refine this pr

core/general-client/src/general_model.cpp

@@ -190,12 +190,19 @@ int PredictorClient::create_predictor() {
 const std::string &PredictorClient::get_model_config() {
   Request req;
   Response res;
+  VLOG(2) << "going to send request";
   req.set_request_type("GetConf");
+  _api.thrd_initialize();
+  std::string variant_tag;
+  _predictor = _api.fetch_predictor("general_model", &variant_tag);
+
+  VLOG(2) << "sending";
   if (_predictor->inference(&req, &res) != 0) {
     LOG(ERROR) << "failed call predictor with req: " << req.ShortDebugString();
     _api.thrd_clear();
     return "";
   } else {
+    VLOG(2) << "get model config succeed";
     const std::string &config_str = res.config_str();
     return config_str;
   }

core/general-server/op/general_get_conf_op.cpp

@@ -27,16 +27,24 @@ using baidu::paddle_serving::predictor::general_model::Response;
 
 int GeneralGetConfOp::inference() {
   // reade request from client
+  VLOG(2) << "going to get request";
   const Request *req = dynamic_cast<const Request *>(get_request_message());
 
+  VLOG(2) << "request got";
   baidu::paddle_serving::predictor::Resource &resource =
       baidu::paddle_serving::predictor::Resource::instance();
 
-  std::string conf_str = resource.get_general_model_conf_str();
+  VLOG(2) << "request type : " << req->request_type();
+
+  VLOG(2) << "fetching conf str";
+  const std::string &conf_str = resource.get_general_model_conf_str();
+  VLOG(2) << conf_str;
   Response *res = mutable_data<Response>();
-  res->set_config_str(conf_str);
+  res->set_config_str(conf_str.c_str());
+  VLOG(2) << "done.";
   return 0;
 }
+
 DEFINE_OP(GeneralGetConfOp);
 }  // namespace serving
 }  // namespace paddle_serving

core/predictor/framework/service.cpp

@@ -136,7 +136,7 @@ const std::string& InferService::name() const { return _infer_service_format; }
 int InferService::inference(const google::protobuf::Message* request,
                             google::protobuf::Message* response,
                             butil::IOBufBuilder* debug_os) {
-  TRACEPRINTF("start to inference");
+  VLOG(2) << "start to inference";
   // when funtion call begins, framework will reset
   // thread local variables&resources automatically.
   if (Resource::instance().thread_clear() != 0) {
@@ -144,7 +144,7 @@ int InferService::inference(const google::protobuf::Message* request,
     return ERR_INTERNAL_FAILURE;
   }
 
-  TRACEPRINTF("finish to thread clear");
+  VLOG(2) << "finish to thread clear";
 
   if (_enable_map_request_to_workflow) {
     LOG(INFO) << "enable map request == True";
@@ -155,14 +155,15 @@ int InferService::inference(const google::protobuf::Message* request,
     }
     size_t fsize = workflows->size();
     for (size_t fi = 0; fi < fsize; ++fi) {
+      VLOG(2) << "workflow index: " << fi;
       Workflow* workflow = (*workflows)[fi];
       if (workflow == NULL) {
         LOG(ERROR) << "Failed to get valid workflow at: " << fi;
         return ERR_INTERNAL_FAILURE;
       }
-      TRACEPRINTF("start to execute workflow[%s]", workflow->name().c_str());
+      VLOG(2) << "start to execute workflow[" << workflow->name() << "]";
       int errcode = _execute_workflow(workflow, request, response, debug_os);
-      TRACEPRINTF("finish to execute workflow[%s]", workflow->name().c_str());
+      VLOG(2) << "finish to execute workflow[" << workflow->name() << "]";
       if (errcode < 0) {
         LOG(ERROR) << "Failed execute workflow[" << workflow->name()
                    << "] in:" << name();
@@ -171,12 +172,12 @@ int InferService::inference(const google::protobuf::Message* request,
     }
   } else {
     LOG(INFO) << "enable map request == False";
-    TRACEPRINTF("start to execute one workflow");
+    VLOG(2) << "start to execute one workflow";
     size_t fsize = _flows.size();
     for (size_t fi = 0; fi < fsize; ++fi) {
-      TRACEPRINTF("start to execute one workflow-%lu", fi);
+      VLOG(2) << "start to execute one workflow-" << fi;
       int errcode = execute_one_workflow(fi, request, response, debug_os);
-      TRACEPRINTF("finish to execute one workflow-%lu", fi);
+      VLOG(2) << "finish to execute one workflow-" << fi;
       if (errcode < 0) {
         LOG(ERROR) << "Failed execute 0-th workflow in:" << name();
         return errcode;
@@ -215,6 +216,7 @@ int InferService::_execute_workflow(Workflow* workflow,
   req_channel.init(0, START_OP_NAME);
   req_channel = request;
 
+  VLOG(2) << "dag full name: " << full_name();
   DagView* dv = workflow->fetch_dag_view(full_name());
   dv->set_request_channel(req_channel);
 
@@ -225,14 +227,14 @@ int InferService::_execute_workflow(Workflow* workflow,
     return errcode;
   }
 
-  TRACEPRINTF("finish to dv execute");
+  VLOG(2) << "finish to dv execute";
   // create ender channel and copy
   const Channel* res_channel = dv->get_response_channel();
   if (!_merger || !_merger->merge(res_channel->message(), response)) {
     LOG(ERROR) << "Failed merge channel res to response";
     return ERR_INTERNAL_FAILURE;
   }
-  TRACEPRINTF("finish to copy from");
+  VLOG(2) << "finish to copy from";
 
   workflow_time.stop();
   LOG(INFO) << "workflow total time: " << workflow_time.u_elapsed();
@@ -241,7 +243,7 @@ int InferService::_execute_workflow(Workflow* workflow,
 
   // return tls data to object pool
   workflow->return_dag_view(dv);
-  TRACEPRINTF("finish to return dag view");
+  VLOG(2) << "finish to return dag view";
   return ERR_OK;
 }
 

python/examples/fit_a_line/test_client_without_config.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.
+# pylint: disable=doc-string-missing
+
+from paddle_serving_client import Client
+import sys
+
+client = Client()
+#client.load_client_config(sys.argv[1])
+client.connect(["127.0.0.1:9696"])
+'''
+import paddle
+test_reader = paddle.batch(
+    paddle.reader.shuffle(
+        paddle.dataset.uci_housing.test(), buf_size=500),
+    batch_size=1)
+
+for data in test_reader():
+    fetch_map = client.predict(feed={"x": data[0][0]}, fetch=["price"])
+    print("{} {}".format(fetch_map["price"][0], data[0][1][0]))
+'''

python/paddle_serving_client/__init__.py

@@ -154,6 +154,10 @@ class Client(object):
                 print(
                     "parameter endpoints({}) will not take effect, because you use the add_variant function.".
                     format(endpoints))
+        from .serving_client import PredictorClient
+        from .serving_client import PredictorRes
+        self.result_handle_ = PredictorRes()
+        self.client_handle_ = PredictorClient()
         sdk_desc = self.predictor_sdk_.gen_desc()
         self.client_handle_.create_predictor_by_desc(sdk_desc.SerializeToString(
         ))
@@ -163,11 +167,10 @@ class Client(object):
         model_conf = google.protobuf.text_format.Merge(
             str(model_config_str), model_conf)
 
-        self.result_handle_ = PredictorRes()
-        self.client_handle_ = PredictorClient()
         self.client_handle_.init_from_string(model_config_str)
         if "FLAGS_max_body_size" not in os.environ:
             os.environ["FLAGS_max_body_size"] = str(512 * 1024 * 1024)
+        read_env_flags = ["profile_client", "profile_server", "max_body_size"]
         self.client_handle_.init_gflags([sys.argv[
             0]] + ["--tryfromenv=" + ",".join(read_env_flags)])
         self.feed_names_ = [var.alias_name for var in model_conf.feed_var]

python/paddle_serving_server/__init__.py

@@ -107,7 +107,7 @@ class OpSeqMaker(object):
         node = server_sdk.DAGNode()
         node.name = "general_get_conf_0"
         node.type = "GeneralGetConfOp"
-        get_conf_workflow.nodes.extend(node)
+        get_conf_workflow.nodes.extend([node])
         workflow_conf.workflows.extend([get_conf_workflow])
         return workflow_conf
 
@@ -233,15 +233,13 @@ class Server(object):
             infer_service.request_field_key = "request_type"
 
             kv_workflow1 = server_sdk.ValueMappedWorkflow()
-            kv_workflow1.request_field_value = "GetConf"
-            kv_workflow1.workflows = "workflow1"
-
+            kv_workflow1.request_field_value = "Predict"
+            kv_workflow1.workflow = "workflow1"
             infer_service.value_mapped_workflows.extend([kv_workflow1])
 
             kv_workflow2 = server_sdk.ValueMappedWorkflow()
-            kv_workflow2.request_field_value = "Predict"
-            kv_workflow2.workflows = "workflow2"
-
+            kv_workflow2.request_field_value = "GetConf"
+            kv_workflow2.workflow = "workflow2"
             infer_service.value_mapped_workflows.extend([kv_workflow2])
 
             infer_service.name = "GeneralModelService"