Add some comments for runtime (#309)

* Add some notes for runtime * modify note * modify note * add some comment * Add comment for runtime * Add comment for runtime * Add comment for runtime * Add comment for runtime
2025-12-24 13:28:13 +08:00 · 2022-09-30 14:43:44 +08:00
parent dfb83a889e
commit 8a1e2c6143
5 changed files with 344 additions and 239 deletions
--- a/.clang-format
+++ b/.clang-format
@@ -1,178 +1,180 @@
---
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+# AlignConsecutiveAssignments: None
+# AlignConsecutiveBitFields: None
+# AlignConsecutiveDeclarations: None
+# AlignEscapedNewlines: Right
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+# AllowAllConstructorInitializersOnNextLine: true
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--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -24,15 +24,15 @@ repos:
        files: \.(c|cc|cxx|cpp|cu|h|hpp|hxx|proto|py)$
        exclude: (?!.*third_party)^.*$

-   repo: local
-    hooks:
-    -   id: clang-format-with-version-check
-        name: clang-format
-        description: Format files with ClangFormat.
-        entry: bash .clang_format.hook -i
-        language: system
-        files: \.(c|cc|cxx|cpp|cu|h|hpp|hxx|proto)$
-
+# -   repo: local
+#     hooks:
+#     -   id: clang-format-with-version-check
+#         name: clang-format
+#         description: Format files with ClangFormat.
+#         entry: bash .clang_format.hook -i
+#         language: system
+#         files: \.(c|cc|cxx|cpp|cu|h|hpp|hxx|proto)$
+#
 -   repo: local
    hooks:
    -   id: cpplint-cpp-source
--- a/fastdeploy/backends/backend.h
+++ b/fastdeploy/backends/backend.h
@@ -24,10 +24,12 @@

 namespace fastdeploy {

+/*! @brief Information of Tensor
+ */
 struct TensorInfo {
-  std::string name;
-  std::vector<int> shape;
-  FDDataType dtype;
+  std::string name;        ///< Name of tensor
+  std::vector<int> shape;  ///< Shape of tensor
+  FDDataType dtype;        ///< Data type of tensor

  friend std::ostream& operator<<(std::ostream& output,
                                  const TensorInfo& info) {
--- a/fastdeploy/runtime.cc
+++ b/fastdeploy/runtime.cc
@@ -93,6 +93,32 @@ std::string Str(const ModelFormat& f) {
  return "UNKNOWN-ModelFormat";
 }

+std::ostream& operator<<(std::ostream& out, const Backend& backend) {
+  if (backend == Backend::ORT) {
+    out << "Backend::ORT";
+  } else if (backend == Backend::TRT) {
+    out << "Backend::TRT";
+  } else if (backend == Backend::PDINFER) {
+    out << "Backend::PDINFER";
+  } else if (backend == Backend::OPENVINO) {
+    out << "Backend::OPENVINO";
+  } else if (backend == Backend::LITE) {
+    out << "Backend::LITE";
+  }
+  out << "UNKNOWN-Backend";
+  return out;
+}
+
+std::ostream& operator<<(std::ostream& out, const ModelFormat& format) {
+  if (format == ModelFormat::PADDLE) {
+    out << "ModelFormat::PADDLE";
+  } else if (format == ModelFormat::ONNX) {
+    out << "ModelFormat::ONNX";
+  }
+  out << "UNKNOWN-ModelFormat";
+  return out;
+}
+
 bool CheckModelFormat(const std::string& model_file,
                      const ModelFormat& model_format) {
  if (model_format == ModelFormat::PADDLE) {
@@ -255,6 +281,10 @@ void RuntimeOption::SetTrtInputShape(const std::string& input_name,
  }
 }

+void RuntimeOption::SetTrtMaxWorkspaceSize(size_t max_workspace_size) {
+  trt_max_workspace_size = max_workspace_size;
+}
+
 void RuntimeOption::EnableTrtFP16() { trt_enable_fp16 = true; }

 void RuntimeOption::DisableTrtFP16() { trt_enable_fp16 = false; }
@@ -263,10 +293,6 @@ void RuntimeOption::SetTrtCacheFile(const std::string& cache_file_path) {
  trt_serialize_file = cache_file_path;
 }

-void RuntimeOption::SetTrtMaxWorkspaceSize(size_t max_workspace_size) {
-  trt_max_workspace_size = max_workspace_size;
-}
-
 bool Runtime::Init(const RuntimeOption& _option) {
  option = _option;
  if (option.model_format == ModelFormat::AUTOREC) {
--- a/fastdeploy/runtime.h
+++ b/fastdeploy/runtime.h
@@ -11,6 +11,13 @@
 // 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.
+
+/*! \file runtime.h
+    \brief A brief file description.
+
+    More details
+ */
+
 #pragma once

 #include <map>
@@ -19,95 +26,149 @@
 #include "fastdeploy/backends/backend.h"
 #include "fastdeploy/utils/perf.h"

+/** \brief All C++ FastDeploy APIs are defined inside this namespace
+*
+*/
 namespace fastdeploy {

-enum FASTDEPLOY_DECL Backend { UNKNOWN, ORT, TRT, PDINFER, OPENVINO, LITE };
-// AUTOREC will according to the name of model file
-// to decide which ModelFormat is
-enum FASTDEPLOY_DECL ModelFormat { AUTOREC, PADDLE, ONNX };
+/*! Inference backend supported in FastDeploy */
+enum Backend {
+  UNKNOWN,  ///< Unknown inference backend
+  ORT,  ///< ONNX Runtime, support Paddle/ONNX format model, CPU / Nvidia GPU
+  TRT,  ///< TensorRT, support Paddle/ONNX format model, Nvidia GPU only
+  PDINFER,  ///< Paddle Inference, support Paddle format model, CPU / Nvidia GPU
+  OPENVINO,  ///< Intel OpenVINO, support Paddle/ONNX format, CPU only
+  LITE,  ///< Paddle Lite, support Paddle format model, ARM CPU only
+};
+
+/*! Deep learning model format */
+enum ModelFormat {
+  AUTOREC,  ///< Auto recognize the model format by model file name
+  PADDLE,  ///< Model with paddlepaddle format
+  ONNX,  ///< Model with ONNX format
+};
+
+FASTDEPLOY_DECL std::ostream& operator<<(std::ostream& out,
+                                         const Backend& backend);
+FASTDEPLOY_DECL std::ostream& operator<<(std::ostream& out,
+                                         const ModelFormat& format);

 FASTDEPLOY_DECL std::string Str(const Backend& b);
 FASTDEPLOY_DECL std::string Str(const ModelFormat& f);
+
+/**
+ * @brief Get all the available inference backend in FastDeploy
+ */
 FASTDEPLOY_DECL std::vector<Backend> GetAvailableBackends();

+/**
+ * @brief Check if the inference backend available
+ */
 FASTDEPLOY_DECL bool IsBackendAvailable(const Backend& backend);

 bool CheckModelFormat(const std::string& model_file,
                      const ModelFormat& model_format);
 ModelFormat GuessModelFormat(const std::string& model_file);

+/*! @brief Option object used when create a new Runtime object
+ */
 struct FASTDEPLOY_DECL RuntimeOption {
-  // set path of model file and params file
-  // for onnx, only need to define model_file, but also need to
-  // define model_format
-  // model_format support 'paddle' / 'onnx' now.
+   /** \brief Set path of model file and parameter file
+   *
+   * \param[in] model_path Path of model file, e.g ResNet50/model.pdmodel for Paddle format model / ResNet50/model.onnx for ONNX format model
+   * \param[in] params_path Path of parameter file, this only used when the model format is Paddle, e.g Resnet50/model.pdiparams
+   * \param[in] format Format of the loaded model
+   */
  void SetModelPath(const std::string& model_path,
                    const std::string& params_path = "",
                    const ModelFormat& format = ModelFormat::PADDLE);

-  // set model inference in GPU
+  /// Use cpu to inference, the runtime will inference on CPU by default
  void UseCpu();

-  // set model inference in CPU
+  /// Use Nvidia GPU to inference
  void UseGpu(int gpu_id = 0);

-  // set number of thread while inference in CPU
+  /*
+   * @brief Set number of cpu threads while inference on CPU, by default it will decided by the different backends
+   */
  void SetCpuThreadNum(int thread_num);

-  // use paddle inference backend
+  /// Set Paddle Inference as inference backend, support CPU/GPU
  void UsePaddleBackend();

-  // use onnxruntime backend
+  /// Set ONNX Runtime as inference backend, support CPU/GPU
  void UseOrtBackend();

-  // use tensorrt backend
+  /// Set TensorRT as inference backend, only support GPU
  void UseTrtBackend();

-  // use openvino backend
+  /// Set OpenVINO as inference backend, only support CPU
  void UseOpenVINOBackend();

-  // use paddle lite backend
+  /// Set Paddle Lite as inference backend, only support arm cpu
  void UseLiteBackend();

-  // enable mkldnn while use paddle inference in CPU
+  /// Enable mkldnn while using Paddle Inference as inference backend
  void EnablePaddleMKLDNN();
-  // disable mkldnn while use paddle inference in CPU
+
+  /// Disable mkldnn while using Paddle Inference as inference backend
  void DisablePaddleMKLDNN();
-  // Enable delete in pass
+
+  /*
+   * Delete pass by name while using Paddle Inference as inference backend, this can be called multiple times to delete mulitple passes
+   */
  void DeletePaddleBackendPass(const std::string& delete_pass_name);

-  // enable debug information of paddle backend
+  /**
+   * @brief Enable print debug information while using Paddle Inference as inference backend, the backend disable the debug information by default
+   */
  void EnablePaddleLogInfo();
-  // disable debug information of paddle backend
+
+  /**
+   * @brief Disable print debug information while using Paddle Inference as inference backend
+   */
  void DisablePaddleLogInfo();

-  // set size of cached shape while enable mkldnn with paddle inference backend
+  /**
+   * @brief Set shape cache size while using Paddle Inference with mkldnn, by default it will cache all the difference shape
+   */
  void SetPaddleMKLDNNCacheSize(int size);

-  // set the power mode of paddle lite backend.
+  /**
+   * @brief Set power mode while using Paddle Lite as inference backend, mode(0: LITE_POWER_HIGH; 1: LITE_POWER_LOW; 2: LITE_POWER_FULL; 3: LITE_POWER_NO_BIND, 4: LITE_POWER_RAND_HIGH; 5: LITE_POWER_RAND_LOW, refer [paddle lite](https://paddle-lite.readthedocs.io/zh/latest/api_reference/cxx_api_doc.html#set-power-mode) for more details)
+   */
  void SetLitePowerMode(int mode);

-  // set tensorrt shape while the inputs of model contain dynamic shape
-  // min_shape: the minimum shape
-  // opt_shape: the most common shape while inference, default be empty
-  // max_shape: the maximum shape, default be empty

-  // if opt_shape, max_shape are empty, they will keep same with the min_shape
-  // which means the shape will be fixed as min_shape while inference
+  /** \brief Set shape range of input tensor for the model that contain dynamic input shape while using TensorRT backend
+   *
+   * \param[in] input_name The name of input for the model which is dynamic shape
+   * \param[in] min_shape The minimal shape for the input tensor
+   * \param[in] opt_shape The optimized shape for the input tensor, just set the most common shape, if set as default value, it will keep same with min_shape
+   * \param[in] max_shape The maximum shape for the input tensor, if set as default value, it will keep same with min_shape
+   */
  void SetTrtInputShape(
      const std::string& input_name, const std::vector<int32_t>& min_shape,
      const std::vector<int32_t>& opt_shape = std::vector<int32_t>(),
      const std::vector<int32_t>& max_shape = std::vector<int32_t>());

-  // enable half precision while use tensorrt backend
+  /// Set max_workspace_size for TensorRT, default 1<<30
+  void SetTrtMaxWorkspaceSize(size_t trt_max_workspace_size);
+
+  /**
+   * @brief Enable FP16 inference while using TensorRT backend. Notice: not all the GPU device support FP16, on those device doesn't support FP16, FastDeploy will fallback to FP32 automaticly
+   */
  void EnableTrtFP16();
-  // disable half precision, change to full precision(float32)
+
+  /// Disable FP16 inference while using TensorRT backend
  void DisableTrtFP16();

+  /**
+   * @brief Set cache file path while use TensorRT backend. Loadding a Paddle/ONNX model and initialize TensorRT will take a long time, by this interface it will save the tensorrt engine to `cache_file_path`, and load it directly while execute the code again
+   */
  void SetTrtCacheFile(const std::string& cache_file_path);

-  void SetTrtMaxWorkspaceSize(size_t trt_max_workspace_size);
-
  Backend backend = Backend::UNKNOWN;
  // for cpu inference and preprocess
  // default will let the backend choose their own default value
@@ -158,35 +219,49 @@ struct FASTDEPLOY_DECL RuntimeOption {
  std::map<std::string, std::string> custom_op_info_;
 };

+/*! @brief Runtime object used to inference the loaded model on different devices
+ */
 struct FASTDEPLOY_DECL Runtime {
 public:
-  //  explicit Runtime(const RuntimeOption& _option = RuntimeOption());
-
+  /// Intialize a Runtime object with RuntimeOption
  bool Init(const RuntimeOption& _option);

+  /** \brief Inference the model by the input data, and write to the output
+   *
+   * \param[in] input_tensors Notice the FDTensor::name should keep same with the model's input
+   * \param[in] output_tensors Inference results
+   * \return true if the inference successed, otherwise false
+   */
  bool Infer(std::vector<FDTensor>& input_tensors,
             std::vector<FDTensor>* output_tensors);

-  void CreateOrtBackend();
-
-  void CreatePaddleBackend();
-
-  void CreateTrtBackend();
-
-  void CreateOpenVINOBackend();
-
-  void CreateLiteBackend();
-
+  /** \brief Get number of inputs
+   */
  int NumInputs() { return backend_->NumInputs(); }
+  /** \brief Get number of outputs
+   */
  int NumOutputs() { return backend_->NumOutputs(); }
+  /** \brief Get input information by index
+   */
  TensorInfo GetInputInfo(int index);
+  /** \brief Get output information by index
+   */
  TensorInfo GetOutputInfo(int index);
+  /** \brief Get all the input information
+   */
  std::vector<TensorInfo> GetInputInfos();
+  /** \brief Get all the output information
+   */
  std::vector<TensorInfo> GetOutputInfos();

  RuntimeOption option;

 private:
+  void CreateOrtBackend();
+  void CreatePaddleBackend();
+  void CreateTrtBackend();
+  void CreateOpenVINOBackend();
+  void CreateLiteBackend();
  std::unique_ptr<BaseBackend> backend_;
 };
 }  // namespace fastdeploy