add senta web service

python/examples/senta/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 lac_reader import LACReader
+from senta_reader import 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')
+        r = os.popen(
+            "GLOG_v=2 python -m paddle_serving_server.serve --model ../../lac/jieba_server_model/ --port 9292 &"
+        )
+        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(["127.0.0.1:9292"])
+
+    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.init_lac_reader()
+senta_service.init_senta_reader()
+print("Init senta done")
+senta_service.init_lac_service()
+print("init lac service done")
+senta_service.prepare_server(
+    workdir=sys.argv[2], port=int(sys.argv[3]), device="cpu")
+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)

python/paddle_serving_server/serve.py

@@ -79,6 +79,7 @@ def start_standard_model():  # pylint: disable=doc-string-missing
     server.set_num_threads(thread_num)
     server.set_memory_optimize(mem_optim)
     server.set_max_body_size(max_body_size)
+    server.set_port(port)
 
     server.load_model_config(model)
     server.prepare_server(workdir=workdir, port=port, device=device)