[Other] Optimize backend selection strategy (#574)

* Optimize backend selection strategy

* remove debug code

* Update runtime.cc

* Update picodet.cc

* Update yolox.cc

* fix ci

examples/vision/detection/paddledetection/cpp/infer_ppyoloe.cc

@@ -34,7 +34,6 @@ void CpuInfer(const std::string& model_dir, const std::string& image_file) {
   }
 
   auto im = cv::imread(image_file);
-  auto im_bak = im.clone();
 
   fastdeploy::vision::DetectionResult res;
   if (!model.Predict(&im, &res)) {
@@ -43,7 +42,7 @@ void CpuInfer(const std::string& model_dir, const std::string& image_file) {
   }
 
   std::cout << res.Str() << std::endl;
-  auto vis_im = fastdeploy::vision::Visualize::VisDetection(im_bak, res, 0.5);
+  auto vis_im = fastdeploy::vision::VisDetection(im, res, 0.5);
   cv::imwrite("vis_result.jpg", vis_im);
   std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
 }
@@ -63,7 +62,6 @@ void GpuInfer(const std::string& model_dir, const std::string& image_file) {
   }
 
   auto im = cv::imread(image_file);
-  auto im_bak = im.clone();
 
   fastdeploy::vision::DetectionResult res;
   if (!model.Predict(&im, &res)) {
@@ -72,7 +70,7 @@ void GpuInfer(const std::string& model_dir, const std::string& image_file) {
   }
 
   std::cout << res.Str() << std::endl;
-  auto vis_im = fastdeploy::vision::Visualize::VisDetection(im_bak, res, 0.5);
+  auto vis_im = fastdeploy::vision::VisDetection(im, res, 0.5);
   cv::imwrite("vis_result.jpg", vis_im);
   std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
 }
@@ -93,7 +91,6 @@ void TrtInfer(const std::string& model_dir, const std::string& image_file) {
   }
 
   auto im = cv::imread(image_file);
-  auto im_bak = im.clone();
 
   fastdeploy::vision::DetectionResult res;
   if (!model.Predict(&im, &res)) {
@@ -102,7 +99,7 @@ void TrtInfer(const std::string& model_dir, const std::string& image_file) {
   }
 
   std::cout << res.Str() << std::endl;
-  auto vis_im = fastdeploy::vision::Visualize::VisDetection(im_bak, res, 0.5);
+  auto vis_im = fastdeploy::vision::VisDetection(im, res, 0.5);
   cv::imwrite("vis_result.jpg", vis_im);
   std::cout << "Visualized result saved in ./vis_result.jpg" << std::endl;
 }

fastdeploy/fastdeploy_model.cc

@@ -16,18 +16,32 @@
 
 namespace fastdeploy {
 
-bool FastDeployModel::InitRuntime() {
+std::string Str(const std::vector<Backend>& backends) {
-  FDASSERT(
+  std::ostringstream oss;
-      CheckModelFormat(runtime_option.model_file, runtime_option.model_format),
+  if (backends.size() == 0) {
-      "ModelFormatCheck Failed.");
+    oss << "[]";
-  if (runtime_initialized_) {
+    return oss.str();
-    FDERROR << "The model is already initialized, cannot be initliazed again."
-            << std::endl;
-    return false;
   }
-  if (runtime_option.backend != Backend::UNKNOWN) {
+  oss << "[ " << backends[0];
+  for (int i = 1; i < backends.size(); ++i) {
+    oss << " ," << backends[i];
+  }
+  oss << " ]";
+  return oss.str();
+}
+
+bool IsSupported(const std::vector<Backend>& backends, Backend backend) {
+  for (size_t i = 0; i < backends.size(); ++i) {
+    if (backends[i] == backend) {
+      return true;
+    }
+  }
+  return false;
+}
+
+bool FastDeployModel::InitRuntimeWithSpecifiedBackend() {
   if (!IsBackendAvailable(runtime_option.backend)) {
-      FDERROR << Str(runtime_option.backend)
+    FDERROR << runtime_option.backend
             << " is not compiled with current FastDeploy library."
             << std::endl;
     return false;
@@ -35,78 +49,45 @@ bool FastDeployModel::InitRuntime() {
 
   bool use_gpu = (runtime_option.device == Device::GPU);
   bool use_ipu = (runtime_option.device == Device::IPU);
-#ifndef WITH_GPU
-    use_gpu = false;
-#endif
-#ifndef WITH_IPU
-    use_ipu = false;
-#endif
   bool use_rknpu = (runtime_option.device == Device::RKNPU);
   bool use_timvx = (runtime_option.device == Device::TIMVX);
 
-    // whether the model is supported by the setted backend
-    bool is_supported = false;
   if (use_gpu) {
-      for (auto& item : valid_gpu_backends) {
+    if (!IsSupported(valid_gpu_backends, runtime_option.backend)) {
-        if (item == runtime_option.backend) {
+      FDERROR << "The valid gpu backends of model " << ModelName() << " are " << Str(valid_gpu_backends) << ", " << runtime_option.backend << " is not supported." << std::endl;
-          is_supported = true;
+      return false;
-          break;
-        }
     }
   } else if (use_rknpu) {
-      for (auto& item : valid_rknpu_backends) {
+    if (!IsSupported(valid_rknpu_backends, runtime_option.backend)) {
-        if (item == runtime_option.backend) {
+      FDERROR << "The valid rknpu backends of model " << ModelName() << " are " << Str(valid_rknpu_backends) << ", " << runtime_option.backend << " is not supported." << std::endl;
-          is_supported = true;
+      return false;
-          break;
-        }
     }
   } else if (use_timvx) {
-      for (auto& item : valid_timvx_backends) {
+    if (!IsSupported(valid_timvx_backends, runtime_option.backend)) {
-        if (item == runtime_option.backend) {
+      FDERROR << "The valid timvx backends of model " << ModelName() << " are " << Str(valid_timvx_backends) << ", " << runtime_option.backend << " is not supported." << std::endl;
-          is_supported = true;
+      return false;
-          break;
-        }
-      }
-    }else if(use_ipu) {
-      for (auto& item : valid_ipu_backends) {
-        if (item == runtime_option.backend) {
-          is_supported = true;
-          break;
     }
+  } else if(use_ipu) {
+    if (!IsSupported(valid_ipu_backends, runtime_option.backend)) {
+      FDERROR << "The valid ipu backends of model " << ModelName() << " are " << Str(valid_ipu_backends) << ", " << runtime_option.backend << " is not supported." << std::endl;
+      return false;
     }
   } else {
-      for (auto& item : valid_cpu_backends) {
+    if (!IsSupported(valid_cpu_backends, runtime_option.backend)) {
-        if (item == runtime_option.backend) {
+      FDERROR << "The valid cpu backends of model " << ModelName() << " are " << Str(valid_cpu_backends) << ", " << runtime_option.backend << " is not supported." << std::endl;
-          is_supported = true;
+      return false;
-          break;
-        }
     }
   }
 
-    if (is_supported) {
   runtime_ = std::shared_ptr<Runtime>(new Runtime());
   if (!runtime_->Init(runtime_option)) {
     return false;
   }
   runtime_initialized_ = true;
   return true;
-    } else {
+}
-      FDWARNING << ModelName() << " is not supported with backend "
-                << Str(runtime_option.backend) << "." << std::endl;
-      if (use_gpu) {
-        FDASSERT(valid_gpu_backends.size() > 0,
-                 "There's no valid gpu backend for %s.", ModelName().c_str());
-        FDWARNING << "FastDeploy will choose " << Str(valid_gpu_backends[0])
-                  << " for model inference." << std::endl;
-      } else {
-        FDASSERT(valid_cpu_backends.size() > 0,
-                 "There's no valid cpu backend for %s.", ModelName().c_str());
-        FDWARNING << "FastDeploy will choose " << Str(valid_cpu_backends[0])
-                  << " for model inference." << std::endl;
-      }
-    }
-  }
 
+bool FastDeployModel::InitRuntimeWithSpecifiedDevice() {
   if (runtime_option.device == Device::CPU) {
     return CreateCpuBackend();
   } else if (runtime_option.device == Device::GPU) {
@@ -130,10 +111,26 @@ bool FastDeployModel::InitRuntime() {
     return false;
 #endif
   }
-  FDERROR << "Only support CPU/GPU/NPU now." << std::endl;
+  FDERROR << "Only support CPU/GPU/IPU/RKNPU/TIMVX now." << std::endl;
   return false;
 }
 
+bool FastDeployModel::InitRuntime() {
+  FDASSERT(
+      CheckModelFormat(runtime_option.model_file, runtime_option.model_format),
+      "ModelFormatCheck Failed.");
+  if (runtime_initialized_) {
+    FDERROR << "The model is already initialized, cannot be initliazed again."
+            << std::endl;
+    return false;
+  }
+  if (runtime_option.backend != Backend::UNKNOWN) {
+    return InitRuntimeWithSpecifiedBackend();
+  }
+
+  return InitRuntimeWithSpecifiedDevice();
+}
+
 bool FastDeployModel::CreateCpuBackend() {
   if (valid_cpu_backends.size() == 0) {
     FDERROR << "There's no valid cpu backends for model: " << ModelName()

fastdeploy/fastdeploy_model.h

@@ -41,12 +41,10 @@ class FASTDEPLOY_DECL FastDeployModel {
   std::vector<Backend> valid_gpu_backends = {Backend::ORT};
   /** Model's valid ipu backends. This member defined all the ipu backends have successfully tested for the model
    */
-  std::vector<Backend> valid_ipu_backends = {Backend::PDINFER};
+  std::vector<Backend> valid_ipu_backends = {};
   /** Model's valid timvx backends. This member defined all the timvx backends have successfully tested for the model
    */
   std::vector<Backend> valid_timvx_backends = {};
-
-
   /** Model's valid hardware backends. This member defined all the gpu backends have successfully tested for the model
    */
   std::vector<Backend> valid_rknpu_backends = {};
@@ -116,20 +114,22 @@ class FASTDEPLOY_DECL FastDeployModel {
 
  protected:
   virtual bool InitRuntime();
-  virtual bool CreateCpuBackend();
-  virtual bool CreateGpuBackend();
-  virtual bool CreateIpuBackend();
-  virtual bool CreateRKNPUBackend();
-  virtual bool CreateTimVXBackend();
 
   bool initialized = false;
-  std::vector<Backend> valid_external_backends_;
   // Reused input tensors
   std::vector<FDTensor> reused_input_tensors_;
   // Reused output tensors
   std::vector<FDTensor> reused_output_tensors_;
 
  private:
+  bool InitRuntimeWithSpecifiedBackend();
+  bool InitRuntimeWithSpecifiedDevice();
+  bool CreateCpuBackend();
+  bool CreateGpuBackend();
+  bool CreateIpuBackend();
+  bool CreateRKNPUBackend();
+  bool CreateTimVXBackend();
+
   std::shared_ptr<Runtime> runtime_;
   bool runtime_initialized_ = false;
   // whether to record inference time

fastdeploy/runtime.cc

@@ -97,7 +97,7 @@ std::string Str(const Backend& b) {
   }else if (b == Backend::OPENVINO) {
     return "Backend::OPENVINO";
   } else if (b == Backend::LITE) {
-    return "Backend::LITE";
+    return "Backend::PDLITE";
   }
   return "UNKNOWN-Backend";
 }
@@ -116,9 +116,10 @@ std::ostream& operator<<(std::ostream& out, const Backend& backend) {
   }else if (backend == Backend::POROS) {
     out << "Backend::POROS";
   } else if (backend == Backend::LITE) {
-    out << "Backend::LITE";
+    out << "Backend::PDLITE";
-  }
+  } else {
     out << "UNKNOWN-Backend";
+  }
   return out;
 }
 

fastdeploy/vision/classification/ppcls/model.cc

@@ -23,10 +23,16 @@ PaddleClasModel::PaddleClasModel(const std::string& model_file,
                                  const std::string& config_file,
                                  const RuntimeOption& custom_option,
                                  const ModelFormat& model_format) : preprocessor_(config_file) {
+  if (model_format == ModelFormat::PADDLE) {
     valid_cpu_backends = {Backend::ORT, Backend::OPENVINO, Backend::PDINFER,
                           Backend::LITE};
     valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
     valid_timvx_backends = {Backend::LITE};
+    valid_ipu_backends = {Backend::PDINFER};
+  } else if (model_format == ModelFormat::ONNX) {
+    valid_cpu_backends = {Backend::ORT, Backend::OPENVINO};
+    valid_gpu_backends = {Backend::ORT, Backend::TRT};
+  }
   
   runtime_option = custom_option;
   runtime_option.model_format = model_format;

fastdeploy/vision/detection/ppdet/picodet.cc

@@ -24,7 +24,7 @@ PicoDet::PicoDet(const std::string& model_file, const std::string& params_file,
                  const RuntimeOption& custom_option,
                  const ModelFormat& model_format) {
   config_file_ = config_file;
-  valid_cpu_backends = {Backend::PDINFER, Backend::ORT, Backend::LITE};
+  valid_cpu_backends = {Backend::OPENVINO, Backend::PDINFER, Backend::ORT, Backend::LITE};
   valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
   runtime_option = custom_option;
   runtime_option.model_format = model_format;

fastdeploy/vision/segmentation/ppseg/model.cc

@@ -103,16 +103,11 @@ bool PaddleSegModel::BuildPreprocessPipelineFromConfig() {
     int input_height = input_shape[2].as<int>();
     int input_width = input_shape[3].as<int>();
     if (input_height == -1 || input_width == -1) {
-      FDWARNING << "The exported PaddleSeg model is with dynamic shape input, "
+      FDWARNING << "Some exportd PaddleSeg models with dynamic shape may "
-                << "which is not supported by ONNX Runtime and Tensorrt. "
+                "not be able inference with ONNX Runtime/TensorRT, if error "
-                << "Only OpenVINO and Paddle Inference are available now. "
+                "happend, please try to change to use Paddle "
-                << "For using ONNX Runtime or Tensorrt, "
+                "Inference/OpenVINO backends instead, or export model with "
-                << "Please refer to "
+                "fixed input shape." << std::endl;
-                   "https://github.com/PaddlePaddle/PaddleSeg/blob/develop/"
-                   "docs/model_export.md"
-                << " to export model with fixed input shape." << std::endl;
-      valid_cpu_backends = {Backend::OPENVINO, Backend::PDINFER, Backend::LITE};
-      valid_gpu_backends = {Backend::PDINFER};
     }
     if (input_height != -1 && input_width != -1 && !yml_contain_resize_op) {
       processors_.push_back(

python/setup.py

@@ -45,9 +45,15 @@ import multiprocessing
 with open(os.path.join(TOP_DIR, "python", "requirements.txt")) as fin:
     REQUIRED_PACKAGES = fin.read()
 
+if os.getenv("BUILD_ON_CPU", "OFF") == "ON":
+    os.environ["ENABLE_PADDLE_BACKEND"] = "ON"
+    os.environ["ENABLE_ORT_BACKEND"] = "ON"
+    os.environ["ENABLE_OPENVINO_BACKEND"] = "ON"
+    os.environ["ENABLE_VISION"] = "ON"
+    os.environ["ENABLE_TEXT"] = "ON"
+    os.environ["WITH_GPU"] = "OFF"
+
 setup_configs = dict()
-setup_configs["ENABLE_PADDLE_FRONTEND"] = os.getenv("ENABLE_PADDLE_FRONTEND",
-                                                    "ON")
 setup_configs["ENABLE_RKNPU2_BACKEND"] = os.getenv("ENABLE_RKNPU2_BACKEND",
                                                    "OFF")
 setup_configs["ENABLE_ORT_BACKEND"] = os.getenv("ENABLE_ORT_BACKEND", "OFF")