fix response op

core/general-server/op/general_reader_op.cpp

@@ -168,7 +168,7 @@ int GeneralReaderOp::inference() {
         int cur_len = out->at(i).lod[0].back();
         VLOG(2) << "current len: " << cur_len;
 
-        int sample_len;
+        int sample_len = 0;
         if (tensor.shape_size() == 1) {
           sample_len = data_len;
         } else {

core/general-server/op/general_response_op.cpp

@@ -15,8 +15,10 @@
 #include "core/general-server/op/general_response_op.h"
 #include <algorithm>
 #include <iostream>
+#include <map>
 #include <memory>
 #include <sstream>
+#include <utility>
 #include "core/general-server/op/general_infer_helper.h"
 #include "core/predictor/framework/infer.h"
 #include "core/predictor/framework/memory.h"
@@ -86,37 +88,51 @@ int GeneralResponseOp::inference() {
     // To get the order of model return values
     output->set_engine_name(pre_name);
     FetchInst *fetch_inst = output->add_insts();
+
+    std::map<std::string, int> fetch_index_map;
+    for (int i = 0; i < in->size(); ++i) {
+      VLOG(2) << "index " << i << " var " << in->at(i).name;
+      fetch_index_map.insert(std::pair<std::string, int>(in->at(i).name, i));
+    }
+
     for (auto &idx : fetch_index) {
       Tensor *tensor = fetch_inst->add_tensor_array();
       tensor->set_elem_type(1);
+      int true_idx = fetch_index_map[model_config->_fetch_name[idx]];
       if (model_config->_is_lod_fetch[idx]) {
-        VLOG(2) << "out[" << idx << "] is lod_tensor";
-        for (int k = 0; k < in->at(idx).shape.size(); ++k) {
+        VLOG(2) << "out[" << idx << "] " << model_config->_fetch_name[idx]
+                << " is lod_tensor";
+        for (int k = 0; k < in->at(true_idx).shape.size(); ++k) {
           VLOG(2) << "shape[" << k << "]: " << in->at(idx).shape[k];
-          tensor->add_shape(in->at(idx).shape[k]);
+          tensor->add_shape(in->at(true_idx).shape[k]);
         }
       } else {
-        VLOG(2) << "out[" << idx << "] is tensor";
-        for (int k = 0; k < in->at(idx).shape.size(); ++k) {
-          VLOG(2) << "shape[" << k << "]: " << in->at(idx).shape[k];
-          tensor->add_shape(in->at(idx).shape[k]);
+        VLOG(2) << "out[" << idx << "] " << model_config->_fetch_name[idx]
+                << " is tensor";
+        for (int k = 0; k < in->at(true_idx).shape.size(); ++k) {
+          VLOG(2) << "shape[" << k << "]: " << in->at(true_idx).shape[k];
+          tensor->add_shape(in->at(true_idx).shape[k]);
         }
       }
     }
 
     int var_idx = 0;
     for (auto &idx : fetch_index) {
+      int true_idx = fetch_index_map[model_config->_fetch_name[idx]];
       int cap = 1;
-      for (int j = 0; j < in->at(idx).shape.size(); ++j) {
-        cap *= in->at(idx).shape[j];
-      }
-      if (in->at(idx).dtype == paddle::PaddleDType::INT64) {
-        int64_t *data_ptr = static_cast<int64_t *>(in->at(idx).data.data());
+      for (int j = 0; j < in->at(true_idx).shape.size(); ++j) {
+        cap *= in->at(true_idx).shape[j];
+      }
+      if (in->at(true_idx).dtype == paddle::PaddleDType::INT64) {
+        VLOG(2) << "Prepare float var [" << model_config->_fetch_name[idx]
+                << "].";
+        int64_t *data_ptr =
+            static_cast<int64_t *>(in->at(true_idx).data.data());
         if (model_config->_is_lod_fetch[idx]) {
           FetchInst *fetch_p = output->mutable_insts(0);
-          for (int j = 0; j < in->at(idx).lod[0].size(); ++j) {
+          for (int j = 0; j < in->at(true_idx).lod[0].size(); ++j) {
             fetch_p->mutable_tensor_array(var_idx)->add_lod(
-                in->at(idx).lod[0][j]);
+                in->at(true_idx).lod[0][j]);
           }
           for (int j = 0; j < cap; ++j) {
             fetch_p->mutable_tensor_array(var_idx)->add_int64_data(data_ptr[j]);
@@ -127,14 +143,17 @@ int GeneralResponseOp::inference() {
             fetch_p->mutable_tensor_array(var_idx)->add_int64_data(data_ptr[j]);
           }
         }
+        VLOG(2) << "fetch var [" << model_config->_fetch_name[idx] << "] ready";
         var_idx++;
-      } else if (in->at(idx).dtype == paddle::PaddleDType::FLOAT32) {
-        float *data_ptr = static_cast<float *>(in->at(idx).data.data());
+      } else if (in->at(true_idx).dtype == paddle::PaddleDType::FLOAT32) {
+        VLOG(2) << "Prepare float var [" << model_config->_fetch_name[idx]
+                << "].";
+        float *data_ptr = static_cast<float *>(in->at(true_idx).data.data());
         if (model_config->_is_lod_fetch[idx]) {
           FetchInst *fetch_p = output->mutable_insts(0);
-          for (int j = 0; j < in->at(idx).lod[0].size(); ++j) {
+          for (int j = 0; j < in->at(true_idx).lod[0].size(); ++j) {
             fetch_p->mutable_tensor_array(var_idx)->add_lod(
-                in->at(idx).lod[0][j]);
+                in->at(true_idx).lod[0][j]);
           }
           for (int j = 0; j < cap; ++j) {
             fetch_p->mutable_tensor_array(var_idx)->add_float_data(data_ptr[j]);
@@ -145,6 +164,7 @@ int GeneralResponseOp::inference() {
             fetch_p->mutable_tensor_array(var_idx)->add_float_data(data_ptr[j]);
           }
         }
+        VLOG(2) << "fetch var [" << model_config->_fetch_name[idx] << "] ready";
         var_idx++;
       }
     }