def train():
"""
;parm 请求参数格式
{
"name":"train",
"data":{
"name":"textcnn-one",
"categories":"0.1",
"directory":"text"
}
}
:return:
"""
try:
param = json.loads(request.get_data())
if param['name'] != 'train':
return jsonify(Response(code=1, msg='service interface name error').__dict__)
data = param['data']
task_train(current_app.instance_path,data['name'],data['categories'].split(','),data['directory'])
return jsonify(Response(data={'msg':'train complete!'}).__dict__)
# executor.submit(task_train,current_app.instance_path,data['name'],data['categories'].split(','))
# return jsonify(Response(data={'msg': 'start train!'}).__dict__)
except Exception as e:
current_app.logger.errot(e)
return jsonify(Response(code=-1, msg='service call error').__dict__)
def train_cnn():
"""
;parm 请求参数格式
{
"name":"traincnn",
"data":{
"name":"textcnn"
"directory":"D:/textcnn/dataset/train"
}
}
:return:
"""
try:
param = json.loads(request.get_data())
if param['name'] != 'traincnn':
return jsonify(Response(code=1, msg='service interface name error').__dict__)
data = param['data']
model_name = data['name']
word_model_dir = os.path.join(current_app.instance_path, 'word2vec')
train_class=Train(word_model_dir)
train_class.main(data['directory'],current_app.instance_path,word_model_dir,model_name)
return jsonify(Response(msg='text cnn model train complete').__dict__)
except Exception as e:
current_app.logger.errot(e)
return jsonify(Response(code=-1, msg='service call error').__dict__)
def predict_real_top():
"""
参数格式
{
"name":"predict_real_top",
"data":{
"name":"textcnn",
"top":3,
"data":"nichola nicklebi celabr human spirit unrel dickensian decenc turn me horror scroog",
}
}
:return:
"""
try:
param = json.loads(request.get_data())
if param['name'] != 'predict_real_top':
return jsonify(Response(code=1, msg='service interface name error').__dict__)
data = param['data']
model_name = data['name']
checkpoint_dir=os.path.join(current_app.instance_path, 'runs',model_name)
categories=list(open(os.path.join(checkpoint_dir, 'categories.txt'),"r",encoding='utf-8').readlines())
categories_array=categories[0].split(',')
if len(categories_array) < int(data['top']):
msg = 'the number of model classifications is {}'.format(len(categories_array))
return jsonify(Response(code=-1, data=msg, msg='error').__dict__)
else:
predict_content=data['data']
top_num=data['top']
predict_real_class=Predict_Real()
ruselt_data=predict_real_class.predict(checkpoint_dir,predict_content,top_num,categories_array)
return jsonify(Response(data=ruselt_data, msg='service call 成功').__dict__)
except Exception as e:
current_app.logger.errot(e)
return jsonify(Response(code=-1, msg='service call error').__dict__)
def sample():
"""
接收请求端数据，并按一个时间为一个文件进行组织存储
;parm请求参数格式
{
"name":"sample",
"data":{
"id":1346268613836800,
"name":"",
"label":"0",
"content":"",
"date":1585014916672,
"directory":"text"
}
}
:return:
"""
try:
param=json.loads(request.get_data())
if param['name'] != 'sample':
return jsonify(Response(code=1,msg='service interface name error').__dict__)
data=param['data']
dir_path=path.join(current_app.instance_path,'dataset',data['directory'],data['label'])
if not os.path.exists(dir_path):
os.makedirs(dir_path)
# write file
file = path.join(dir_path,data['name'])
FileUtils.write(file=file,data='{}\n'.format(data['content']),append=True)
return jsonify(Response(data=dir_path).__dict__)
except:
return jsonify(Response(code=-1, msg='service call error').__dict__)
def predict_top():
"""
参数格式
{
"name":"predict",
"data":{
"name":"textcnn",
"top":3,
"data":"nichola nicklebi celabr human spirit unrel dickensian decenc turn me horror scroog",
}
}
:return:
"""
try:
param = json.loads(request.get_data())
if param['name'] != 'predict':
return jsonify(Response(code=1, msg='service interface name error').__dict__)
data = param['data']
model = get_model(data['name'])
if model.categories_len() < int(data['top']):
msg='the number of model classifications is {}'.format(model.categories_len())
return jsonify(Response(code=-1,data=msg,msg='error').__dict__)
else:
return jsonify(Response(data=model.predict_top(data['data'],int(data['top']))).__dict__)
except Exception as e:
current_app.logger.errot(e)
return jsonify(Response(code=-1, msg='service call error').__dict__)
def predict_cnn():
"""
参数格式
{
{
"name":"predict_local_top",
"data":{
"name":"textcnn",
"top":3,
"data":"D:/textcnn/dataset/test",
}
}
}
:return:
"""
try:
param = json.loads(request.get_data())
if param['name'] != 'predict_local_top':
return jsonify(Response(code=1, msg='service interface name error').__dict__)
data = param['data']
# categories_path=param['categories_path']
model_name = data['name']
checkpoint_dir=os.path.join(current_app.instance_path, 'runs',model_name)
categories=list(open(os.path.join(checkpoint_dir, 'categories.txt'),"r",encoding='utf-8').readlines())
categoriesArray=categories[0].split(',')
if len(categoriesArray) < int(data['top']):
msg = 'the number of model classifications is {}'.format(len(categoriesArray))
return jsonify(Response(code=-1, data=msg, msg='error').__dict__)
else:
top_num=data['top']
testdata_dir=data['data']
predictlocalclass=Predict()
ruseltdata=predictlocalclass.predict(checkpoint_dir,testdata_dir,top_num,categoriesArray)
return jsonify(Response(data=ruseltdata, msg='service call 成功').__dict__)
# predictlocalclass.predict(categories_path, checkpoint_filepath, testdata_dirpath)
# predictlocalclass.predict(mpdel_name, top_num, testdata_dir)
# return jsonify(Response(data=ruseltdata, msg='service call 成功').__dict__)
except Exception as e:
current_app.logger.errot(e)
return jsonify(Response(code=-1, msg='service call error').__dict__)
def predict():
"""
参数格式
{
"name":"predict",
"data":{
"name":"textcnn",
"data":"nichola nicklebi celabr human spirit unrel dickensian decenc turn me horror scroog",
}
}
:return:
"""
try:
param = json.loads(request.get_data())
if param['name'] != 'predict':
return jsonify(Response(code=1, msg='service interface name error').__dict__)
data = param['data']
model=get_model(data['name'])
return jsonify(Response(data=model.predict(data['data'])).__dict__)
except Exception as e:
current_app.logger.errot(e)
return jsonify(Response(code=-1, msg='service call error').__dict__)
def word_train():
"""
;parm 请求参数格式
{
"name":"wordtrain",
"data":{
"directory":"D:/data/cutdata.txt"
}
}
:return:
"""
try:
param = json.loads(request.get_data())
if param['name'] != 'wordtrain':
return jsonify(Response(code=1, msg='service interface name error').__dict__)
data = param['data']
data_path=data['directory']
word_model_dir=os.path.join(current_app.instance_path,'word2vec')
word2vecclass.train_word(data_path,word_model_dir)
return jsonify(Response(msg='word train complete').__dict__)
except Exception as e:
current_app.logger.errot(e)
return jsonify(Response(code=-1, msg='service call error').__dict__)