bug fix

core/general-client/src/general_model.cpp

@@ -108,7 +108,6 @@ void PredictorClient::set_predictor_conf(const std::string &conf_path,
   _predictor_path = conf_path;
   _predictor_conf = conf_file;
 }
-
 int PredictorClient::destroy_predictor() {
   _api.thrd_finalize();
   _api.destroy();
@@ -160,6 +159,7 @@ int PredictorClient::batch_predict(
   VLOG(2) << "fetch general model predictor done.";
   VLOG(2) << "float feed name size: " << float_feed_name.size();
   VLOG(2) << "int feed name size: " << int_feed_name.size();
+  VLOG(2) << "max body size : " << brpc::fLU64::FLAGS_max_body_size;
   Request req;
   for (auto &name : fetch_name) {
     req.add_fetch_var_names(name);
@@ -179,12 +179,16 @@ int PredictorClient::batch_predict(
       tensor_vec.push_back(inst->add_tensor_array());
     }
 
-    VLOG(2) << "batch [" << bi << "] int_feed_name and float_feed_name"
+    VLOG(2) << "batch [" << bi << "] int_feed_name and float_feed_name "
             << "prepared";
     int vec_idx = 0;
+    VLOG(2) << "tensor_vec size " << tensor_vec.size() << " float shape "
+            << float_shape.size();
     for (auto &name : float_feed_name) {
       int idx = _feed_name_to_idx[name];
       Tensor *tensor = tensor_vec[idx];
+      VLOG(2) << "prepare float feed " << name << " shape size "
+              << float_shape[vec_idx].size();
       for (int j = 0; j < float_shape[vec_idx].size(); ++j) {
         tensor->add_shape(float_shape[vec_idx][j]);
       }
@@ -202,6 +206,8 @@ int PredictorClient::batch_predict(
     for (auto &name : int_feed_name) {
       int idx = _feed_name_to_idx[name];
       Tensor *tensor = tensor_vec[idx];
+      VLOG(2) << "prepare int feed " << name << " shape size "
+              << int_shape[vec_idx].size();
       for (int j = 0; j < int_shape[vec_idx].size(); ++j) {
         tensor->add_shape(int_shape[vec_idx][j]);
       }
@@ -243,8 +249,11 @@ int PredictorClient::batch_predict(
     postprocess_start = client_infer_end;
 
     for (auto &name : fetch_name) {
-      int idx = _fetch_name_to_idx[name];
+      // int idx = _fetch_name_to_idx[name];
+      int idx = 0;
       int shape_size = res.insts(0).tensor_array(idx).shape_size();
+      VLOG(2) << "fetch var " << name << " index " << idx << " shape size "
+              << shape_size;
       predict_res_batch._shape_map[name].resize(shape_size);
       for (int i = 0; i < shape_size; ++i) {
         predict_res_batch._shape_map[name][i] =
@@ -258,11 +267,14 @@ int PredictorClient::batch_predict(
               res.insts(0).tensor_array(idx).lod(i);
         }
       }
+      idx += 1;
     }
 
     for (auto &name : fetch_name) {
-      int idx = _fetch_name_to_idx[name];
+      // int idx = _fetch_name_to_idx[name];
+      int idx = 0;
       if (_fetch_name_to_type[name] == 0) {
+        VLOG(2) << "ferch var " << name << "type int";
         predict_res_batch._int64_value_map[name].resize(
             res.insts(0).tensor_array(idx).int64_data_size());
         int size = res.insts(0).tensor_array(idx).int64_data_size();
@@ -271,6 +283,7 @@ int PredictorClient::batch_predict(
               res.insts(0).tensor_array(idx).int64_data(i);
         }
       } else {
+        VLOG(2) << "fetch var " << name << "type float";
         predict_res_batch._float_value_map[name].resize(
             res.insts(0).tensor_array(idx).float_data_size());
         int size = res.insts(0).tensor_array(idx).float_data_size();
@@ -279,6 +292,7 @@ int PredictorClient::batch_predict(
               res.insts(0).tensor_array(idx).float_data(i);
         }
       }
+      idx += 1;
     }
     postprocess_end = timeline.TimeStampUS();
   }

core/general-server/op/general_response_op.cpp

@@ -64,6 +64,8 @@ int GeneralResponseOp::inference() {
   std::shared_ptr<PaddleGeneralModelConfig> model_config =
       resource.get_general_model_config();
 
+  VLOG(2) << "max body size : " << brpc::fLU64::FLAGS_max_body_size;
+
   std::vector<int> fetch_index;
   fetch_index.resize(req->fetch_var_names_size());
   for (int i = 0; i < req->fetch_var_names_size(); ++i) {

python/paddle_serving_client/__init__.py

@@ -111,6 +111,8 @@ class Client(object):
         self.result_handle_ = PredictorRes()
         self.client_handle_ = PredictorClient()
         self.client_handle_.init(path)
+        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)])
@@ -223,8 +225,6 @@ class Client(object):
         for i, feed_i in enumerate(feed_batch):
             int_slot = []
             float_slot = []
-            int_shape = []
-            float_shape = []
             for key in feed_i:
                 if key not in self.feed_names_:
                     raise ValueError("Wrong feed name: {}.".format(key))

python/paddle_serving_server/serve.py

@@ -44,7 +44,7 @@ def parse_args():  # pylint: disable=doc-string-missing
     parser.add_argument(
         "--max_body_size",
         type=int,
-        default=64 * 1024 * 1024,
+        default=512 * 1024 * 1024,
         help="Limit sizes of messages")
     return parser.parse_args()