senta_web_service.py

# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from paddle_serving_server_gpu.web_service import WebService
from paddle_serving_client import Client
from paddle_serving_app import LACReader, SentaReader
import numpy as np
import os
import io
import sys
import subprocess
from multiprocessing import Process, Queue


class SentaService(WebService):
    def start_lac_service(self):
        print(" ---- start lac service ---- ")
        os.chdir('./lac_serving')
        self.lac_port = self.port + 100
        r = os.popen(
            "python -m paddle_serving_server.serve --model ../../lac/jieba_server_model/ --port {} &".
            format(self.lac_port))
        os.chdir('..')

    def init_lac_service(self):
        ps = Process(target=self.start_lac_service())
        ps.start()
        #self.init_lac_client()

    def lac_predict(self, feed_data):
        self.init_lac_client()
        lac_result = self.lac_client.predict(
            feed={"words": feed_data}, fetch=["crf_decode"])
        self.lac_client.release()
        return lac_result

    def init_lac_client(self):
        self.lac_client = Client()
        self.lac_client.load_client_config(
            "../lac/jieba_client_conf/serving_client_conf.prototxt")
        self.lac_client.connect(["127.0.0.1:{}".format(self.lac_port)])

    def init_lac_reader(self):
        self.lac_reader = LACReader("../lac/lac_dict")

    def init_senta_reader(self):
        self.senta_reader = SentaReader(vocab_path="./senta_data/word_dict.txt")

    def preprocess(self, feed={}, fetch={}):
        print("---- preprocess ----")
        print(feed)
        if "words" not in feed:
            raise ("feed data error!")
        feed_data = self.lac_reader.process(feed["words"])
        fetch = ["crf_decode"]
        print("---- lac reader ----")
        print(feed_data)
        lac_result = self.lac_predict(feed_data)
        print("---- lac out ----")
        print(lac_result)
        segs = self.lac_reader.parse_result(feed["words"],
                                            lac_result["crf_decode"])
        print("---- lac parse ----")
        feed_data = self.senta_reader.process(segs)
        print("---- senta reader ----")
        print("feed_data", feed_data)
        fetch = ["sentence_feature"]
        return {"words": feed_data}, fetch


senta_service = SentaService(name="senta")
senta_service.load_model_config(sys.argv[1])
senta_service.prepare_server(
    workdir=sys.argv[2], port=int(sys.argv[3]), device="cpu")
senta_service.init_lac_reader()
senta_service.init_senta_reader()
print("Init senta done")
senta_service.init_lac_service()
print("init lac service done")
senta_service.run_server()
#senta_service.run_flask()

from flask import Flask, request

app_instance = Flask(__name__)


@app_instance.before_first_request
def init():
    global uci_service
    senta_service._launch_web_service()


service_name = "/" + senta_service.name + "/prediction"


@app_instance.route(service_name, methods=["POST"])
def run():
    print("---- run ----")
    print(request.json)
    return senta_service.get_prediction(request)


if __name__ == "__main__":
    app_instance.run(host="0.0.0.0",
                     port=senta_service.port,
                     threaded=False,
                     processes=4)