Merge pull request #685 from wangxicoding/speedup_copy

Speedup output copy, set grpc max message to 512MB

core/general-client/src/general_model.cpp

@@ -285,22 +285,16 @@ int PredictorClient::batch_predict(
         // int idx = _fetch_name_to_idx[name];
         if (_fetch_name_to_type[name] == 0) {
           VLOG(2) << "ferch var " << name << "type int";
-          model._int64_value_map[name].resize(
-              output.insts(0).tensor_array(idx).int64_data_size());
           int size = output.insts(0).tensor_array(idx).int64_data_size();
-          for (int i = 0; i < size; ++i) {
-            model._int64_value_map[name][i] =
-                output.insts(0).tensor_array(idx).int64_data(i);
-          }
+          model._int64_value_map[name] = std::vector<int64_t>(
+              output.insts(0).tensor_array(idx).int64_data().begin(),
+              output.insts(0).tensor_array(idx).int64_data().begin() + size);
         } else {
           VLOG(2) << "fetch var " << name << "type float";
-          model._float_value_map[name].resize(
-              output.insts(0).tensor_array(idx).float_data_size());
           int size = output.insts(0).tensor_array(idx).float_data_size();
-          for (int i = 0; i < size; ++i) {
-            model._float_value_map[name][i] =
-                output.insts(0).tensor_array(idx).float_data(i);
-          }
+          model._float_value_map[name] = std::vector<float>(
+              output.insts(0).tensor_array(idx).float_data().begin(),
+              output.insts(0).tensor_array(idx).float_data().begin() + size);
         }
         idx += 1;
       }
@@ -564,22 +558,16 @@ int PredictorClient::numpy_predict(
         // int idx = _fetch_name_to_idx[name];
         if (_fetch_name_to_type[name] == 0) {
           VLOG(2) << "ferch var " << name << "type int";
-          model._int64_value_map[name].resize(
-              output.insts(0).tensor_array(idx).int64_data_size());
           int size = output.insts(0).tensor_array(idx).int64_data_size();
-          for (int i = 0; i < size; ++i) {
-            model._int64_value_map[name][i] =
-                output.insts(0).tensor_array(idx).int64_data(i);
-          }
+          model._int64_value_map[name] = std::vector<int64_t>(
+              output.insts(0).tensor_array(idx).int64_data().begin(),
+              output.insts(0).tensor_array(idx).int64_data().begin() + size);
         } else {
           VLOG(2) << "fetch var " << name << "type float";
-          model._float_value_map[name].resize(
-              output.insts(0).tensor_array(idx).float_data_size());
           int size = output.insts(0).tensor_array(idx).float_data_size();
-          for (int i = 0; i < size; ++i) {
-            model._float_value_map[name][i] =
-                output.insts(0).tensor_array(idx).float_data(i);
-          }
+          model._float_value_map[name] = std::vector<float>(
+              output.insts(0).tensor_array(idx).float_data().begin(),
+              output.insts(0).tensor_array(idx).float_data().begin() + size);
         }
         idx += 1;
       }

python/paddle_serving_client/__init__.py

@@ -391,7 +391,13 @@ class MultiLangClient(object):
         self._parse_model_config(path)
 
     def connect(self, endpoint):
-        self.channel_ = grpc.insecure_channel(endpoint[0])  #TODO
+        # https://github.com/tensorflow/serving/issues/1382
+        options = [('grpc.max_receive_message_length', 512 * 1024 * 1024),
+                   ('grpc.max_send_message_length', 512 * 1024 * 1024),
+                   ('grpc.max_receive_message_length', 512 * 1024 * 1024)]
+
+        self.channel_ = grpc.insecure_channel(
+            endpoint[0], options=options)  #TODO
         self.stub_ = multi_lang_general_model_service_pb2_grpc.MultiLangGeneralModelServiceStub(
             self.channel_)