-
Notifications
You must be signed in to change notification settings - Fork 0
/
chat.py
72 lines (55 loc) · 2.01 KB
/
chat.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
#-*- coding: utf-8 -*-
from konlpy.tag import Twitter
import os
os.environ["CUDA_VISIBLE_DEVICES"]="4"
import tensorflow as tf
import numpy as np
import math
import sys
from model import sequence2sequence
import config
from Conversation import Conversation
twitter=Twitter()
class Chat:
def __init__(self,VOC_PATH, train_dir):
self.conv= Conversation()
self.conv.Load_voc(VOC_PATH)
self.model=sequence2sequence(self.conv.voc_size)
self.sess=tf.Session()
ckpt=tf.train.get_checkpoint_state(train_dir)
self.model.saver.restore(self.sess,ckpt.model_checkpoint_path)
def decode(self,enc_input, dec_input):
if type(dec_input) is np.ndarray:
dec_input=dec_input.tolist()
input_len=int(math.ceil((len(enc_input)+1) * 1.5))
enc_input,dec_input,_=self.conv.transform(enc_input,dec_input,input_len, config.max_decode_len)
return self.model.predict(self.sess, [enc_input], [dec_input])
def run(self):
sys.stdout.write(" > ")
sys.stdout.flush()
line=sys.stdin.readline()
while line:
print(self.response(line.strip()))
sys.stdout.write("\n > ")
sys.stdout.flush()
line=sys.stdin.readline()
def response(self, ipt):
#enc_input=twitter.morphs(ipt)
enc_input=self.conv.Tokenizer(ipt) # twitter 사용시 위 라인의 주석을 풀고, 이 라인을 주석처리.
enc_input=self.conv.Tokens_to_index(enc_input)
cur=0
dec_input=[]
for i in range(config.max_decode_len):
outputs=self.decode(enc_input,dec_input)
if self.conv.is_eos(outputs[0][cur]):
break
elif self.conv.is_defined(outputs[0][cur]) is not True:
dec_input.append(outputs[0][cur])
cur+=1
reply=self.conv.decode([dec_input],True)
return reply
def main():
chatbot=Chat(config.VOC_PATH,config.train_dir)
chatbot.run()
if __name__=="__main__":
main()