ii graphsurgeon-tf7.1.0-1+cuda10.2amd64 GraphSurgeonforTensorRTpackageii libnvinfer-bin7.1.0-1+cuda10.2amd64 TensorRT binaries ii libnvinfer-dev7.1.0-1+cuda10.2amd64 TensorRT development libraries and headers ii libnvinfer-doc7.1.0-1+cuda10.2all TensorRT documentation ii libnvinfer-plugin-dev7.1....
ii libnvinfer-plugin7 7.2.3-1+cuda11.1 amd64 TensorRT plugin libraries ii libnvinfer-samples 7.2.3-1+cuda11.1 all TensorRT samples ii libnvinfer7 7.2.3-1+cuda11.1 amd64 TensorRT runtime libraries ii libnvonnxparsers-dev 7.2.3-1+cuda11.1 amd64 TensorRT ONNX libraries ii libnvonnxparser...
target_link_libraries(tensorrt ${CUDA_LIBRARIES} ${TENSORRT_LIBRARY} ${CUDA_CUBLAS_LIBRARIES} ${CUDA_cudart_static_LIBRARY} ${OpenCV_LIBS}) cmake文件主要注意的几点是cuda和TensorRT动态链接库的查找,只要这几个必备的动态链接库使用cmake查找到就可以编译成功,另外由于我是用了Opencv,所以也将Opencv也加入...
ii libnvinfer8 8.4.0-1+cuda11.6 amd64 TensorRT runtime libraries ii libnvonnxparsers-dev 8.4.0-1+cuda11.6 amd64 TensorRT ONNX libraries ii libnvonnxparsers8 8.4.0-1+cuda11.6 amd64 TensorRT ONNX libraries ii libnvparsers-dev 8.4.0-1+cuda11.6 amd64 TensorRT parsers libraries ii libnv...
算子层已经开始和底层硬件打交道,这部分的IR对接和优化需要处理器开发者提供,例如Intel的MKL, Nvidia的CuDNN和TensorRT,这些“libraries”是处理器开发者经过精细优化的高效算法,它们深度结合了处理器的特点。例如:CuDNN就会采用适合的精度来调用Tensor Core来进行矩阵运算,这比直接用CUDA core内其它计算单元快N倍。
1 Win7+CUDA9.0+TensorRT安装 1-1 下载对应TensorRT版本 https://developer.nvidia.com/nvidia-tensorrt-5x-download 这里我们选择 TensorRT 5.0 GA For Windows 1-2 解压 TensorRT 1-3 配置环境变量 将TensorRT解压位置\lib 加入系统环境变量 ...
ii libnvinfer-plugin-dev 8.2.4-1+cuda11.4 amd64 TensorRT plugin libraries ... ... 关于那两个巨坑 第1 个坑说白了就是要在安装前,一定要先验证一下有没有装好 CUDA,可以用下面的命令查询一下: dpkg -l | grep cuda# 会像上面一样,列出所有 CUDA 相关的包 ...
Getting started with TensorRT 10.0 is easier, thanks to updated Debian and RPM metapackages. For example,>apt-get install tensorrtorpip install tensorrtwill install all relevant TensorRT libraries for C++ or Python. In addition, Debug Tensors is a newly added API to mark tensors as debug ...
Hi, I try convert onnx model to tensortRT C++ API but I couldn't. My system: I have a jetson tx2, tensorRT6 (and tensorRT 5.1.6 on different tx2) I tried to this commend cmake . -DCUDA_INCLUDE_DIRS=/usr/local/cuda/include -DTENSORRT_ROOT...
TRT_LIB_DIR: Path to the TensorRT installation directory containing libraries. TRT_OUT_DIR: Output directory where generated build artifacts will be copied. Optional CMake build arguments: CMAKE_BUILD_TYPE: Specify if binaries generated are for release or debug (contain debug symbols). Values cons...