = int(label)-1
text = line[2]
if text[0] =="\"":
text = text[1:-1]
if text[0] == " ":
text = text[1:]
choice_array = range_arr[:label]+range_arr[label+1:]
ps_label = random.choice(choice_array)
true_ex = topics[label] + text
false_ex = topics[ps_label] + text
true_train.append(true_ex)
false_train.append(false_ex)
return true_train,false_train,true_test,false_test
def main():
fid = open("data/AG-news/train.csv")
text_train = fid.read()
fid = open("data/AG-news/test.csv")
text_test = fid.read()
fid.close()
csv.writer(open("data/AG-news/train.tsv", 'w+'), delimiter='\t').writerows(csv.reader(open("data/AG-news/train.csv")))
csv.writer(open("data/AG-news/dev.tsv", 'w+'), delimiter='\t').writerows(csv.reader(open("data/AG-news/test.csv")))
true_train, false_train, true_test, false_test = proc_and_binarize("data/AG-news")
random.shuffle(true_train)
random.shuffle(false_train)
random.shuffle(true_test)
random.shuffle(false_test)
false_lines = []
true_lines = []
for i in range(0,len(false_test)):
false_lines.append(false_test[i] + "\t0" + "\n")
for i in range(0,len(false_test)):
true_lines.append(true_test[i] + "\t1" + "\n")
test_lines = false_lines+true_lines
random.shuffle(test_lines)
false_lines = []
true_lines = []
for i in range(0,len(false_train)):
false_lines.append(false_train[i] + "\t0" + "\n")
for i in range(0,len(true_train)):
true_lines.append(true_train[i] + "\t1" + "\n")
train_lines = false_lines+true_lines
random.shuffle(train_lines)
train_split_all= "\n" + "".join(train_lines)
test_split_all= "\n" + "".join(test_lines)
fid = open("data/AG-news/train.tsv",'w')
fid.write(train_split_all)
fid.close()
fid = open("data/AG-news/dev.tsv",'w')
fid.write(test_split_all)
fid.close()
main()