add cpp serving infer(except PPShiTu)

deploy/paddleserving/build_server.sh

@@ -0,0 +1,74 @@
+#使用镜像：
+#registry.baidubce.com/paddlepaddle/paddle:latest-dev-cuda10.1-cudnn7-gcc82
+
+#编译Serving Server：
+
+#client和app可以直接使用release版本
+
+#server因为加入了自定义OP，需要重新编译
+
+#默认编译时的${PWD}=PaddleClas/deploy/paddleserving/
+
+python_name=${1:-'python'}
+
+apt-get update
+apt install -y libcurl4-openssl-dev libbz2-dev
+wget https://paddle-serving.bj.bcebos.com/others/centos_ssl.tar && tar xf centos_ssl.tar && rm -rf centos_ssl.tar && mv libcrypto.so.1.0.2k /usr/lib/libcrypto.so.1.0.2k && mv libssl.so.1.0.2k /usr/lib/libssl.so.1.0.2k && ln -sf /usr/lib/libcrypto.so.1.0.2k /usr/lib/libcrypto.so.10 && ln -sf /usr/lib/libssl.so.1.0.2k /usr/lib/libssl.so.10 && ln -sf /usr/lib/libcrypto.so.10 /usr/lib/libcrypto.so && ln -sf /usr/lib/libssl.so.10 /usr/lib/libssl.so
+
+# 安装go依赖
+rm -rf /usr/local/go
+wget -qO- https://paddle-ci.cdn.bcebos.com/go1.17.2.linux-amd64.tar.gz | tar -xz -C /usr/local
+export GOROOT=/usr/local/go
+export GOPATH=/root/gopath
+export PATH=$PATH:$GOPATH/bin:$GOROOT/bin
+go env -w GO111MODULE=on
+go env -w GOPROXY=https://goproxy.cn,direct
+go install github.com/grpc-ecosystem/grpc-gateway/protoc-gen-grpc-gateway@v1.15.2
+go install github.com/grpc-ecosystem/grpc-gateway/protoc-gen-swagger@v1.15.2
+go install github.com/golang/protobuf/protoc-gen-go@v1.4.3
+go install google.golang.org/grpc@v1.33.0
+go env -w GO111MODULE=auto
+
+# 下载opencv库
+wget https://paddle-qa.bj.bcebos.com/PaddleServing/opencv3.tar.gz && tar -xvf opencv3.tar.gz && rm -rf opencv3.tar.gz
+export OPENCV_DIR=$PWD/opencv3
+
+# clone Serving
+git clone https://github.com/PaddlePaddle/Serving.git -b develop --depth=1
+cd Serving # PaddleClas/deploy/paddleserving/Serving
+export Serving_repo_path=$PWD
+git submodule update --init --recursive
+${python_name} -m pip install -r python/requirements.txt
+
+# set env
+export PYTHON_INCLUDE_DIR=$(${python_name} -c "from distutils.sysconfig import get_python_inc; print(get_python_inc())")
+export PYTHON_LIBRARIES=$(${python_name} -c "import distutils.sysconfig as sysconfig; print(sysconfig.get_config_var('LIBDIR'))")
+export PYTHON_EXECUTABLE=`which ${python_name}`
+
+export CUDA_PATH='/usr/local/cuda'
+export CUDNN_LIBRARY='/usr/local/cuda/lib64/'
+export CUDA_CUDART_LIBRARY='/usr/local/cuda/lib64/'
+export TENSORRT_LIBRARY_PATH='/usr/local/TensorRT6-cuda10.1-cudnn7/targets/x86_64-linux-gnu/'
+
+# cp 自定义OP代码
+\cp ../preprocess/general_clas_op.* ${Serving_repo_path}/core/general-server/op
+\cp ../preprocess/preprocess_op.* ${Serving_repo_path}/core/predictor/tools/pp_shitu_tools
+
+# 编译Server, export SERVING_BIN
+mkdir server-build-gpu-opencv && cd server-build-gpu-opencv
+cmake -DPYTHON_INCLUDE_DIR=$PYTHON_INCLUDE_DIR \
+            -DPYTHON_LIBRARIES=$PYTHON_LIBRARIES \
+            -DPYTHON_EXECUTABLE=$PYTHON_EXECUTABLE \
+            -DCUDA_TOOLKIT_ROOT_DIR=${CUDA_PATH} \
+            -DCUDNN_LIBRARY=${CUDNN_LIBRARY} \
+            -DCUDA_CUDART_LIBRARY=${CUDA_CUDART_LIBRARY} \
+            -DTENSORRT_ROOT=${TENSORRT_LIBRARY_PATH} \
+            -DOPENCV_DIR=${OPENCV_DIR} \
+            -DWITH_OPENCV=ON \
+            -DSERVER=ON \
+            -DWITH_GPU=ON ..
+make -j32
+
+${python_name} -m pip install python/dist/paddle*
+export SERVING_BIN=$PWD/core/general-server/serving
+cd ../../

deploy/paddleserving/preprocess/general_clas_op.cpp

@@ -0,0 +1,206 @@
+// 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.
+
+#include "core/general-server/op/general_clas_op.h"
+#include "core/predictor/framework/infer.h"
+#include "core/predictor/framework/memory.h"
+#include "core/predictor/framework/resource.h"
+#include "core/util/include/timer.h"
+#include <algorithm>
+#include <iostream>
+#include <memory>
+#include <sstream>
+
+namespace baidu {
+namespace paddle_serving {
+namespace serving {
+
+using baidu::paddle_serving::Timer;
+using baidu::paddle_serving::predictor::MempoolWrapper;
+using baidu::paddle_serving::predictor::general_model::Tensor;
+using baidu::paddle_serving::predictor::general_model::Response;
+using baidu::paddle_serving::predictor::general_model::Request;
+using baidu::paddle_serving::predictor::InferManager;
+using baidu::paddle_serving::predictor::PaddleGeneralModelConfig;
+
+int GeneralClasOp::inference() {
+  VLOG(2) << "Going to run inference";
+  const std::vector<std::string> pre_node_names = pre_names();
+  if (pre_node_names.size() != 1) {
+    LOG(ERROR) << "This op(" << op_name()
+               << ") can only have one predecessor op, but received "
+               << pre_node_names.size();
+    return -1;
+  }
+  const std::string pre_name = pre_node_names[0];
+
+  const GeneralBlob *input_blob = get_depend_argument<GeneralBlob>(pre_name);
+  if (!input_blob) {
+    LOG(ERROR) << "input_blob is nullptr,error";
+    return -1;
+  }
+  uint64_t log_id = input_blob->GetLogId();
+  VLOG(2) << "(logid=" << log_id << ") Get precedent op name: " << pre_name;
+
+  GeneralBlob *output_blob = mutable_data<GeneralBlob>();
+  if (!output_blob) {
+    LOG(ERROR) << "output_blob is nullptr,error";
+    return -1;
+  }
+  output_blob->SetLogId(log_id);
+
+  if (!input_blob) {
+    LOG(ERROR) << "(logid=" << log_id
+               << ") Failed mutable depended argument, op:" << pre_name;
+    return -1;
+  }
+
+  const TensorVector *in = &input_blob->tensor_vector;
+  TensorVector *out = &output_blob->tensor_vector;
+
+  int batch_size = input_blob->_batch_size;
+  output_blob->_batch_size = batch_size;
+  VLOG(2) << "(logid=" << log_id << ") infer batch size: " << batch_size;
+
+  Timer timeline;
+  int64_t start = timeline.TimeStampUS();
+  timeline.Start();
+
+  // only support string type
+
+  char *total_input_ptr = static_cast<char *>(in->at(0).data.data());
+  std::string base64str = total_input_ptr;
+
+  cv::Mat img = Base2Mat(base64str);
+
+  // RGB2BGR
+  cv::cvtColor(img, img, cv::COLOR_BGR2RGB);
+
+  // Resize
+  cv::Mat resize_img;
+  resize_op_.Run(img, resize_img, resize_short_size_);
+
+  // CenterCrop
+  crop_op_.Run(resize_img, crop_size_);
+
+  // Normalize
+  normalize_op_.Run(&resize_img, mean_, scale_, is_scale_);
+
+  // Permute
+  std::vector<float> input(1 * 3 * resize_img.rows * resize_img.cols, 0.0f);
+  permute_op_.Run(&resize_img, input.data());
+  float maxValue = *max_element(input.begin(), input.end());
+  float minValue = *min_element(input.begin(), input.end());
+
+  TensorVector *real_in = new TensorVector();
+  if (!real_in) {
+    LOG(ERROR) << "real_in is nullptr,error";
+    return -1;
+  }
+
+  std::vector<int> input_shape;
+  int in_num = 0;
+  void *databuf_data = NULL;
+  char *databuf_char = NULL;
+  size_t databuf_size = 0;
+
+  input_shape = {1, 3, resize_img.rows, resize_img.cols};
+  in_num = std::accumulate(input_shape.begin(), input_shape.end(), 1,
+                           std::multiplies<int>());
+
+  databuf_size = in_num * sizeof(float);
+  databuf_data = MempoolWrapper::instance().malloc(databuf_size);
+  if (!databuf_data) {
+    LOG(ERROR) << "Malloc failed, size: " << databuf_size;
+    return -1;
+  }
+
+  memcpy(databuf_data, input.data(), databuf_size);
+  databuf_char = reinterpret_cast<char *>(databuf_data);
+  paddle::PaddleBuf paddleBuf(databuf_char, databuf_size);
+  paddle::PaddleTensor tensor_in;
+  tensor_in.name = in->at(0).name;
+  tensor_in.dtype = paddle::PaddleDType::FLOAT32;
+  tensor_in.shape = {1, 3, resize_img.rows, resize_img.cols};
+  tensor_in.lod = in->at(0).lod;
+  tensor_in.data = paddleBuf;
+  real_in->push_back(tensor_in);
+
+  if (InferManager::instance().infer(engine_name().c_str(), real_in, out,
+                                     batch_size)) {
+    LOG(ERROR) << "(logid=" << log_id
+               << ") Failed do infer in fluid model: " << engine_name().c_str();
+    return -1;
+  }
+
+  int64_t end = timeline.TimeStampUS();
+  CopyBlobInfo(input_blob, output_blob);
+  AddBlobInfo(output_blob, start);
+  AddBlobInfo(output_blob, end);
+  return 0;
+}
+
+cv::Mat GeneralClasOp::Base2Mat(std::string &base64_data) {
+  cv::Mat img;
+  std::string s_mat;
+  s_mat = base64Decode(base64_data.data(), base64_data.size());
+  std::vector<char> base64_img(s_mat.begin(), s_mat.end());
+  img = cv::imdecode(base64_img, cv::IMREAD_COLOR); // CV_LOAD_IMAGE_COLOR
+  return img;
+}
+
+std::string GeneralClasOp::base64Decode(const char *Data, int DataByte) {
+  const char DecodeTable[] = {
+      0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,
+      0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,
+      0,  0,  0,  0,  0,  0,  0,  0,  0,
+      62, // '+'
+      0,  0,  0,
+      63,                                     // '/'
+      52, 53, 54, 55, 56, 57, 58, 59, 60, 61, // '0'-'9'
+      0,  0,  0,  0,  0,  0,  0,  0,  1,  2,  3,  4,  5,  6,  7,  8,  9,
+      10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, // 'A'-'Z'
+      0,  0,  0,  0,  0,  0,  26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,
+      37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, // 'a'-'z'
+  };
+
+  std::string strDecode;
+  int nValue;
+  int i = 0;
+  while (i < DataByte) {
+    if (*Data != '\r' && *Data != '\n') {
+      nValue = DecodeTable[*Data++] << 18;
+      nValue += DecodeTable[*Data++] << 12;
+      strDecode += (nValue & 0x00FF0000) >> 16;
+      if (*Data != '=') {
+        nValue += DecodeTable[*Data++] << 6;
+        strDecode += (nValue & 0x0000FF00) >> 8;
+        if (*Data != '=') {
+          nValue += DecodeTable[*Data++];
+          strDecode += nValue & 0x000000FF;
+        }
+      }
+      i += 4;
+    } else // 回车换行,跳过
+    {
+      Data++;
+      i++;
+    }
+  }
+  return strDecode;
+}
+DEFINE_OP(GeneralClasOp);
+} // namespace serving
+} // namespace paddle_serving
+} // namespace baidu

deploy/paddleserving/preprocess/general_clas_op.h

@@ -0,0 +1,70 @@
+// Copyright (c) 2019 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.
+
+#pragma once
+#include "core/general-server/general_model_service.pb.h"
+#include "core/general-server/op/general_infer_helper.h"
+#include "core/predictor/tools/pp_shitu_tools/preprocess_op.h"
+#include "paddle_inference_api.h" // NOLINT
+#include <string>
+#include <vector>
+
+#include "opencv2/core.hpp"
+#include "opencv2/imgcodecs.hpp"
+#include "opencv2/imgproc.hpp"
+#include <chrono>
+#include <iomanip>
+#include <iostream>
+#include <ostream>
+#include <vector>
+
+#include <cstring>
+#include <fstream>
+#include <numeric>
+
+namespace baidu {
+namespace paddle_serving {
+namespace serving {
+
+class GeneralClasOp
+    : public baidu::paddle_serving::predictor::OpWithChannel<GeneralBlob> {
+public:
+  typedef std::vector<paddle::PaddleTensor> TensorVector;
+
+  DECLARE_OP(GeneralClasOp);
+
+  int inference();
+
+private:
+  // clas preprocess
+  std::vector<float> mean_ = {0.485f, 0.456f, 0.406f};
+  std::vector<float> scale_ = {0.229f, 0.224f, 0.225f};
+  bool is_scale_ = true;
+
+  int resize_short_size_ = 256;
+  int crop_size_ = 224;
+
+  PaddleClas::ResizeImg resize_op_;
+  PaddleClas::Normalize normalize_op_;
+  PaddleClas::Permute permute_op_;
+  PaddleClas::CenterCropImg crop_op_;
+
+  // read pics
+  cv::Mat Base2Mat(std::string &base64_data);
+  std::string base64Decode(const char *Data, int DataByte);
+};
+
+} // namespace serving
+} // namespace paddle_serving
+} // namespace baidu

deploy/paddleserving/preprocess/preprocess_op.cpp

@@ -0,0 +1,149 @@
+// 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.
+
+#include "opencv2/core.hpp"
+#include "opencv2/imgcodecs.hpp"
+#include "opencv2/imgproc.hpp"
+#include "paddle_api.h"
+#include "paddle_inference_api.h"
+#include <chrono>
+#include <iomanip>
+#include <iostream>
+#include <ostream>
+#include <vector>
+
+#include <cstring>
+#include <fstream>
+#include <math.h>
+#include <numeric>
+
+#include "preprocess_op.h"
+
+namespace Feature {
+
+void Permute::Run(const cv::Mat *im, float *data) {
+  int rh = im->rows;
+  int rw = im->cols;
+  int rc = im->channels();
+  for (int i = 0; i < rc; ++i) {
+    cv::extractChannel(*im, cv::Mat(rh, rw, CV_32FC1, data + i * rh * rw), i);
+  }
+}
+
+void Normalize::Run(cv::Mat *im, const std::vector<float> &mean,
+                    const std::vector<float> &std, float scale) {
+  (*im).convertTo(*im, CV_32FC3, scale);
+  for (int h = 0; h < im->rows; h++) {
+    for (int w = 0; w < im->cols; w++) {
+      im->at<cv::Vec3f>(h, w)[0] =
+          (im->at<cv::Vec3f>(h, w)[0] - mean[0]) / std[0];
+      im->at<cv::Vec3f>(h, w)[1] =
+          (im->at<cv::Vec3f>(h, w)[1] - mean[1]) / std[1];
+      im->at<cv::Vec3f>(h, w)[2] =
+          (im->at<cv::Vec3f>(h, w)[2] - mean[2]) / std[2];
+    }
+  }
+}
+
+void CenterCropImg::Run(cv::Mat &img, const int crop_size) {
+  int resize_w = img.cols;
+  int resize_h = img.rows;
+  int w_start = int((resize_w - crop_size) / 2);
+  int h_start = int((resize_h - crop_size) / 2);
+  cv::Rect rect(w_start, h_start, crop_size, crop_size);
+  img = img(rect);
+}
+
+void ResizeImg::Run(const cv::Mat &img, cv::Mat &resize_img,
+                    int resize_short_size, int size) {
+  int resize_h = 0;
+  int resize_w = 0;
+  if (size > 0) {
+    resize_h = size;
+    resize_w = size;
+  } else {
+    int w = img.cols;
+    int h = img.rows;
+
+    float ratio = 1.f;
+    if (h < w) {
+      ratio = float(resize_short_size) / float(h);
+    } else {
+      ratio = float(resize_short_size) / float(w);
+    }
+    resize_h = round(float(h) * ratio);
+    resize_w = round(float(w) * ratio);
+  }
+  cv::resize(img, resize_img, cv::Size(resize_w, resize_h));
+}
+
+} // namespace Feature
+
+namespace PaddleClas {
+void Permute::Run(const cv::Mat *im, float *data) {
+  int rh = im->rows;
+  int rw = im->cols;
+  int rc = im->channels();
+  for (int i = 0; i < rc; ++i) {
+    cv::extractChannel(*im, cv::Mat(rh, rw, CV_32FC1, data + i * rh * rw), i);
+  }
+}
+
+void Normalize::Run(cv::Mat *im, const std::vector<float> &mean,
+                    const std::vector<float> &scale, const bool is_scale) {
+  double e = 1.0;
+  if (is_scale) {
+    e /= 255.0;
+  }
+  (*im).convertTo(*im, CV_32FC3, e);
+  for (int h = 0; h < im->rows; h++) {
+    for (int w = 0; w < im->cols; w++) {
+      im->at<cv::Vec3f>(h, w)[0] =
+          (im->at<cv::Vec3f>(h, w)[0] - mean[0]) / scale[0];
+      im->at<cv::Vec3f>(h, w)[1] =
+          (im->at<cv::Vec3f>(h, w)[1] - mean[1]) / scale[1];
+      im->at<cv::Vec3f>(h, w)[2] =
+          (im->at<cv::Vec3f>(h, w)[2] - mean[2]) / scale[2];
+    }
+  }
+}
+
+void CenterCropImg::Run(cv::Mat &img, const int crop_size) {
+  int resize_w = img.cols;
+  int resize_h = img.rows;
+  int w_start = int((resize_w - crop_size) / 2);
+  int h_start = int((resize_h - crop_size) / 2);
+  cv::Rect rect(w_start, h_start, crop_size, crop_size);
+  img = img(rect);
+}
+
+void ResizeImg::Run(const cv::Mat &img, cv::Mat &resize_img,
+                    int resize_short_size) {
+  int w = img.cols;
+  int h = img.rows;
+
+  float ratio = 1.f;
+  if (h < w) {
+    ratio = float(resize_short_size) / float(h);
+  } else {
+    ratio = float(resize_short_size) / float(w);
+  }
+
+  int resize_h = round(float(h) * ratio);
+  int resize_w = round(float(w) * ratio);
+
+  cv::resize(img, resize_img, cv::Size(resize_w, resize_h));
+}
+
+} // namespace PaddleClas

deploy/paddleserving/preprocess/preprocess_op.h

@@ -0,0 +1,81 @@
+// 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.
+
+#pragma once
+
+#include "opencv2/core.hpp"
+#include "opencv2/imgcodecs.hpp"
+#include "opencv2/imgproc.hpp"
+#include <chrono>
+#include <iomanip>
+#include <iostream>
+#include <ostream>
+#include <vector>
+
+#include <cstring>
+#include <fstream>
+#include <numeric>
+
+namespace Feature {
+
+class Normalize {
+public:
+  virtual void Run(cv::Mat *im, const std::vector<float> &mean,
+                   const std::vector<float> &std, float scale);
+};
+
+// RGB -> CHW
+class Permute {
+public:
+  virtual void Run(const cv::Mat *im, float *data);
+};
+
+class CenterCropImg {
+public:
+  virtual void Run(cv::Mat &im, const int crop_size = 224);
+};
+
+class ResizeImg {
+public:
+  virtual void Run(const cv::Mat &img, cv::Mat &resize_img, int max_size_len,
+                   int size = 0);
+};
+
+} // namespace Feature
+
+namespace PaddleClas {
+
+class Normalize {
+public:
+  virtual void Run(cv::Mat *im, const std::vector<float> &mean,
+                   const std::vector<float> &scale, const bool is_scale = true);
+};
+
+// RGB -> CHW
+class Permute {
+public:
+  virtual void Run(const cv::Mat *im, float *data);
+};
+
+class CenterCropImg {
+public:
+  virtual void Run(cv::Mat &im, const int crop_size = 224);
+};
+
+class ResizeImg {
+public:
+  virtual void Run(const cv::Mat &img, cv::Mat &resize_img, int max_size_len);
+};
+
+} // namespace PaddleClas

test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

@@ -0,0 +1,14 @@
+===========================serving_params===========================
+model_name:MobileNetV3_large_x1_0
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/MobileNetV3_large_x1_0_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/MobileNetV3_large_x1_0_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/MobileNetV3_large_x1_0_serving/
+--serving_client:./deploy/paddleserving/MobileNetV3_large_x1_0_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPHGNet/PPHGNet_small_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

@@ -0,0 +1,14 @@
+===========================serving_params===========================
+model_name:PPHGNet_small
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNet_small_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPHGNet_small_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPHGNet_small_serving/
+--serving_client:./deploy/paddleserving/PPHGNet_small_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PPHGNet/PPHGNet_tiny_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

@@ -0,0 +1,14 @@
+===========================serving_params===========================
+model_name:PPHGNet_tiny
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNet_tiny_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPHGNet_tiny_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPHGNet_tiny_serving/
+--serving_client:./deploy/paddleserving/PPHGNet_tiny_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PPLCNet/PPLCNet_x0_25_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

@@ -0,0 +1,14 @@
+===========================serving_params===========================
+model_name:PPLCNet_x0_25
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x0_25_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNet_x0_25_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNet_x0_25_serving/
+--serving_client:./deploy/paddleserving/PPLCNet_x0_25_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPLCNet/PPLCNet_x0_35_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

@@ -0,0 +1,14 @@
+===========================serving_params===========================
+model_name:PPLCNet_x0_35
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x0_35_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNet_x0_35_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNet_x0_35_serving/
+--serving_client:./deploy/paddleserving/PPLCNet_x0_35_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPLCNet/PPLCNet_x0_5_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

@@ -0,0 +1,14 @@
+===========================serving_params===========================
+model_name:PPLCNet_x0_5
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x0_5_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNet_x0_5_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNet_x0_5_serving/
+--serving_client:./deploy/paddleserving/PPLCNet_x0_5_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPLCNet/PPLCNet_x0_75_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

@@ -0,0 +1,14 @@
+===========================serving_params===========================
+model_name:PPLCNet_x0_75
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x0_75_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNet_x0_75_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNet_x0_75_serving/
+--serving_client:./deploy/paddleserving/PPLCNet_x0_75_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPLCNet/PPLCNet_x1_0_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

@@ -0,0 +1,14 @@
+===========================serving_params===========================
+model_name:PPLCNet_x1_0
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x1_0_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNet_x1_0_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNet_x1_0_serving/
+--serving_client:./deploy/paddleserving/PPLCNet_x1_0_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPLCNet/PPLCNet_x1_5_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

@@ -0,0 +1,14 @@
+===========================serving_params===========================
+model_name:PPLCNet_x1_5
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x1_5_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNet_x1_5_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNet_x1_5_serving/
+--serving_client:./deploy/paddleserving/PPLCNet_x1_5_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPLCNet/PPLCNet_x2_0_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

@@ -0,0 +1,14 @@
+===========================serving_params===========================
+model_name:PPLCNet_x2_0
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x2_0_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNet_x2_0_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNet_x2_0_serving/
+--serving_client:./deploy/paddleserving/PPLCNet_x2_0_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPLCNet/PPLCNet_x2_5_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

@@ -0,0 +1,14 @@
+===========================serving_params===========================
+model_name:PPLCNet_x2_5
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x2_5_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNet_x2_5_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNet_x2_5_serving/
+--serving_client:./deploy/paddleserving/PPLCNet_x2_5_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPLCNetV2/PPLCNetV2_base_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

@@ -0,0 +1,14 @@
+===========================serving_params===========================
+model_name:PPLCNetV2_base
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNetV2_base_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNetV2_base_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNetV2_base_serving/
+--serving_client:./deploy/paddleserving/PPLCNetV2_base_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/ResNet/ResNet50_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

@@ -0,0 +1,14 @@
+===========================serving_params===========================
+model_name:ResNet50
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/ResNet50_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/ResNet50_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/ResNet50_serving/
+--serving_client:./deploy/paddleserving/ResNet50_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/ResNet/ResNet50_vd_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

@@ -0,0 +1,14 @@
+===========================serving_params===========================
+model_name:ResNet50_vd
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/ResNet50_vd_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/ResNet50_vd_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/ResNet50_vd_serving/
+--serving_client:./deploy/paddleserving/ResNet50_vd_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/SwinTransformer/SwinTransformer_tiny_patch4_window7_224_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

@@ -0,0 +1,14 @@
+===========================serving_params===========================
+model_name:SwinTransformer_tiny_patch4_window7_224
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/SwinTransformer_tiny_patch4_window7_224_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_serving/
+--serving_client:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/prepare.sh

@@ -199,10 +199,16 @@ fi
 
 if [[ ${MODE} = "serving_infer" ]]; then
     # prepare serving env
+    ${python_name} -m pip install paddle_serving_client==0.9.0
+    ${python_name} -m pip install paddle-serving-app==0.9.0
     python_name=$(func_parser_value "${lines[2]}")
-    ${python_name} -m pip install install paddle-serving-server-gpu==0.7.0.post102
+    if [[ ${FILENAME} =~ "cpp" ]]; then
-    ${python_name} -m pip install paddle_serving_client==0.7.0
+        pushd ./deploy/paddleserving
-    ${python_name} -m pip install paddle-serving-app==0.7.0
+        bash build_server.sh
+        popd
+    else
+        ${python_name} -m pip install install paddle-serving-server-gpu==0.9.0.post102
+    fi
     if [[ ${model_name} =~ "ShiTu" ]]; then
         cls_inference_model_url=$(func_parser_value "${lines[3]}")
         cls_tar_name=$(func_get_url_file_name "${cls_inference_model_url}")

test_tipc/test_serving_infer.sh

@@ -50,8 +50,13 @@ function func_serving_cls(){
     set_serving_server=$(func_set_params "${serving_server_key}" "${serving_server_value}")
     set_serving_client=$(func_set_params "${serving_client_key}" "${serving_client_value}")
 
-    trans_model_cmd="${python} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}"
+    for python_ in ${python[*]}; do
-    eval $trans_model_cmd
+        if [[ ${python_} =~ "python" ]]; then
+            trans_model_cmd="${python_} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}"
+            eval $trans_model_cmd
+            break
+        fi
+    done
 
     # modify the alias_name of fetch_var to "outputs"
     server_fetch_var_line_cmd="sed -i '/fetch_var/,/is_lod_tensor/s/alias_name: .*/alias_name: \"prediction\"/' ${serving_server_value}/serving_server_conf.prototxt"
@@ -69,103 +74,124 @@ function func_serving_cls(){
     unset https_proxy
     unset http_proxy
 
-    # modify the input_name in "classification_web_service.py" to be consistent with feed_var.name in prototxt
+    if [[ ${FILENAME} =~ "cpp" ]]; then
-    set_web_service_feet_var_cmd="sed -i '/preprocess/,/input_imgs}/s/{.*: input_imgs}/{${feed_var_name}: input_imgs}/' ${web_service_py}"
+        for item in ${python[*]}; do
-    eval ${set_web_service_feet_var_cmd}
+            if [[ ${item} =~ "python" ]]; then
+                python_=${item}
+                break
+            fi
+        done
+        set_pipeline_py_feed_var_cmd="sed -i '/feed/,/img}/s/{.*: img}/{${feed_var_name}: img}/' ${pipeline_py}"
+        echo $PWD - $set_pipeline_py_feed_var_cmd
+        eval ${set_pipeline_py_feed_var_cmd}
+        serving_server_dir_name=$(func_get_url_file_name "$serving_server_value")
+        set_client_config_line_cmd="sed -i '/client/,/serving_server_conf.prototxt/s/.\/.*\/serving_server_conf.prototxt/.\/${serving_server_dir_name}\/serving_server_conf.prototxt/' ${pipeline_py}"
+        echo $PWD - $set_client_config_line_cmd
+        eval ${set_client_config_line_cmd}
+        for use_gpu in ${web_use_gpu_list[*]}; do
+            if [ ${use_gpu} = "null" ]; then
+                web_service_cpp_cmd="${python_} -m paddle_serving_server.serve --model ${serving_server_dir_name} --port 9292 &"
+                echo $PWD - $web_service_cpp_cmd
+                eval ${web_service_cpp_cmd}
+                sleep 5s
+                _save_log_path="${LOG_PATH}/server_infer_cpp_cpu_pipeline_batchsize_1.log"
+                pipeline_cmd="${python_} test_cpp_serving_client.py > ${_save_log_path} 2>&1 "
+                echo ${pipeline_cmd}
+                eval ${pipeline_cmd}
+                last_status=${PIPESTATUS[0]}
+                eval "cat ${_save_log_path}"
+                status_check ${last_status} "${pipeline_cmd}" "${status_log}" "${model_name}"
+                ps ux | grep -E 'serving_server|pipeline' | awk '{print $2}' | xargs kill -s 9
+                sleep 5s
+            else
+                web_service_cpp_cmd="${python_} -m paddle_serving_server.serve --model ${serving_server_dir_name} --port 9292 --gpu_id=${use_gpu} &"
+                echo $PWD - $web_service_cpp_cmd
+                eval ${web_service_cpp_cmd}
+                sleep 5s
 
-    model_config=21
+                _save_log_path="${LOG_PATH}/server_infer_cpp_gpu_pipeline_batchsize_1.log"
-    serving_server_dir_name=$(func_get_url_file_name "$serving_server_value")
+                pipeline_cmd="${python_} test_cpp_serving_client.py > ${_save_log_path} 2>&1 "
-    set_model_config_cmd="sed -i '${model_config}s/model_config: .*/model_config: ${serving_server_dir_name}/' config.yml"
-    eval ${set_model_config_cmd}
 
-    for python in ${python[*]}; do
+                echo $PWD - $pipeline_cmd
-        if [[ ${python} = "cpp" ]]; then
+                eval $pipeline_cmd
-            for use_gpu in ${web_use_gpu_list[*]}; do
+                last_status=${PIPESTATUS[0]}
-                if [ ${use_gpu} = "null" ]; then
+                eval "cat ${_save_log_path}"
-                    web_service_cpp_cmd="${python} -m paddle_serving_server.serve --model ppocr_det_mobile_2.0_serving/ ppocr_rec_mobile_2.0_serving/ --port 9293"
+                status_check ${last_status} "${pipeline_cmd}" "${status_log}" "${model_name}"
-                    eval $web_service_cmd
+                ps ux | grep -E 'serving_server|pipeline' | awk '{print $2}' | xargs kill -s 9
-                    sleep 5s
+                sleep 5s
-                    _save_log_path="${LOG_PATH}/server_infer_cpp_cpu_pipeline_usemkldnn_False_threads_4_batchsize_1.log"
+            fi
-                    pipeline_cmd="${python} ocr_cpp_client.py ppocr_det_mobile_2.0_client/ ppocr_rec_mobile_2.0_client/"
+        done
+    else
+        # python serving
+        # modify the input_name in "classification_web_service.py" to be consistent with feed_var.name in prototxt
+        set_web_service_feed_var_cmd="sed -i '/preprocess/,/input_imgs}/s/{.*: input_imgs}/{${feed_var_name}: input_imgs}/' ${web_service_py}"
+        eval ${set_web_service_feed_var_cmd}
+
+        model_config=21
+        serving_server_dir_name=$(func_get_url_file_name "$serving_server_value")
+        set_model_config_cmd="sed -i '${model_config}s/model_config: .*/model_config: ${serving_server_dir_name}/' config.yml"
+        eval ${set_model_config_cmd}
+
+        for use_gpu in ${web_use_gpu_list[*]}; do
+            if [[ ${use_gpu} = "null" ]]; then
+                device_type_line=24
+                set_device_type_cmd="sed -i '${device_type_line}s/device_type: .*/device_type: 0/' config.yml"
+                eval $set_device_type_cmd
+
+                devices_line=27
+                set_devices_cmd="sed -i '${devices_line}s/devices: .*/devices: \"\"/' config.yml"
+                eval $set_devices_cmd
+
+                web_service_cmd="${python_} ${web_service_py} &"
+                eval $web_service_cmd
+                sleep 5s
+                for pipeline in ${pipeline_py[*]}; do
+                    _save_log_path="${LOG_PATH}/server_infer_cpu_${pipeline%_client*}_batchsize_1.log"
+                    pipeline_cmd="${python_} ${pipeline} > ${_save_log_path} 2>&1 "
                     eval $pipeline_cmd
-                    status_check $last_status "${pipeline_cmd}" "${status_log}"
+                    last_status=${PIPESTATUS[0]}
+                    eval "cat ${_save_log_path}"
+                    status_check $last_status "${pipeline_cmd}" "${status_log}" "${model_name}"
                     sleep 5s
-                    ps ux | grep -E 'web_service|pipeline' | awk '{print $2}' | xargs kill -s 9
+                done
-                else
+                ps ux | grep -E 'web_service|pipeline' | awk '{print $2}' | xargs kill -s 9
-                    web_service_cpp_cmd="${python} -m paddle_serving_server.serve --model ppocr_det_mobile_2.0_serving/ ppocr_rec_mobile_2.0_serving/ --port 9293 --gpu_id=0"
+            elif [ ${use_gpu} -eq 0 ]; then
-                    eval $web_service_cmd
+                if [[ ${_flag_quant} = "False" ]] && [[ ${precision} =~ "int8" ]]; then
-                    sleep 5s
+                    continue
-                    _save_log_path="${LOG_PATH}/server_infer_cpp_cpu_pipeline_usemkldnn_False_threads_4_batchsize_1.log"
+                fi
-                    pipeline_cmd="${python} ocr_cpp_client.py ppocr_det_mobile_2.0_client/ ppocr_rec_mobile_2.0_client/"
+                if [[ ${precision} =~ "fp16" || ${precision} =~ "int8" ]] && [ ${use_trt} = "False" ]; then
+                    continue
+                fi
+                if [[ ${use_trt} = "False" || ${precision} =~ "int8" ]] && [[ ${_flag_quant} = "True" ]]; then
+                    continue
+                fi
+
+                device_type_line=24
+                set_device_type_cmd="sed -i '${device_type_line}s/device_type: .*/device_type: 1/' config.yml"
+                eval $set_device_type_cmd
+
+                devices_line=27
+                set_devices_cmd="sed -i '${devices_line}s/devices: .*/devices: \"${use_gpu}\"/' config.yml"
+                eval $set_devices_cmd
+
+                web_service_cmd="${python_} ${web_service_py} & "
+                eval $web_service_cmd
+                sleep 5s
+                for pipeline in ${pipeline_py[*]}; do
+                    _save_log_path="${LOG_PATH}/server_infer_gpu_${pipeline%_client*}_batchsize_1.log"
+                    pipeline_cmd="${python_} ${pipeline} > ${_save_log_path} 2>&1"
                     eval $pipeline_cmd
-                    status_check $last_status "${pipeline_cmd}" "${status_log}"
+                    last_status=${PIPESTATUS[0]}
+                    eval "cat ${_save_log_path}"
+                    status_check $last_status "${pipeline_cmd}" "${status_log}" "${model_name}"
                     sleep 5s
-                    ps ux | grep -E 'web_service|pipeline' | awk '{print $2}' | xargs kill -s 9
+                done
-                fi
+                ps ux | grep -E 'web_service|pipeline' | awk '{print $2}' | xargs kill -s 9
-            done
+            else
-        else
+                echo "Does not support hardware [${use_gpu}] other than CPU and GPU Currently!"
-            # python serving
+            fi
-            for use_gpu in ${web_use_gpu_list[*]}; do
+        done
-                if [[ ${use_gpu} = "null" ]]; then
+    fi
-                    device_type_line=24
-                    set_device_type_cmd="sed -i '${device_type_line}s/device_type: .*/device_type: 0/' config.yml"
-                    eval $set_device_type_cmd
-
-                    devices_line=27
-                    set_devices_cmd="sed -i '${devices_line}s/devices: .*/devices: \"\"/' config.yml"
-                    eval $set_devices_cmd
-
-                    web_service_cmd="${python} ${web_service_py} &"
-                    eval $web_service_cmd
-                    sleep 5s
-                    for pipeline in ${pipeline_py[*]}; do
-                        _save_log_path="${LOG_PATH}/server_infer_cpu_${pipeline%_client*}_batchsize_1.log"
-                        pipeline_cmd="${python} ${pipeline} > ${_save_log_path} 2>&1 "
-                        eval $pipeline_cmd
-                        last_status=${PIPESTATUS[0]}
-                        eval "cat ${_save_log_path}"
-                        status_check $last_status "${pipeline_cmd}" "${status_log}"
-                        sleep 5s
-                    done
-                    ps ux | grep -E 'web_service|pipeline' | awk '{print $2}' | xargs kill -s 9
-                elif [ ${use_gpu} -eq 0 ]; then
-                    if [[ ${_flag_quant} = "False" ]] && [[ ${precision} =~ "int8" ]]; then
-                        continue
-                    fi
-                    if [[ ${precision} =~ "fp16" || ${precision} =~ "int8" ]] && [ ${use_trt} = "False" ]; then
-                        continue
-                    fi
-                    if [[ ${use_trt} = "False" || ${precision} =~ "int8" ]] && [[ ${_flag_quant} = "True" ]]; then
-                        continue
-                    fi
-
-                    device_type_line=24
-                    set_device_type_cmd="sed -i '${device_type_line}s/device_type: .*/device_type: 1/' config.yml"
-                    eval $set_device_type_cmd
-
-                    devices_line=27
-                    set_devices_cmd="sed -i '${devices_line}s/devices: .*/devices: \"${use_gpu}\"/' config.yml"
-                    eval $set_devices_cmd
-
-                    web_service_cmd="${python} ${web_service_py} & "
-                    eval $web_service_cmd
-                    sleep 5s
-                    for pipeline in ${pipeline_py[*]}; do
-                        _save_log_path="${LOG_PATH}/server_infer_gpu_${pipeline%_client*}_batchsize_1.log"
-                        pipeline_cmd="${python} ${pipeline} > ${_save_log_path} 2>&1"
-                        eval $pipeline_cmd
-                        last_status=${PIPESTATUS[0]}
-                        eval "cat ${_save_log_path}"
-                        status_check $last_status "${pipeline_cmd}" "${status_log}"
-                        sleep 5s
-                    done
-                    ps ux | grep -E 'web_service|pipeline' | awk '{print $2}' | xargs kill -s 9
-                else
-                    echo "Does not support hardware [${use_gpu}] other than CPU and GPU Currently!"
-                fi
-            done
-        fi
-    done
 }
 
 
@@ -200,6 +226,12 @@ function func_serving_rec(){
     pipeline_py=$(func_parser_value "${lines[17]}")
 
     IFS='|'
+    for python_ in ${python[*]}; do
+        if [[ ${python_} =~ "python" ]]; then
+            python_interp=${python_}
+            break
+        fi
+    done
 
     # pdserving
     cd ./deploy
@@ -208,7 +240,7 @@ function func_serving_rec(){
     set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}")
     set_serving_server=$(func_set_params "${cls_serving_server_key}" "${cls_serving_server_value}")
     set_serving_client=$(func_set_params "${cls_serving_client_key}" "${cls_serving_client_value}")
-    cls_trans_model_cmd="${python} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}"
+    cls_trans_model_cmd="${python_interp} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}"
     eval $cls_trans_model_cmd
 
     set_dirname=$(func_set_params "${det_infer_model_dir_key}" "${det_infer_model_dir_value}")
@@ -216,7 +248,7 @@ function func_serving_rec(){
     set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}")
     set_serving_server=$(func_set_params "${det_serving_server_key}" "${det_serving_server_value}")
     set_serving_client=$(func_set_params "${det_serving_client_key}" "${det_serving_client_value}")
-    det_trans_model_cmd="${python} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}"
+    det_trans_model_cmd="${python_interp} ${trans_model_py} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_serving_server} ${set_serving_client}"
     eval $det_trans_model_cmd
 
     # modify the alias_name of fetch_var to "outputs"
@@ -235,99 +267,130 @@ function func_serving_rec(){
     unset https_proxy
     unset http_proxy
 
-    # modify the input_name in "recognition_web_service.py" to be consistent with feed_var.name in prototxt
+    if [[ ${FILENAME} =~ "cpp" ]]; then
-    set_web_service_feet_var_cmd="sed -i '/preprocess/,/input_imgs}/s/{.*: input_imgs}/{${feed_var_name}: input_imgs}/' ${web_service_py}"
+        det_serving_client_dir_name=$(func_get_url_file_name "$det_serving_client_value")
-    eval ${set_web_service_feet_var_cmd}
+        set_det_client_config_line_cmd="sed -i '/MainbodyDetect/,/serving_client_conf.prototxt/s/models\/.*\/serving_client_conf.prototxt/models\/${det_serving_client_dir_name}\/serving_client_conf.prototxt/' ${pipeline_py}"
+        echo $PWD - $set_det_client_config_line_cmd
+        eval ${set_det_client_config_line_cmd}
 
-    for python in ${python[*]}; do
+        cls_serving_client_dir_name=$(func_get_url_file_name "$cls_serving_client_value")
-        if [[ ${python} = "cpp" ]]; then
+        set_cls_client_config_line_cmd="sed -i '/ObjectRecognition/,/serving_client_conf.prototxt/s/models\/.*\/serving_client_conf.prototxt/models\/${cls_serving_client_dir_name}\/serving_client_conf.prototxt/' ${pipeline_py}"
-            for use_gpu in ${web_use_gpu_list[*]}; do
+        echo $PWD - $set_cls_client_config_line_cmd
-                if [ ${use_gpu} = "null" ]; then
+        eval ${set_cls_client_config_line_cmd}
-                    web_service_cpp_cmd="${python} web_service_py"
 
-                    eval $web_service_cmd
+        set_pipeline_py_feed_var_cmd="sed -i '/ObjectRecognition/,/feed={\"x\": batch_imgs}/s/{.*: batch_imgs}/{${feed_var_name}: batch_imgs}/' ${pipeline_py}"
-                    sleep 5s
+        echo $PWD - $set_pipeline_py_feed_var_cmd
-                    _save_log_path="${LOG_PATH}/server_infer_cpp_cpu_pipeline_usemkldnn_False_threads_4_batchsize_1.log"
+        eval ${set_pipeline_py_feed_var_cmd}
-                    pipeline_cmd="${python} ocr_cpp_client.py ppocr_det_mobile_2.0_client/ ppocr_rec_mobile_2.0_client/"
+
+        for use_gpu in ${web_use_gpu_list[*]}; do
+            if [ ${use_gpu} = "null" ]; then
+
+                det_serving_server_dir_name=$(func_get_url_file_name "$det_serving_server_value")
+                web_service_cpp_cmd="${python_interp} -m paddle_serving_server.serve --model ../../models/${det_serving_server_dir_name} --port 9293 >>log_mainbody_detection.txt &"
+
+                cls_serving_server_dir_name=$(func_get_url_file_name "$cls_serving_server_value")
+                web_service_cpp_cmd2="${python_interp} -m paddle_serving_server.serve --model ../../models/${cls_serving_server_dir_name} --port 9294 >>log_feature_extraction.txt &"
+                echo $PWD - $web_service_cpp_cmd
+                eval $web_service_cpp_cmd
+                echo $PWD - $web_service_cpp_cmd2
+                eval $web_service_cpp_cmd2
+                sleep 5s
+                _save_log_path="${LOG_PATH}/server_infer_cpp_cpu_batchsize_1.log"
+                pipeline_cmd="${python_interp} test_cpp_serving_client.py > ${_save_log_path} 2>&1 "
+                echo ${pipeline_cmd}
+                eval ${pipeline_cmd}
+                last_status=${PIPESTATUS[0]}
+                eval "cat ${_save_log_path}"
+                status_check ${last_status} "${pipeline_cmd}" "${status_log}" "${model_name}"
+                ps ux | grep -E 'serving_server|pipeline' | awk '{print $2}' | xargs kill -s 9
+                sleep 5s
+            else
+                det_serving_server_dir_name=$(func_get_url_file_name "$det_serving_server_value")
+                web_service_cpp_cmd="${python_interp} -m paddle_serving_server.serve --model ../../models/${det_serving_server_dir_name} --port 9293 --gpu_id=${use_gpu} >>log_mainbody_detection.txt &"
+
+                cls_serving_server_dir_name=$(func_get_url_file_name "$cls_serving_server_value")
+                web_service_cpp_cmd2="${python_interp} -m paddle_serving_server.serve --model ../../models/${cls_serving_server_dir_name} --port 9294 --gpu_id=${use_gpu} >>log_feature_extraction.txt &"
+                echo $PWD - $web_service_cpp_cmd
+                eval $web_service_cpp_cmd
+                echo $PWD - $web_service_cpp_cmd2
+                eval $web_service_cpp_cmd2
+                sleep 5s
+                _save_log_path="${LOG_PATH}/server_infer_cpp_gpu_batchsize_1.log"
+                pipeline_cmd="${python_interp} test_cpp_serving_client.py > ${_save_log_path} 2>&1 "
+                echo ${pipeline_cmd}
+                eval ${pipeline_cmd}
+                last_status=${PIPESTATUS[0]}
+                eval "cat ${_save_log_path}"
+                status_check ${last_status} "${pipeline_cmd}" "${status_log}" "${model_name}"
+                ps ux | grep -E 'serving_server|pipeline' | awk '{print $2}' | xargs kill -s 9
+                sleep 5s
+            fi
+        done
+    else
+        # modify the input_name in "recognition_web_service.py" to be consistent with feed_var.name in prototxt
+        set_web_service_feed_var_cmd="sed -i '/preprocess/,/input_imgs}/s/{.*: input_imgs}/{${feed_var_name}: input_imgs}/' ${web_service_py}"
+        eval ${set_web_service_feed_var_cmd}
+        # python serving
+        for use_gpu in ${web_use_gpu_list[*]}; do
+            if [[ ${use_gpu} = "null" ]]; then
+                device_type_line=24
+                set_device_type_cmd="sed -i '${device_type_line}s/device_type: .*/device_type: 0/' config.yml"
+                eval $set_device_type_cmd
+
+                devices_line=27
+                set_devices_cmd="sed -i '${devices_line}s/devices: .*/devices: \"\"/' config.yml"
+                eval $set_devices_cmd
+
+                web_service_cmd="${python} ${web_service_py} &"
+                eval $web_service_cmd
+                sleep 5s
+                for pipeline in ${pipeline_py[*]}; do
+                    _save_log_path="${LOG_PATH}/server_infer_cpu_${pipeline%_client*}_batchsize_1.log"
+                    pipeline_cmd="${python} ${pipeline} > ${_save_log_path} 2>&1 "
                     eval $pipeline_cmd
-                    status_check $last_status "${pipeline_cmd}" "${status_log}"
+                    last_status=${PIPESTATUS[0]}
+                    eval "cat ${_save_log_path}"
+                    status_check $last_status "${pipeline_cmd}" "${status_log}" "${model_name}"
                     sleep 5s
-                    ps ux | grep -E 'web_service|pipeline' | awk '{print $2}' | xargs kill -s 9
+                done
-                else
+                ps ux | grep -E 'web_service|pipeline' | awk '{print $2}' | xargs kill -s 9
-                    web_service_cpp_cmd="${python} web_service_py"
+            elif [ ${use_gpu} -eq 0 ]; then
-                    eval $web_service_cmd
+                if [[ ${_flag_quant} = "False" ]] && [[ ${precision} =~ "int8" ]]; then
-                    sleep 5s
+                    continue
-                    _save_log_path="${LOG_PATH}/server_infer_cpp_cpu_pipeline_usemkldnn_False_threads_4_batchsize_1.log"
+                fi
-                    pipeline_cmd="${python} ocr_cpp_client.py ppocr_det_mobile_2.0_client/ ppocr_rec_mobile_2.0_client/"
+                if [[ ${precision} =~ "fp16" || ${precision} =~ "int8" ]] && [ ${use_trt} = "False" ]; then
-                    eval $pipeline_cmd
+                    continue
-                    status_check $last_status "${pipeline_cmd}" "${status_log}"
+                fi
-                    sleep 5s
+                if [[ ${use_trt} = "False" || ${precision} =~ "int8" ]] && [[ ${_flag_quant} = "True" ]]; then
-                    ps ux | grep -E 'web_service|pipeline' | awk '{print $2}' | xargs kill -s 9
+                    continue
                 fi
-            done
-        else
-            # python serving
-            for use_gpu in ${web_use_gpu_list[*]}; do
-                if [[ ${use_gpu} = "null" ]]; then
-                    device_type_line=24
-                    set_device_type_cmd="sed -i '${device_type_line}s/device_type: .*/device_type: 0/' config.yml"
-                    eval $set_device_type_cmd
 
-                    devices_line=27
+                device_type_line=24
-                    set_devices_cmd="sed -i '${devices_line}s/devices: .*/devices: \"\"/' config.yml"
+                set_device_type_cmd="sed -i '${device_type_line}s/device_type: .*/device_type: 1/' config.yml"
-                    eval $set_devices_cmd
+                eval $set_device_type_cmd
 
-                    web_service_cmd="${python} ${web_service_py} &"
+                devices_line=27
-                    eval $web_service_cmd
+                set_devices_cmd="sed -i '${devices_line}s/devices: .*/devices: \"${use_gpu}\"/' config.yml"
-                    sleep 5s
+                eval $set_devices_cmd
-                    for pipeline in ${pipeline_py[*]}; do
-                        _save_log_path="${LOG_PATH}/server_infer_cpu_${pipeline%_client*}_batchsize_1.log"
-                        pipeline_cmd="${python} ${pipeline} > ${_save_log_path} 2>&1 "
-                        eval $pipeline_cmd
-                        last_status=${PIPESTATUS[0]}
-                        eval "cat ${_save_log_path}"
-                        status_check $last_status "${pipeline_cmd}" "${status_log}"
-                        sleep 5s
-                    done
-                    ps ux | grep -E 'web_service|pipeline' | awk '{print $2}' | xargs kill -s 9
-                elif [ ${use_gpu} -eq 0 ]; then
-                    if [[ ${_flag_quant} = "False" ]] && [[ ${precision} =~ "int8" ]]; then
-                        continue
-                    fi
-                    if [[ ${precision} =~ "fp16" || ${precision} =~ "int8" ]] && [ ${use_trt} = "False" ]; then
-                        continue
-                    fi
-                    if [[ ${use_trt} = "False" || ${precision} =~ "int8" ]] && [[ ${_flag_quant} = "True" ]]; then
-                        continue
-                    fi
 
-                    device_type_line=24
+                web_service_cmd="${python} ${web_service_py} & "
-                    set_device_type_cmd="sed -i '${device_type_line}s/device_type: .*/device_type: 1/' config.yml"
+                eval $web_service_cmd
-                    eval $set_device_type_cmd
+                sleep 10s
-
+                for pipeline in ${pipeline_py[*]}; do
-                    devices_line=27
+                    _save_log_path="${LOG_PATH}/server_infer_gpu_${pipeline%_client*}_batchsize_1.log"
-                    set_devices_cmd="sed -i '${devices_line}s/devices: .*/devices: \"${use_gpu}\"/' config.yml"
+                    pipeline_cmd="${python} ${pipeline} > ${_save_log_path} 2>&1"
-                    eval $set_devices_cmd
+                    eval $pipeline_cmd
-
+                    last_status=${PIPESTATUS[0]}
-                    web_service_cmd="${python} ${web_service_py} & "
+                    eval "cat ${_save_log_path}"
-                    eval $web_service_cmd
+                    status_check $last_status "${pipeline_cmd}" "${status_log}" "${model_name}"
                     sleep 10s
-                    for pipeline in ${pipeline_py[*]}; do
+                done
-                        _save_log_path="${LOG_PATH}/server_infer_gpu_${pipeline%_client*}_batchsize_1.log"
+                ps ux | grep -E 'web_service|pipeline' | awk '{print $2}' | xargs kill -s 9
-                        pipeline_cmd="${python} ${pipeline} > ${_save_log_path} 2>&1"
+            else
-                        eval $pipeline_cmd
+                echo "Does not support hardware [${use_gpu}] other than CPU and GPU Currently!"
-                        last_status=${PIPESTATUS[0]}
+            fi
-                        eval "cat ${_save_log_path}"
+        done
-                        status_check $last_status "${pipeline_cmd}" "${status_log}"
+    fi
-                        sleep 10s
-                    done
-                    ps ux | grep -E 'web_service|pipeline' | awk '{print $2}' | xargs kill -s 9
-                else
-                    echo "Does not support hardware [${use_gpu}] other than CPU and GPU Currently!"
-                fi
-            done
-        fi
-    done
 }