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标题:尝试用Paddle-Lite推理开源的Lightglue模型,一调Run()函数就crash了
版本、预测库信息: 1)Paddle Lite 版本:v2.13rc 2)Host 环境: 3)运行设备环境:展锐T760(UMS9620W)/Android 4)预测后端信息:CPU/GPU
预测信息 1)预测 API:C++ 2)预测选项信息:arm64-v8a、4线程 3)预测库来源:官网下载
复现信息:如为报错,请提供剥离业务环境的可复现预测 demo,用于问题复现 开源模型:https://github.com/fabio-sim/LightGlue-ONNX.git 模型转化路径:pytorch-->onnx-->nb x2paddle --framework=onnx --model=lightglue_1.onnx --save_dir=lightglue_1_paddlelite --to_lite=True --lite_valid_places=arm --lite_model_type=naive_buffer
问题描述:请详细描述您的问题,同步贴出报错信息、日志/代码关键片段 代码:
// -------------------------step 1: create predictor------------------------------ // paddle::lite_api::MobileConfig mb_config; mb_config.set_model_from_file(config->model_path); mb_config.set_threads(config->num_threads); //mb_config.set_power_mode(paddle::lite_api::LITE_POWER_HIGH); predictor = CreatePaddlePredictor<paddle::lite_api::MobileConfig>(mb_config); ... // -------------------------step 2: copy input data------------------------------ // std::unique_ptr<paddle::lite_api::Tensor> input_kpts0_tensor(std::move(predictor->GetInput(0))); input_kpts0_tensor->Resize({1, keypoints0.shape[2], 2}); auto* input_kpts0_data = input_kpts0_tensor->mutable_data<float>(); memcpy(input_kpts0_data, keypoints0.data, keypoints0.length * sizeof(float)); std::unique_ptr<paddle::lite_api::Tensor> input_kpts1_tensor(std::move(predictor->GetInput(1))); input_kpts1_tensor->Resize({1, keypoints1.shape[2], 2}); auto* input_kpts1_data = input_kpts1_tensor->mutable_data<float>(); memcpy(input_kpts1_data, keypoints1.data, keypoints1.length * sizeof(float)); std::unique_ptr<paddle::lite_api::Tensor> input_desc0_tensor(std::move(predictor->GetInput(2))); input_desc0_tensor->Resize({1, descriptors0.shape[2], descriptors0.shape[3]}); auto* input_desc0_data = input_desc0_tensor->mutable_data<float>(); memcpy(input_desc0_data, descriptors0.data, descriptors0.length * sizeof(float)); std::unique_ptr<paddle::lite_api::Tensor> input_desc1_tensor(std::move(predictor->GetInput(3))); input_desc1_tensor->Resize({1, descriptors1.shape[2], descriptors1.shape[3]}); auto* input_desc1_data = input_desc1_tensor->mutable_data<float>(); memcpy(input_desc1_data, descriptors1.data, descriptors1.length * sizeof(float)); // -------------------------step 3: run model------------------------------ // timespec begin, end; gettime(begin); predictor->Run(); // 这里crash了 gettime(end); LOGD("Inference -- step 3: Paddle-Lite, %d threads, run lightglue complete, time: %d", this->config.num_threads, get_milliseconds(begin, end)); // -------------------------step 4: parse output--------------------------- // std::vector<std::string> output_names = predictor->GetOutputNames(); assert(output_names.size() == 1); ...
调用Run()函数就crash了,报错日志: 2024-04-30 14:59:17.576 18781-18781/com.abcde.pointglue A/libc: Fatal signal 11 (SIGSEGV), code 1 (SEGV_MAPERR), fault addr 0x70d5a85514 in tid 18781 (abcde.pointglue), pid 18781 (abcde.pointglue)
The text was updated successfully, but these errors were encountered:
运行前 export GLOG_v=5,执行的时候加上 >log.txt 2>&1 就可以将 log 重定向到 log.txt 文件,把log.txt和nb模型放上来哈~
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MuShangCC
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标题:尝试用Paddle-Lite推理开源的Lightglue模型,一调Run()函数就crash了
版本、预测库信息:
1)Paddle Lite 版本:v2.13rc
2)Host 环境:
3)运行设备环境:展锐T760(UMS9620W)/Android
4)预测后端信息:CPU/GPU
预测信息
1)预测 API:C++
2)预测选项信息:arm64-v8a、4线程
3)预测库来源:官网下载
复现信息:如为报错,请提供剥离业务环境的可复现预测 demo,用于问题复现
开源模型:https://github.com/fabio-sim/LightGlue-ONNX.git
模型转化路径:pytorch-->onnx-->nb
x2paddle --framework=onnx
--model=lightglue_1.onnx
--save_dir=lightglue_1_paddlelite
--to_lite=True
--lite_valid_places=arm
--lite_model_type=naive_buffer
问题描述:请详细描述您的问题,同步贴出报错信息、日志/代码关键片段
代码:
调用Run()函数就crash了,报错日志:
2024-04-30 14:59:17.576 18781-18781/com.abcde.pointglue A/libc: Fatal signal 11 (SIGSEGV), code 1 (SEGV_MAPERR), fault addr 0x70d5a85514 in tid 18781 (abcde.pointglue), pid 18781 (abcde.pointglue)
The text was updated successfully, but these errors were encountered: