从tuna上下载Anaconda版本 3-5.3.1_linux_x86_64.(其它版本也可以,本教程采用3-5.3.1)
cd Downloads
bash Anaconda3-5.3.1-Linux-x86_64.sh
一直按住Enter.直到选择yes or no.
除了安装vs code选择no, 其余选yes.
将anaconda加入路径:
vim ~/.bashrc
增加最后一行:
export PATH="/home/lxj/anaconda3/bin:$PATH"
立即生效
source ~/.bashrc
此时,默认python已经切为Anaconda环境的 python3了
官方下载cuda10.1 for ubuntu18.04
下载结束后
cd Downloads
sudo dpkg -i cuda-repo-ubuntu1804-10-1-local-10.1.105-418.39_1.0-1_amd64.deb
sudo apt-key add /var/cuda-repo-10-1-local-10.1.105-418.39/7fa2af80.pub
sudo apt-get update
sudo apt-get install cuda-10-1
官方下载cudnn for linux v7.6.5 for cuda 10.1
解压cudnn
cp cudnn-10.1-linux-x64-v5.1.solitairetheme8 cudnn-8.0-linux-x64-v5.1.tgz
tar -zxvf cudnn-10.1-linux-x64-v7.6.5.32.tgz
移动到cuda目录下
sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda-10.1/lib64/
sudo cp cuda/include/cudnn.h /usr/local/cuda-10.1/include/
为所有用户设置读取权限
sudo chmod a+r /usr/local/cuda-10.1/include/cudnn.h
sudo chmod a+r /usr/local/cuda-10.1/lib64/libcudnn*
安装libcupti 也就是NVIDIA cuda分析工具接口
sudo apt-get install libcupti-dev
配置环境变量
export PATH="/usr/local/cuda-10.1/bin:$PATH"
export LD_LIBRARY_PATH="usr/local/cuda-10.1/lib64:$LD_LIBRARY_PATH"
核实安装成功
nvcc -V
#Cuda compilation tools, release 10.1, V10.1.105
sudo apt-get install python3-dev python3-pip
该步骤仅仅为了区分我电脑上其它python环境,如果嫌麻烦可以跳过.
conda create -n trt python=3.6
source activate
source deactivate #防止下一行报错
conda activate trt #激活新环境,接下来的包安装在trt环境中
当前使用版本号6.0.1.5 GA for ubuntu 18.04
TensorRT 6.0.1.5 GA for Ubuntu 1804 and CUDA 10.1 DEB local repo packages
下载结束后解压
cd Downloads
tar -xvf TensorRT-6.0.1.5.Ubuntu-18.04.x86_64-gnu.cuda-10.1.cudnn7.6.tar.gz
在trt环境中,安装python版本
cd TensorRT-6.0.1.5/python
pip3 install tensorrt-6.0.1.5-cp36-none-linux_x86_64.whl
加入环境变量
vim ~/.bashrc
export LD_LIBRARY_PATH="/home/lxj/Downloads/TensorRT-6.0.1.5/targets/x86_64-linux-gnu/lib:$LD_LIBRARY_PATH"
source ~/.bashrc
source deactivate
source activate
conda activate trt
python
import tensorrt
tensorrt.__version__
#'6.0.1.5'
cd ../uff
pip3 install uff-0.6.5-py2.py3-none-any.whl
cd ../graphsurgeon
pip3 install graphsurgeon-0.4.1-py2.py3-none-any.whl