TensorRT之安装与测试（Windows和Linux环境下安装TensorRT-5.0）

1 Win7+CUDA9.0+TensorRT-5.0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

将TensorRT解压位置\lib下的dll文件复制到C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.0\bin目录下

1-4 测试示例代码

用VS2017打开sampleMNIST示例（D:\TensorRT-5.0.4.3\samples\sampleMNIST）
a. 将D:\TensorRT-5.0.4.3\lib加入 VC++目录–>可执行文件目录

b. 将D:\TensorRT-5.0.4.3\include加入C/C++ --> 常规 --> 附加包含目录

c.将D:\TensorRT-5.0.4.3\lib加入 VC++目录–>库目录
将nvinfer.lib、nvinfer_plugin.lib、nvonnxparser.lib和nvparsers.lib加入链接器–>输入–>附加依赖项

编译后运行得到结果

2 Ubuntu-16.04+CUDA9.0+TensorRT-5.0安装

2-1下载

https://developer.nvidia.com/nvidia-tensorrt-5x-download

2-2 解压

tar -zxvf TensorRT-5.0.2.6.Ubuntu-16.04.4.x86_64-gnu.cuda-9.0.cudnn7.3.tar.gz
cd TensorRT-5.0.2.6/

2-3 添加环境变量

vim ~/.bashrc
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/liumin/software/TensorRT-5.0.2.6/lib
source ~/.bashrc

2-4 安装 Python TensorRT wheel 文件

cd python/
pip install tensorrt-5.0.2.6-py2.py3-none-any.whl

2-5 安装 Python UFF wheel 文件

cd ../uff/
pip install uff-0.5.5-py2.py3-none-any.whl

2-6 安装 Python graphsurgeon wheel 文件

cd ../graphsurgeon/
pip install graphsurgeon-0.3.2-py2.py3-none-any.whl

2-7 测试

cd samples/sampleMNIST
make
cd ../../bin
./sample_mnist

输出：

Building and running a GPU inference engine for MNIST
…
Output: 0:
1:
2:
3:
4:
5: **********
6:
7:
8:
9:

参考资料
1 TensorRT Installation Guide https://docs.nvidia.com/deeplearning/sdk/tensorrt-install-guide/index.html
2 TensorRT Documentation https://docs.nvidia.com/deeplearning/sdk/tensorrt-api/c_api/index.html
3 Best Practices For TensorRT Performance https://docs.nvidia.com/deeplearning/sdk/tensorrt-best-practices/index.html
4 TensorRT Developer Guide https://docs.nvidia.com/deeplearning/sdk/tensorrt-developer-guide/index.html
5 TensorRT API https://docs.nvidia.com/deeplearning/sdk/tensorrt-api/index.html
6 Samples Support Guide https://docs.nvidia.com/deeplearning/sdk/tensorrt-sample-support-guide/index.html