Integrate CAN-aware CMS risk pipeline and relocatable Orin runtime

2026-09-23 18:54:11 +08:00
parent 26c5bfb88d
commit 9aadf9cbda
119 changed files with 13940 additions and 152 deletions
@@ -1,122 +0,0 @@
-#pragma once
-
-#include <NvInfer.h>
-#include <NvInferVersion.h>
-#include <cuda_runtime.h>
-
-#include <cstring>
-#include <cstdint>
-#include <filesystem>
-#include <fstream>
-#include <iostream>
-#include <memory>
-#include <stdexcept>
-#include <string>
-#include <vector>
-
-namespace fangjia {
-
-inline void checkCuda(cudaError_t status, char const* expression, char const* file, int line) {
-    if (status != cudaSuccess) {
-        throw std::runtime_error(
-            std::string("CUDA failure: ") + expression + " at " + file + ":" +
-            std::to_string(line) + ": " + cudaGetErrorString(status));
-    }
-}
-
-#define CUDA_CHECK(expr) ::fangjia::checkCuda((expr), #expr, __FILE__, __LINE__)
-
-class TrtLogger final : public nvinfer1::ILogger {
-public:
-    explicit TrtLogger(Severity minimum = Severity::kWARNING) : minimum_(minimum) {}
-
-    void log(Severity severity, char const* message) noexcept override {
-        if (severity <= minimum_) {
-            std::cerr << "[TensorRT] " << message << '\n';
-        }
-    }
-
-private:
-    Severity minimum_;
-};
-
-template <typename T>
-struct TrtDeleter {
-    void operator()(T* object) const noexcept { delete object; }
-};
-
-template <typename T>
-using TrtUniquePtr = std::unique_ptr<T, TrtDeleter<T>>;
-
-inline std::vector<std::uint8_t> readBinary(std::filesystem::path const& path) {
-    std::ifstream stream(path, std::ios::binary | std::ios::ate);
-    if (!stream) {
-        throw std::runtime_error("Cannot open " + path.string());
-    }
-    auto const size = stream.tellg();
-    if(size<=0)throw std::runtime_error("Empty or unreadable engine: "+path.string());
-    stream.seekg(0);
-    std::vector<std::uint8_t> bytes(static_cast<std::size_t>(size));
-    if(!stream.read(reinterpret_cast<char*>(bytes.data()), size))throw std::runtime_error("Truncated engine: "+path.string());
-    return bytes;
-}
-
-inline void writeBinary(std::filesystem::path const& path, void const* data, std::size_t size) {
-    std::filesystem::create_directories(path.parent_path());
-    std::ofstream stream(path, std::ios::binary);
-    if (!stream) {
-        throw std::runtime_error("Cannot write " + path.string());
-    }
-    stream.write(static_cast<char const*>(data), static_cast<std::streamsize>(size));
-}
-
-inline std::size_t volume(nvinfer1::Dims const& dims) {
-    std::size_t value = 1;
-    for (int index = 0; index < dims.nbDims; ++index) {
-        if (dims.d[index] < 0) {
-            throw std::runtime_error("Unresolved dynamic tensor dimension");
-        }
-        value *= static_cast<std::size_t>(dims.d[index]);
-    }
-    return value;
-}
-
-inline std::size_t dataTypeSize(nvinfer1::DataType type) {
-    switch (type) {
-    case nvinfer1::DataType::kFLOAT: return 4;
-    case nvinfer1::DataType::kHALF: return 2;
-    case nvinfer1::DataType::kINT8: return 1;
-    case nvinfer1::DataType::kINT32: return 4;
-#if NV_TENSORRT_MAJOR >= 10
-    case nvinfer1::DataType::kINT64: return 8;
-#endif
-    case nvinfer1::DataType::kBOOL: return 1;
-    default: throw std::runtime_error("Unsupported TensorRT data type");
-    }
-}
-
-class CudaEventTimer {
-public:
-    CudaEventTimer() {
-        CUDA_CHECK(cudaEventCreate(&start_));
-        CUDA_CHECK(cudaEventCreate(&end_));
-    }
-    ~CudaEventTimer() {
-        cudaEventDestroy(start_);
-        cudaEventDestroy(end_);
-    }
-    void start(cudaStream_t stream) { CUDA_CHECK(cudaEventRecord(start_, stream)); }
-    float stop(cudaStream_t stream) {
-        CUDA_CHECK(cudaEventRecord(end_, stream));
-        CUDA_CHECK(cudaEventSynchronize(end_));
-        float milliseconds = 0.0F;
-        CUDA_CHECK(cudaEventElapsedTime(&milliseconds, start_, end_));
-        return milliseconds;
-    }
-
-private:
-    cudaEvent_t start_{};
-    cudaEvent_t end_{};
-};
-
-} // namespace fangjia