TensorRT cache file loading error on Windows

[jiangjiajun]

[DefTruth]

cache反序列化问题已经修复。另外经排查，用户的测试代码中指针的用法会导致无法预测，需要进行修改。

#include "fastdeploy/vision.h"

void TrtInfer(const std::string& model_file, const std::string& image_file) {
	struct fastdeploy::RuntimeOption roi_option;
	fastdeploy::vision::detection::YOLOv7End2EndTRT* model;

	roi_option.UseGpu();
	roi_option.UseTrtBackend();
	roi_option.SetTrtInputShape("images", { 1, 3, 640, 640 });
	roi_option.EnableTrtFP16();
	roi_option.SetTrtCacheFile("yolo_end2end.cache");
    
	// model =
	// 	&fastdeploy::vision::detection::YOLOv7End2EndTRT(model_file, "", roi_option);
        //  这行指针赋值代码用法修改成以下这句
	model = new fastdeploy::vision::detection::YOLOv7End2EndTRT(model_file, "", roi_option);
	if (!model->Initialized()) {
		std::cerr << "Failed to initialize." << std::endl;
		return;
	}
	auto im = cv::imread(image_file);
	fastdeploy::vision::DetectionResult res;
	if (!model->Predict(&im, &res)) {
		std::cerr << "Failed to predict." << std::endl;
		return;
	}
	std::cout << res.Str() << std::endl;
        delete model;
}

int main() {
      TrtInfer("yolov7-end2end-trt-nms.onnx", "000000014439.jpg");
      return 0;
}

首次运行会保存cache文件，log如下

[INFO] fastdeploy/backends/tensorrt/trt_backend.cc(416)::fastdeploy::TrtBackend::BuildTrtEngine Start to building TensorRT Engine...
[INFO] fastdeploy/backends/tensorrt/trt_backend.cc(488)::fastdeploy::TrtBackend::BuildTrtEngine TensorRT Engine is built succussfully.
[INFO] fastdeploy/backends/tensorrt/trt_backend.cc(490)::fastdeploy::TrtBackend::BuildTrtEngine Serialize TensorRTEngine to local file yolo_end2end.cache.
[INFO] fastdeploy/backends/tensorrt/trt_backend.cc(501)::fastdeploy::TrtBackend::BuildTrtEngine TensorRTEngine is serialized to local file yolo_end2end.cache, we can load this model from the seralized engine directly next time.
[INFO] fastdeploy/runtime.cc(289)::fastdeploy::Runtime::Init    Runtime initialized with Backend::TRT in Device::GPU.

第二次及之后运行，直接从cache中加载，加快初始化

[INFO] fastdeploy/backends/tensorrt/trt_backend.cc(541)::fastdeploy::TrtBackend::CreateTrtEngineFromOnnx        Detect serialized TensorRT Engine file in yolo_end2end.cache, will load it directly.
[INFO] fastdeploy/backends/tensorrt/trt_backend.cc(106)::fastdeploy::TrtBackend::LoadTrtCache   Build TensorRT Engine from cache file: yolo_end2end.cache with shape range information as below,
[INFO] fastdeploy/backends/tensorrt/trt_backend.cc(109)::fastdeploy::TrtBackend::LoadTrtCache   Input name: images, shape=[1, 3, 640, 640], min=[1, 3, 640, 640], max=[1, 3, 640, 640]
[INFO] fastdeploy/runtime.cc(289)::fastdeploy::Runtime::Init    Runtime initialized with Backend::TRT in Device::GPU.

[WXL-steven]

我遇到了相似的错误，问题似乎依旧存在？

此外，检查了trt_backend.cc文件，之前的pull #274 已被合并。

[jiangjiajun]

此ISSUE由于一年未更新，将会关闭处理，如有需要，可再次更新打开。