[Other] Optimize runtime module (#1356)

* Optimize runtime

* fix error

* [Backend] Add option to print tensorrt conversion log (#1386)

Add option to print tensorrt conversion log

Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>

---------

Co-authored-by: root <root@bjyz-sys-gpu-kongming3.bjyz.baidu.com>

fastdeploy/runtime/backends/tensorrt/option.h

@@ -30,6 +30,9 @@ struct TrtBackendOption {
   /// `max_workspace_size` for TensorRT
   size_t max_workspace_size = 1 << 30;
 
+  /// Enable log while converting onnx model to tensorrt
+  bool enable_log_info = false;
+
   /*
    * @brief Enable half precison inference, on some device not support half precision, it will fallback to float32 mode
    */

fastdeploy/runtime/backends/tensorrt/option_pybind.cc

@@ -21,6 +21,7 @@ void BindTrtOption(pybind11::module& m) {
   pybind11::class_<TrtBackendOption>(m, "TrtBackendOption")
       .def(pybind11::init())
       .def_readwrite("enable_fp16", &TrtBackendOption::enable_fp16)
+      .def_readwrite("enable_log_info", &TrtBackendOption::enable_log_info)
       .def_readwrite("max_batch_size", &TrtBackendOption::max_batch_size)
       .def_readwrite("max_workspace_size",
                      &TrtBackendOption::max_workspace_size)

fastdeploy/runtime/backends/tensorrt/trt_backend.cc

@@ -114,6 +114,13 @@ bool TrtBackend::LoadTrtCache(const std::string& trt_engine_file) {
 }
 
 bool TrtBackend::Init(const RuntimeOption& runtime_option) {
+  auto trt_option = runtime_option.trt_option;
+  trt_option.model_file = runtime_option.model_file;
+  trt_option.params_file = runtime_option.params_file;
+  trt_option.model_format = runtime_option.model_format;
+  trt_option.gpu_id = runtime_option.device_id;
+  trt_option.enable_pinned_memory = runtime_option.enable_pinned_memory;
+  trt_option.external_stream_ = runtime_option.external_stream_;
   if (runtime_option.device != Device::GPU) {
     FDERROR << "TrtBackend only supports Device::GPU, but now it's "
             << runtime_option.device << "." << std::endl;
@@ -130,7 +137,7 @@ bool TrtBackend::Init(const RuntimeOption& runtime_option) {
     if (runtime_option.model_from_memory_) {
       return InitFromPaddle(runtime_option.model_file,
                             runtime_option.params_file,
-                            runtime_option.trt_option);
+                            trt_option);
     } else {
       std::string model_buffer;
       std::string params_buffer;
@@ -141,17 +148,17 @@ bool TrtBackend::Init(const RuntimeOption& runtime_option) {
                "Failed to read parameters file %s.",
                runtime_option.params_file.c_str());
       return InitFromPaddle(model_buffer, params_buffer,
-                            runtime_option.trt_option);
+                            trt_option);
     }
   } else {
     if (runtime_option.model_from_memory_) {
-      return InitFromOnnx(runtime_option.model_file, runtime_option.trt_option);
+      return InitFromOnnx(runtime_option.model_file, trt_option);
     } else {
       std::string model_buffer;
       FDASSERT(ReadBinaryFromFile(runtime_option.model_file, &model_buffer),
                "Failed to read model file %s.",
                runtime_option.model_file.c_str());
-      return InitFromOnnx(model_buffer, runtime_option.trt_option);
+      return InitFromOnnx(model_buffer, trt_option);
     }
   }
   return true;
@@ -525,6 +532,9 @@ void TrtBackend::AllocateOutputsBuffer(std::vector<FDTensor>* outputs,
 }
 
 bool TrtBackend::BuildTrtEngine() {
+  if (option_.enable_log_info) {
+    FDTrtLogger::Get()->SetLog(true, true);
+  }
   auto config =
       FDUniquePtr<nvinfer1::IBuilderConfig>(builder_->createBuilderConfig());
   if (!config) {

fastdeploy/runtime/backends/tensorrt/utils.h

@@ -220,20 +220,30 @@ class FDTrtLogger : public nvinfer1::ILogger {
     logger = new FDTrtLogger();
     return logger;
   }
+  void SetLog(bool enable_info = false, bool enable_warning = false) {
+    enable_info_ = enable_info;
+    enable_warning_ = enable_warning;
+  }
+
   void log(nvinfer1::ILogger::Severity severity,
            const char* msg) noexcept override {
     if (severity == nvinfer1::ILogger::Severity::kINFO) {
-      // Disable this log
-      //      FDINFO << msg << std::endl;
+      if (enable_info_) {
+        FDINFO << msg << std::endl;
+      }
     } else if (severity == nvinfer1::ILogger::Severity::kWARNING) {
-      // Disable this log
-      //      FDWARNING << msg << std::endl;
+      if (enable_warning_) {
+        FDWARNING << msg << std::endl;
+      }
     } else if (severity == nvinfer1::ILogger::Severity::kERROR) {
       FDERROR << msg << std::endl;
     } else if (severity == nvinfer1::ILogger::Severity::kINTERNAL_ERROR) {
       FDASSERT(false, "%s", msg);
     }
   }
+ private:
+  bool enable_info_ = false;
+  bool enable_warning_ = false;
 };
 
 struct ShapeRangeInfo {