fix general reader infer batch size problem

core/general-server/op/general_infer_op.cpp

@@ -36,8 +36,9 @@ using baidu::paddle_serving::predictor::InferManager;
 using baidu::paddle_serving::predictor::PaddleGeneralModelConfig;
 
 int GeneralInferOp::inference() {
+  VLOG(2) << "Going to run inference";
   const GeneralBlob *input_blob = get_depend_argument<GeneralBlob>(pre_name());
-
+  VLOG(2) << "Get precedent op name: " << pre_name();
   GeneralBlob *output_blob = mutable_data<GeneralBlob>();
 
   if (!input_blob) {
@@ -48,6 +49,8 @@ int GeneralInferOp::inference() {
   const TensorVector *in = &input_blob->tensor_vector;
   TensorVector *out = &output_blob->tensor_vector;
   int batch_size = input_blob->GetBatchSize();
+  VLOG(2) << "input batch size: " << batch_size;
+
   output_blob->SetBatchSize(batch_size);
 
   VLOG(2) << "infer batch size: " << batch_size;

core/general-server/op/general_text_reader_op.cpp

@@ -45,7 +45,9 @@ int GeneralTextReaderOp::inference() {
   std::vector<int64_t> capacity;
 
   GeneralBlob *res = mutable_data<GeneralBlob>();
-  TensorVector *in = &res->tensor_vector;
+  TensorVector *out = &res->tensor_vector;
+
+  res->SetBatchSize(batch_size);
 
   if (!res) {
     LOG(ERROR) << "Failed get op tls reader object output";
@@ -103,23 +105,23 @@ int GeneralTextReaderOp::inference() {
       VLOG(2) << "var[" << i << "] is tensor, capacity: " << capacity[i];
     }
     lod_tensor.name = model_config->_feed_name[i];
-    in->push_back(lod_tensor);
+    out->push_back(lod_tensor);
   }
 
   for (int i = 0; i < var_num; ++i) {
-    if (in->at(i).lod.size() == 1) {
+    if (out->at(i).lod.size() == 1) {
       for (int j = 0; j < batch_size; ++j) {
         const Tensor &tensor = req->insts(j).tensor_array(i);
         int data_len = tensor.int_data_size();
-        int cur_len = in->at(i).lod[0].back();
-        in->at(i).lod[0].push_back(cur_len + data_len);
+        int cur_len = out->at(i).lod[0].back();
+        out->at(i).lod[0].push_back(cur_len + data_len);
       }
-      in->at(i).data.Resize(in->at(i).lod[0].back() * elem_size[i]);
-      in->at(i).shape = {in->at(i).lod[0].back(), 1};
+      out->at(i).data.Resize(out->at(i).lod[0].back() * elem_size[i]);
+      out->at(i).shape = {out->at(i).lod[0].back(), 1};
       VLOG(2) << "var[" << i
-              << "] is lod_tensor and len=" << in->at(i).lod[0].back();
+              << "] is lod_tensor and len=" << out->at(i).lod[0].back();
     } else {
-      in->at(i).data.Resize(batch_size * capacity[i] * elem_size[i]);
+      out->at(i).data.Resize(batch_size * capacity[i] * elem_size[i]);
       VLOG(2) << "var[" << i
               << "] is tensor and capacity=" << batch_size * capacity[i];
     }
@@ -127,7 +129,7 @@ int GeneralTextReaderOp::inference() {
 
   for (int i = 0; i < var_num; ++i) {
     if (elem_type[i] == 0) {
-      int64_t *dst_ptr = static_cast<int64_t *>(in->at(i).data.data());
+      int64_t *dst_ptr = static_cast<int64_t *>(out->at(i).data.data());
       int offset = 0;
       for (int j = 0; j < batch_size; ++j) {
         for (int k = 0;
@@ -136,14 +138,14 @@ int GeneralTextReaderOp::inference() {
           dst_ptr[offset + k] =
               req->insts(j).tensor_array(i).int_data(k);
         }
-        if (in->at(i).lod.size() == 1) {
-          offset = in->at(i).lod[0][j + 1];
+        if (out->at(i).lod.size() == 1) {
+          offset = out->at(i).lod[0][j + 1];
         } else {
           offset += capacity[i];
         }
       }
     } else {
-      float *dst_ptr = static_cast<float *>(in->at(i).data.data());
+      float *dst_ptr = static_cast<float *>(out->at(i).data.data());
       int offset = 0;
       for (int j = 0; j < batch_size; ++j) {
         for (int k = 0;
@@ -152,8 +154,8 @@ int GeneralTextReaderOp::inference() {
           dst_ptr[offset + k] =
               req->insts(j).tensor_array(i).int_data(k);
         }
-        if (in->at(i).lod.size() == 1) {
-          offset = in->at(i).lod[0][j + 1];
+        if (out->at(i).lod.size() == 1) {
+          offset = out->at(i).lod[0][j + 1];
         } else {
           offset += capacity[i];
         }
@@ -162,6 +164,7 @@ int GeneralTextReaderOp::inference() {
   }
 
   int64_t end = timeline.TimeStampUS();
+  res->p_size = 0;
   AddBlobInfo(res, start);
   AddBlobInfo(res, end);