refine imdb benchmark scripts and text_classify_service

python/examples/imdb/get_data.sh

 wget --no-check-certificate https://fleet.bj.bcebos.com/text_classification_data.tar.gz
+wget --no-check-certificate https://paddle-serving.bj.bcebos.com/imdb-demo/imdb_model.tar.gz
 tar -zxvf text_classification_data.tar.gz
-#wget --no-check-certificate https://paddle-serving.bj.bcebos.com/imdb-demo%2Fimdb.tar.gz
-#tar -xzf imdb-demo%2Fimdb.tar.gz
+tar -zxvf imdb_model.tar.gz

python/examples/imdb/imdb_reader.py

@@ -30,6 +30,14 @@ class IMDBDataset(dg.MultiSlotDataGenerator):
         self._pattern = re.compile(r'(;|,|\.|\?|!|\s|\(|\))')
         self.return_value = ("words", [1, 2, 3, 4, 5, 6]), ("label", [0])
 
+    def get_words_only(self, line):
+        sent = line.lower().replace("<br />", " ").strip()
+        words = [x for x in self._pattern.split(sent) if x and x != " "]
+        feas = [
+            self._vocab[x] if x in self._vocab else self._unk_id for x in words
+        ]
+        return feas
+
     def get_words_and_label(self, line):
         send = '|'.join(line.split('|')[:-1]).lower().replace("<br />",
                                                               " ").strip()

python/examples/imdb/imdb_web_service_demo.sh

-wget https://paddle-serving.bj.bcebos.com/imdb-demo%2Fimdb_service.tar.gz
+wget https://paddle-serving.bj.bcebos.com/imdb-demo/imdb_service.tar.gz
 tar -xzf imdb_service.tar.gz
 wget --no-check-certificate https://fleet.bj.bcebos.com/text_classification_data.tar.gz
 tar -zxvf text_classification_data.tar.gz

python/examples/imdb/local_train.py

@@ -49,8 +49,9 @@ if __name__ == "__main__":
     dataset.set_batch_size(128)
     dataset.set_filelist(filelist)
     dataset.set_thread(10)
-    from nets import bow_net
-    avg_cost, acc, prediction = bow_net(data, label, dict_dim)
+    from nets import lstm_net
+    model_name = "imdb_lstm"
+    avg_cost, acc, prediction = lstm_net(data, label, dict_dim)
     optimizer = fluid.optimizer.SGD(learning_rate=0.01)
     optimizer.minimize(avg_cost)
 
@@ -65,6 +66,7 @@ if __name__ == "__main__":
             program=fluid.default_main_program(), dataset=dataset, debug=False)
         logger.info("TRAIN --> pass: {}".format(i))
         if i == 5:
-            serving_io.save_model("imdb_model", "imdb_client_conf",
+            serving_io.save_model("{}_model".format(model_name),
+                                  "{}_client_conf".format(model_name),
                                   {"words": data}, {"prediction": prediction},
                                   fluid.default_main_program())

python/examples/imdb/test_gpu_server.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.
-
-import os
-import sys
-from paddle_serving_server_gpu import OpMaker
-from paddle_serving_server_gpu import OpSeqMaker
-from paddle_serving_server_gpu import Server
-
-op_maker = OpMaker()
-read_op = op_maker.create('general_reader')
-general_infer_op = op_maker.create('general_infer')
-
-op_seq_maker = OpSeqMaker()
-op_seq_maker.add_op(read_op)
-op_seq_maker.add_op(general_infer_op)
-
-server = Server()
-server.set_op_sequence(op_seq_maker.get_op_sequence())
-server.set_num_threads(12)
-server.load_model_config(sys.argv[1])
-port = int(sys.argv[2])
-server.prepare_server(workdir="work_dir1", port=port, device="gpu")
-server.run_server()

python/examples/imdb/test_server.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.
-
-import os
-import sys
-from paddle_serving_server import OpMaker
-from paddle_serving_server import OpSeqMaker
-from paddle_serving_server import Server
-
-op_maker = OpMaker()
-read_op = op_maker.create('general_reader')
-general_infer_op = op_maker.create('general_infer')
-general_response_op = op_maker.create('general_response')
-
-op_seq_maker = OpSeqMaker()
-op_seq_maker.add_op(read_op)
-op_seq_maker.add_op(general_infer_op)
-op_seq_maker.add_op(general_response_op)
-
-server = Server()
-server.set_op_sequence(op_seq_maker.get_op_sequence())
-server.set_num_threads(4)
-
-server.load_model_config(sys.argv[1])
-port = int(sys.argv[2])
-server.prepare_server(workdir="work_dir1", port=port, device="cpu")
-server.run_server()

python/examples/imdb/text_classify_service.py

@@ -11,7 +11,6 @@
 # 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.
-#!flask/bin/python
 from paddle_serving_server.web_service import WebService
 from imdb_reader import IMDBDataset
 import sys
@@ -27,7 +26,7 @@ class IMDBService(WebService):
         if "words" not in feed:
             exit(-1)
         res_feed = {}
-        res_feed["words"] = self.dataset.get_words_and_label(feed["words"])[0]
+        res_feed["words"] = self.dataset.get_words_only(feed["words"])[0]
         return res_feed, fetch
 
 imdb_service = IMDBService(name="imdb")