forked from floratest1/SpireCV
96 lines
4.0 KiB
Bash
Executable File
96 lines
4.0 KiB
Bash
Executable File
#!/bin/sh
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echo "\033[32m[INFO]:\033[0m Please enter the folder path of the installation package: "
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# package_dir="/home/jario/Downloads/nv"
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wget https://download.amovlab.com/model/install/x86-nvidia/cuda-repo-ubuntu1804-11-1-local_11.1.1-455.32.00-1_amd64.deb
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wget https://download.amovlab.com/model/install/x86-nvidia/cudnn-11.3-linux-x64-v8.2.1.32.tgz
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wget https://download.amovlab.com/model/install/x86-nvidia/nv-tensorrt-repo-ubuntu1804-cuda11.3-trt8.0.1.6-ga-20210626_1-1_amd64.deb
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wget https://download.amovlab.com/model/install/x86-nvidia/cuda-ubuntu1804.pin
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package_dir="."
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cuda_fn=$package_dir"/cuda-repo-ubuntu1804-11-1-local_11.1.1-455.32.00-1_amd64.deb"
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cudnn_fn=$package_dir"/cudnn-11.3-linux-x64-v8.2.1.32.tgz"
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tensorrt_fn=$package_dir"/nv-tensorrt-repo-ubuntu1804-cuda11.3-trt8.0.1.6-ga-20210626_1-1_amd64.deb"
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tmp_dir="/tmp"
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echo "\033[32m[INFO]: CUDA_PKG: \033[0m"$cuda_fn
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echo "\033[32m[INFO]: CUDNN_PKG: \033[0m"$cudnn_fn
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echo "\033[32m[INFO]: TENSORRT_PKG: \033[0m"$tensorrt_fn
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# 所有文件都存在时，才会继续执行脚本
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if [ ! -f "$cuda_fn" ]; then
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echo "\033[31m[ERROR]: CUDA_PKG not exist!: \033[0m"
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exit 1
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fi
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if [ ! -f "$cudnn_fn" ]; then
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echo "\033[31m[ERROR]: CUDNN_PKG not exist!: \033[0m"
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exit 1
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fi
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if [ ! -f "$tensorrt_fn" ]; then
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echo "\033[31m[ERROR]: TENSORRT_PKG not exist!: \033[0m"
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exit 1
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fi
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# 删除显卡驱动
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# sudo apt-get remove nvidia-*
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# 安装显卡驱动
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# echo "\033[32m[INFO]: Nvidia Driver installing ...\033[0m"
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# ubuntu-drivers devices
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# sudo ubuntu-drivers autoinstall
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# 删除已安装CUDA
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# --purge选项会将配置文件、数据库等删除
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# sudo apt-get autoremove --purge cuda
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# 查看安装了哪些cuda相关的库，可以用以下指令
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# sudo dpkg -l |grep cuda
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# sudo dpkg -P cuda-repo-ubuntu1804-10-2-local-10.2.89-440.33.01
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# sudo dpkg -P cuda-repo-ubuntu1804-11-1-local
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# sudo dpkg -P nv-tensorrt-repo-ubuntu1804-cuda10.2-trt8.0.1.6-ga-20210626
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# 这个key值是官网文档查到的，当然通过apt-key list也能查看
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# sudo apt-key list
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# sudo apt-key del 7fa2af80
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# 安装CUDA
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echo "\033[32m[INFO]: CUDA installing ...\033[0m"
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# wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
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sudo cp $package_dir/cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
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sudo dpkg -i $cuda_fn
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sudo apt-key add /var/cuda-repo-ubuntu1804-11-1-local/7fa2af80.pub
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sudo apt-get update
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sudo apt-get -y install cuda
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# 安装CUDNN
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echo "\033[32m[INFO]: CUDNN installing ...\033[0m"
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tar zxvf $cudnn_fn -C $tmp_dir
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sudo cp $tmp_dir/cuda/include/cudnn* /usr/local/cuda/include/
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sudo cp $tmp_dir/cuda/lib64/libcudnn* /usr/local/cuda/lib64/
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sudo chmod a+r /usr/local/cuda/include/cudnn* /usr/local/cuda/lib64/libcudnn*
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sudo ln -sf /usr/local/cuda/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.2.1 /usr/local/cuda/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8
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sudo ln -sf /usr/local/cuda/targets/x86_64-linux/lib/libcudnn.so.8.2.1 /usr/local/cuda/targets/x86_64-linux/lib/libcudnn.so.8
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sudo ln -sf /usr/local/cuda/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.2.1 /usr/local/cuda/targets/x86_64-linux/lib/libcudnn_ops_train.so.8
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sudo ln -sf /usr/local/cuda/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.2.1 /usr/local/cuda/targets/x86_64-linux/lib/libcudnn_adv_train.so.8
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sudo ln -sf /usr/local/cuda/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.2.1 /usr/local/cuda/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8
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sudo ln -sf /usr/local/cuda/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.2.1 /usr/local/cuda/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8
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sudo ln -sf /usr/local/cuda/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.2.1 /usr/local/cuda/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8
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# 安装TensorRT
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sudo dpkg -i $tensorrt_fn
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sudo apt-key add /var/nv-tensorrt-repo-cuda11.3-trt8.0.1.6-ga-20210626/7fa2af80.pub
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sudo apt-get update
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sudo apt-get install tensorrt -y
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sudo apt-get install python3-libnvinfer-dev -y
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sudo rm $cuda_fn
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sudo rm $cudnn_fn
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sudo rm $tensorrt_fn
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sudo rm cuda-ubuntu1804.pin
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