https://www.nvidia.co.uk/NVIDIA-Linux-x86_64-460.39.run&lang=uk&type=TITAN

https://www.nvidia.co.uk/content/DriverDownload-March2009/confirmation.php?url=/XFree86/Linux-x86_64/460.39/NVIDIA-Linux-x86_64-460.39.run&lang=uk&type=TITAN

GTX 1650Ti：
https://www.nvidia.cn/Linux-x86_64-460.39.run&lang=cn&type=TITAN

CUDA11.2:
https://developer.nvidia.com/cuda

wget https://developer.download.nvidia.com/compute/cuda/11.2.0/local_installers/cuda_11.2.0_460.27.04_linux.run
sudo sh cuda_11.2.0_460.27.04_linux.run

CUDNN:
https://developer.nvidia.com/rdp/cudnn-archive

推荐迅雷下载：直接复制以下链接到迅雷下载即可
cudnn-11.1-linux-x64-v8.0.4.30.tgz
cudnn-11.1-linux-x64-v8.0.4.30.tgz

在这里插入图片描述
双击复制到迅雷弹出下载界面：

注意：安装驱动时，要注意匹配自己本机的算力，以便更好地实现模型的加速和算法策略的生成。

算力查询地址：
https://developer.nvidia.com/cuda-gpus#compute

在这里插入图片描述
案例：yolov3检测框的丢失，相关分析可参考文章：

https://blog.csdn.net/weixin_43915860/article/details/103180908

以前PyTorch版本

Commands for Versions >= 1.0.0
v1.6.0
Conda
OSX

# conda
conda install pytorch==1.6.0 torchvision==0.7.0 -c pytorch

Linux and Windows

# CUDA 9.2
conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=9.2 -c pytorch

# CUDA 10.1
conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.1 -c pytorch

# CUDA 10.2
conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.2 -c pytorch

# CPU Only
conda install pytorch==1.6.0 torchvision==0.7.0 cpuonly -c pytorch

Wheel
OSX

pip install torch==1.6.0 torchvision==0.7.0

Linux and Windows

# CUDA 10.2
pip install torch==1.6.0 torchvision==0.7.0

# CUDA 10.1
pip install torch==1.6.0+cu101 torchvision==0.7.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html

# CUDA 9.2
pip install torch==1.6.0+cu92 torchvision==0.7.0+cu92 -f https://download.pytorch.org/whl/torch_stable.html

# CPU only
pip install torch==1.6.0+cpu torchvision==0.7.0+cpu -f https://download.pytorch.org/whl/torch_stable.html

v1.5.1
Conda
OSX

# conda
conda install pytorch==1.5.1 torchvision==0.6.1 -c pytorch

Linux and Windows

# CUDA 9.2
conda install pytorch==1.5.1 torchvision==0.6.1 cudatoolkit=9.2 -c pytorch

# CUDA 10.1
conda install pytorch==1.5.1 torchvision==0.6.1 cudatoolkit=10.1 -c pytorch

# CUDA 10.2
conda install pytorch==1.5.1 torchvision==0.6.1 cudatoolkit=10.2 -c pytorch

# CPU Only
conda install pytorch==1.5.1 torchvision==0.6.1 cpuonly -c pytorch

Wheel
OSX

pip install torch==1.5.1 torchvision==0.6.1

Linux and Windows

# CUDA 10.2
pip install torch==1.5.1 torchvision==0.6.1

# CUDA 10.1
pip install torch==1.5.1+cu101 torchvision==0.6.1+cu101 -f https://download.pytorch.org/whl/torch_stable.html

# CUDA 9.2
pip install torch==1.5.1+cu92 torchvision==0.6.1+cu92 -f https://download.pytorch.org/whl/torch_stable.html

# CPU only
pip install torch==1.5.1+cpu torchvision==0.6.1+cpu -f https://download.pytorch.org/whl/torch_stable.html

v1.5.0
Conda
OSX

# conda
conda install pytorch==1.5.0 torchvision==0.6.0 -c pytorch

Linux and Windows

# CUDA 9.2
conda install pytorch==1.5.0 torchvision==0.6.0 cudatoolkit=9.2 -c pytorch

# CUDA 10.1
conda install pytorch==1.5.0 torchvision==0.6.0 cudatoolkit=10.1 -c pytorch

# CUDA 10.2
conda install pytorch==1.5.0 torchvision==0.6.0 cudatoolkit=10.2 -c pytorch

# CPU Only
conda install pytorch==1.5.0 torchvision==0.6.0 cpuonly -c pytorch

Wheel
OSX

pip install torch==1.5.0 torchvision==0.6.0

Linux and Windows

# CUDA 10.2
pip install torch==1.5.0 torchvision==0.6.0

# CUDA 10.1
pip install torch==1.5.0+cu101 torchvision==0.6.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html

# CUDA 9.2
pip install torch==1.5.0+cu92 torchvision==0.6.0+cu92 -f https://download.pytorch.org/whl/torch_stable.html

# CPU only
pip install torch==1.5.0+cpu torchvision==0.6.0+cpu -f https://download.pytorch.org/whl/torch_stable.html

v1.4.0
Conda
OSX

# conda
conda install pytorch==1.4.0 torchvision==0.5.0 -c pytorch

Linux and Windows

# CUDA 9.2
conda install pytorch==1.4.0 torchvision==0.5.0 cudatoolkit=9.2 -c pytorch

# CUDA 10.1
conda install pytorch==1.4.0 torchvision==0.5.0 cudatoolkit=10.1 -c pytorch

# CPU Only
conda install pytorch==1.4.0 torchvision==0.5.0 cpuonly -c pytorch

Wheel
OSX

pip install torch==1.4.0 torchvision==0.5.0

Linux and Windows

# CUDA 10.1
pip install torch==1.4.0 torchvision==0.5.0

# CUDA 9.2
pip install torch==1.4.0+cu92 torchvision==0.5.0+cu92 -f https://download.pytorch.org/whl/torch_stable.html

# CPU only
pip install torch==1.4.0+cpu torchvision==0.5.0+cpu -f https://download.pytorch.org/whl/torch_stable.html

v1.2.0
Conda
OSX

# conda
conda install pytorch==1.2.0 torchvision==0.4.0 -c pytorch

Linux and Windows

# CUDA 9.2
conda install pytorch==1.2.0 torchvision==0.4.0 cudatoolkit=9.2 -c pytorch

# CUDA 10.0
conda install pytorch==1.2.0 torchvision==0.4.0 cudatoolkit=10.0 -c pytorch

# CPU Only
conda install pytorch==1.2.0 torchvision==0.4.0 cpuonly -c pytorch

Wheel
OSX

pip install torch==1.2.0 torchvision==0.4.0

Linux and Windows

# CUDA 10.0
pip install torch==1.2.0 torchvision==0.4.0

# CUDA 9.2
pip install torch==1.2.0+cu92 torchvision==0.4.0+cu92 -f https://download.pytorch.org/whl/torch_stable.html

# CPU only
pip install torch==1.2.0+cpu torchvision==0.4.0+cpu -f https://download.pytorch.org/whl/torch_stable.html

v1.1.0
Conda
OSX

# conda
conda install pytorch==1.1.0 torchvision==0.3.0 -c pytorch

Linux and Windows

# CUDA 9.0
conda install pytorch==1.1.0 torchvision==0.3.0 cudatoolkit=9.0 -c pytorch

# CUDA 10.0
conda install pytorch==1.1.0 torchvision==0.3.0 cudatoolkit=10.0 -c pytorch

# CPU Only
conda install pytorch-cpu==1.1.0 torchvision-cpu==0.3.0 cpuonly -c pytorch

Wheel
OSX

pip install torch==1.1.0 torchvision==0.3.0

Linux and Windows

# CUDA 10.0
Download and install wheel from https://download.pytorch.org/whl/cu100/torch_stable.html

# CUDA 9.0
Download and install wheel from https://download.pytorch.org/whl/cu90/torch_stable.html

# CPU only
Download and install wheel from https://download.pytorch.org/whl/cpu/torch_stable.html

v1.0.1
Conda
OSX

# conda
conda install pytorch==1.0.1 torchvision==0.2.2 -c pytorch

Linux and Windows

# CUDA 9.0
conda install pytorch==1.0.1 torchvision==0.2.2 cudatoolkit=9.0 -c pytorch

# CUDA 10.0
conda install pytorch==1.0.1 torchvision==0.2.2 cudatoolkit=10.0 -c pytorch

# CPU Only
conda install pytorch-cpu==1.0.1 torchvision-cpu==0.2.2 cpuonly -c pytorch

Wheel
OSX

pip install torch==1.0.1 torchvision==0.2.2

Linux and Windows

# CUDA 10.0
Download and install wheel from https://download.pytorch.org/whl/cu100/torch_stable.html

# CUDA 9.0
Download and install wheel from https://download.pytorch.org/whl/cu90/torch_stable.html

# CPU only
Download and install wheel from https://download.pytorch.org/whl/cpu/torch_stable.html

v1.0.0
Conda
OSX

# conda
conda install pytorch==1.0.0 torchvision==0.2.1 -c pytorch

Linux and Windows

# CUDA 10.0
conda install pytorch==1.0.0 torchvision==0.2.1 cuda100 -c pytorch

# CUDA 9.0
conda install pytorch==1.0.0 torchvision==0.2.1 cuda90 -c pytorch

# CUDA 8.0
conda install pytorch==1.0.0 torchvision==0.2.1 cuda80 -c pytorch

# CPU Only
conda install pytorch-cpu==1.0.0 torchvision-cpu==0.2.1 cpuonly -c pytorch

Wheel
OSX

pip install torch==1.0.0 torchvision==0.2.1

Linux and Windows

# CUDA 10.0
Download and install wheel from https://download.pytorch.org/whl/cu100/torch_stable.html

# CUDA 9.0
Download and install wheel from https://download.pytorch.org/whl/cu90/torch_stable.html

# CUDA 8.0
Download and install wheel from https://download.pytorch.org/whl/cu80/torch_stable.html

# CPU only
Download and install wheel from https://download.pytorch.org/whl/cpu/torch_stable.html

Commands for Versions < 1.0.0
Via conda

    This should be used for most previous macOS version installs.

To install a previous version of PyTorch via Anaconda or Miniconda, replace “0.4.1” in the following commands with the desired version (i.e., “0.2.0”).

Installing with CUDA 9

conda install pytorch=0.4.1 cuda90 -c pytorch

or

conda install pytorch=0.4.1 cuda92 -c pytorch

Installing with CUDA 8

conda install pytorch=0.4.1 cuda80 -c pytorch

Installing with CUDA 7.5

conda install pytorch=0.4.1 cuda75 -c pytorch

Installing without CUDA

conda install pytorch=0.4.1 -c pytorch

https://pytorch.org/get-started/locally/](https://pytorch.org/get-started/locally/)

(ubuntu版本)快速下载NVIDIA最新显卡驱动RTX3080ti、GTX1650ti、CUDA11.2，CUDNN的地址

以前PyTorch版本

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