'install', '--extra-index-url', 'https://pypi.nvidia.com', 'tensorrt_cu12_libs==10.8.0.43', 'tensorrt_cu12_bindings==10.8.0.43']' returned non-zero exit status 2. 判断为在nvidia服务器上链接失败原因,所以我手动下载这两个依赖,加上镜像源 -i https://pypi.mirrors.ustc.edu.cn/simple/ ...
例如下载TensorRT-7.2.3.4.Ubuntu-18.04.x86_64-gnu.cuda-11.1.cudnn8.1.tar.gz,下载好后,tar -zxvf解压即可。 解压之后我们需要添加环境变量,以便让我们的程序能够找到TensorRT的libs。 vim ~/.bashrc # 添加以下内容 export LD_LIBRARY_PATH=/path/to/TensorRT-7.2.3.4/lib:$LD_LIBRARY_PATH export LIBRARY_...
针对你遇到的“error: could not build wheels for tensorrt-cu12, which is required to install”错误,以下是一些可能的解决步骤,帮助你解决这个问题: 确认CUDA和cuDNN的安装与兼容性: 确保你已经安装了CUDA 12.x和与TensorRT兼容的cuDNN版本。你可以访问NVIDIA的官方网站来查找TensorRT支持的CUDA和cuDNN版本。
target_link_libraries(tensorrt ${CUDA_LIBRARIES} ${TENSORRT_LIBRARY} ${CUDA_CUBLAS_LIBRARIES} ${CUDA_cudart_static_LIBRARY} ${OpenCV_LIBS}) cmake文件主要注意的几点是cuda和TensorRT动态链接库的查找,只要这几个必备的动态链接库使用cmake查找到就可以编译成功,另外由于我是用了Opencv,所以也将Opencv也加入...
tar -xvzf TensorRT-7.0.0.11.Ubuntu-16.04.x86_64-gnu.cuda-10.0.cudnn7.6.tar.gz export TRT_RELEASE=`pwd`/TensorRT-7.0.0.11 // 环境变量LD_LIBRARY_PATH是系统动态库的查找路径, PATH是系统可执行文件的查找路径 export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$TRT_RELEASE/lib ...
https://www.lfd.uci.edu/~gohlke/pythonlibs/#pycuda上找到对应CUDA,python的版本。 安装graphsurgeon,onnx_graphsurgeon,uff,python目录下的whl文件。 3、TensorRT测试 简单测试一下 三、TensorRT用例测试 1、首先将.pt转换为.engine:.pt ->.onnx ->.engine 1.1、pt模型转onnx模型代码 代码语言:javascript 代...
{OpenCV_LIBS} # OpenCV 库 ${CUDA_LIBRARIES} # CUDA 库 ${CUDA_cublas_LIBRARY} # CUDA BLAS 库 ${CUDA_cudart_LIBRARY} # CUDA Runtime 库 ${CUDA_cudnn_LIBRARY} # CUDA cuDNN 库 ${CUDAToolkit_LIBRARIES} # CUDA Toolkit 库 ) # 设置可执行文件的输出路径 set(EXECUTABLE_OUTPUT_PATH "${C...
set ZLIB_LIBRARY_RELEASE=D:/extlibs/zlib/build-msvc-static/install/lib/zlibstatic.lib set CUDA_HOME=F:\NVIDIA\CUDA\v11.6 set CUDNN_HOME=F:\NVIDIA\CUDNN\v8.5 set TENSORRT_HOME=F:\NVIDIA\TensorRT\v8.4.3.1 set HTTP_PROXY=http://127.0.0.1:10809 rem 你懂的 ...
(tensorrt_libs) ‣ Python bindings matching the Python version in use (tensorrt_bindings) ‣ Frontend source package, which pulls in the correct version of dependent TensorRT modules from pypi.nvidia.com (tensorrt) ‣ You can append -cu11 or -cu12 to any of the Python modules if you ...
pip uninstall tensorrt-libs pip uninstall tensorrt-bindings pip uninstall nvidia-cuda-nvrtc-cu11 pip uninstall nvidia-cuda-runtime-cu11 pip uninstall nvidia-cudnn-cu11 pip uninstall nvidia-cublas-cu11 pip uninstall polygraphy #安装 pip install nvidia-cudnn-cu12 ...