def predict(lstTxt, model_preDir):
pass
res_pre = []
filename = os.path.join(arg_dic['output_predict'], 'test_results.tsv')
bc = Bert_Class(model_preDir)
for i in os.listdir(model_preDir):
if '.pb' in i:
for j in lstTxt:
res_pb = bc.predict_on_pb(j)
res_pre.append(res_pb)
with open(filename, 'w', newline='') as csvfile:
writer = csv.writer(csvfile)
for row in res_pre:
writer.writerow(row)
elif 'checkpoint' in i:
bc.predict_on_ckpt(lstTxt)
time_end = int(time.time())
result = []
result.append(time_end)
try:
with open(filename, 'r') as f:
data = f.read()
lst_ret = data.splitlines()
lst_ret1 = [int(x) for x in lst_ret]
result.append(lst_ret1)
# 统计时去除“其它”分类0
lst_ret = [int(x) for x in lst_ret if not x in ['', '0']]
# 合并次数
lstset = Counter(lst_ret)
result.append(lstset)
return result
except:
return ''
def skl_getMatrix():
skl_print = '开始打印混淆矩阵!'.center(50)
# bobao(skl_print)
pass
path = r'D:\work_space\Weibo\Weibo_multi-label-classifier\data\dataAll\dat_20200403'
model_preDir = r'./model_predict/'
filename = os.path.join(arg_dic['output_predict'], 'test_results.tsv')
dev = os.path.join(path,'dev.tsv')
y_true = []
lines = []
with open(dev,'r',encoding='utf-8') as f:
reader = csv.reader(f,delimiter="\t")
for line in reader:
y_true.append(int(line[0]))
lines.append(line[1])
bc = Bert_Class(model_preDir)
bc.predict_on_ckpt(lines)
with open(filename, 'r') as f:
data = f.read()
lst_ret = data.splitlines()
y_pred = [int(x) for x in lst_ret]
print(y_true)
print(y_pred)
eval_report = classification_report(y_true,y_pred)
print(eval_report)
return 0
# -*- coding: utf-8 -*- ''' @author: [email protected] @license: (C) Copyright 2019 @desc: 项目描述。 @DateTime: Created on 2019/7/22, at 下午 05:07 by PyCharm ''' from sanic import Sanic from sanic.response import json as Rjson from predict_GPU import Bert_Class app = Sanic() my = Bert_Class() @app.route("/", methods=['GET', 'POST']) async def home(request): # 1，首先要从HTTP请求获取用户的字符串 dict1 = {'tips': '请用POST方法，传递“用户id、question”字段'} if request.method == 'GET': user, key_str = request.args.get('user_id'), request.args.get( 'question') elif request.method == 'POST': for k, v in request.form.items(): dict1[k] = v # 最关心的问题字段是keyword user, key_str = request.form.get('user_id'), request.form.get( 'question') else: return Rjson(dict1) if not key_str or not user: # 如果有空的字段，返回警告信息。