(conda + pip) Configure the deep learning environment of each version of Pytorch

1 Introduction

• When using Anaconda to configure the Pytorch deep learning environment, the installation instructions given by the official website link will be very slow and errors are often reported. To this end, the current mainstream version of pytorch deep learning environment configuration instructions are compiled. The following instructions are suitable for Windows operating systems and run in Anaconda Prompt .
• In addition, sometimes when using conda to install, an error will be reported. The article includes pip installation instructions. Since the pip installation method given on the official website is somewhat unfriendly, certain improvements have been made in the article. Most of the instructions are effective in personal testing.

2. Configure mirror source

Let me tell you in advance : If an HTTP error is reported after configuring the mirror source, you only need to delete the s in https://... in the source link.
Tsinghua Source

conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/ 
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/msys2/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
conda config --set show_channel_urls yes

Dayuan of Science and Technology of China

conda config --add channels https://mirrors.ustc.edu.cn/anaconda/pkgs/main/
conda config --add channels https://mirrors.ustc.edu.cn/anaconda/pkgs/free/
conda config --add channels https://mirrors.ustc.edu.cn/anaconda/cloud/conda-forge/
conda config --add channels https://mirrors.ustc.edu.cn/anaconda/cloud/msys2/
conda config --set show_channel_urls yes

3. Corresponding versions of pytorch, torchvision and python

The corresponding relationship between pytorch, torchvision and python comes from pytorch official github, link: https://github.com/pytorch/vision#installation

4. Create and enter the virtual environment

Create a virtual environment, where pt is the name of the customized virtual environment. In addition, based on pitfall experience, python 3.6.5 version can adapt to more pytorch versions and some additional packages. It is recommended to select version 3.6.5 for the python interpreter version when creating an environment. .

conda create -n pt python=3.6.5

Then click y to agree to the installation and wait for a while to enter the virtual environment.

activate pt

5. Pytorch 0.4.1

# conda
conda install pytorch==0.4.1 torchvision==0.2.1 cuda90  # CUDA 9.0
conda install pytorch==0.4.1 torchvision==0.2.1 cuda92  # CUDA 9.2
conda install pytorch==0.4.1 torchvision==0.2.1 cuda80  # CUDA 8.0
conda install pytorch==0.4.1 torchvision==0.2.1 cuda75  # CUDA 7.5
conda install pytorch==0.4.1 torchvision==0.2.1 cpuonly  # CPU 版本
# pip
pip install https://download.pytorch.org/whl/cu90/torch-0.4.1-cp36-cp36m-win_amd64.whl torchvision==0.2.1  # CUDA 9.0
pip install https://download.pytorch.org/whl/cu92/torch-0.4.1-cp36-cp36m-win_amd64.whl torchvision==0.2.1  # CUDA 9.2
pip install https://download.pytorch.org/whl/cu80/torch-0.4.1-cp36-cp36m-win_amd64.whl torchvision==0.2.1  # CUDA 8.0
pip install https://download.pytorch.org/whl/cu75/torch-0.4.1-cp36-cp36m-win_amd64.whl torchvision==0.2.1  # CUDA 7.5
pip install https://download.pytorch.org/whl/cpu/torch-0.4.1-cp36-cp36m-win_amd64.whl torchvision==0.2.1  # CPU 版本

6. Pytorch 1.0.0

# conda
conda install pytorch==1.0.0 torchvision==0.2.1 cuda100  # CUDA 10.0
conda install pytorch==1.0.0 torchvision==0.2.1 cuda90  # CUDA 9.0
conda install pytorch==1.0.0 torchvision==0.2.1 cuda80  # CUDA 8.0
conda install pytorch-cpu==1.0.0 torchvision-cpu==0.2.1 cpuonly  # CPU 版本
# pip
pip install https://download.pytorch.org/whl/cu100/torch-1.0.0-cp36-cp36m-win_amd64.whl torchvision==0.2.1  # CUDA 10.0
pip install https://download.pytorch.org/whl/cu90/torch-1.0.0-cp36-cp36m-win_amd64.whl torchvision==0.2.1  # CUDA 9.0
pip install https://download.pytorch.org/whl/cu80/torch-1.0.0-cp36-cp36m-win_amd64.whl torchvision==0.2.1  # CUDA 8.0
pip install https://download.pytorch.org/whl/cpu/torch-1.0.0-cp36-cp36m-win_amd64.whl torchvision==0.2.1  # CPU 版本

7. Pytorch 1.0.1

# conda
conda install pytorch==1.0.1 torchvision==0.2.2 cudatoolkit=10.0  # CUDA 10.0
conda install pytorch==1.0.1 torchvision==0.2.2 cudatoolkit=9.0  # CUDA 9.0
conda install pytorch-cpu==1.0.1 torchvision-cpu==0.2.2 cpuonly  # CPU 版本
# pip
pip install https://download.pytorch.org/whl/cu100/torch-1.0.1-cp36-cp36m-win_amd64.whl torchvision==0.2.2  # CUDA 10.0
pip install https://download.pytorch.org/whl/cu90/torch-1.0.1-cp36-cp36m-win_amd64.whl torchvision==0.2.2  # CUDA 9.0
pip install https://download.pytorch.org/whl/cpu/torch-1.0.1-cp36-cp36m-win_amd64.whl torchvision==0.2.2  # CPU 版本

8. Pytorch 1.1.0

# conda
conda install pytorch==1.1.0 torchvision==0.3.0 cudatoolkit=10.0  # CUDA 10.0
conda install pytorch==1.1.0 torchvision==0.3.0 cudatoolkit=9.0  # CUDA 9.0
conda install pytorch-cpu==1.1.0 torchvision-cpu==0.3.0 cpuonly  # CPU 版本
# pip
pip install https://download.pytorch.org/whl/cu100/torch-1.1.0-cp36-cp36m-win_amd64.whl torchvision==0.3.0  # CUDA 10.0
pip install https://download.pytorch.org/whl/cu90/torch-1.1.0-cp36-cp36m-win_amd64.whl torchvision==0.3.0  # CUDA 9.0
pip install https://download.pytorch.org/whl/cpu/torch-1.1.0-cp36-cp36m-win_amd64.whl torchvision==0.3.0  # CPU 版本

9. Pytorch 1.2.0

# conda
conda install pytorch==1.2.0 torchvision==0.4.0 cudatoolkit=10.0  # CUDA 10.0
conda install pytorch==1.2.0 torchvision==0.4.0 cudatoolkit=9.2  # CUDA 9.2
conda install pytorch==1.2.0 torchvision==0.4.0 cpuonly  # CPU 版本
# pip
pip install torch==1.2.0+cu100 torchvision==0.4.0+cu100 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 10.0
pip install torch==1.2.0+cu92 torchvision==0.4.0+cu92 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 9.2
pip install torch==1.2.0+cpu torchvision==0.4.0+cpu -f https://download.pytorch.org/whl/torch_stable.html  # CPU 版本

10. Pytorch 1.4.0

# conda
conda install pytorch==1.4.0 torchvision==0.5.0 cudatoolkit=10.1  # CUDA 10.1
conda install pytorch==1.4.0 torchvision==0.5.0 cudatoolkit=9.2  # CUDA 9.2
conda install pytorch==1.4.0 torchvision==0.5.0 cpuonly  # CPU 版本
# pip
pip install torch==1.4.0+cu101 torchvision==0.5.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 10.1
pip install torch==1.4.0+cu92 torchvision==0.5.0+cu92 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 9.2
pip install torch==1.4.0+cpu torchvision==0.5.0+cpu -f https://download.pytorch.org/whl/torch_stable.html  # CPU 版本

11. Pytorch 1.5.0

# conda
conda install pytorch==1.5.0 torchvision==0.6.0 cudatoolkit=10.2  # CUDA 10.2
conda install pytorch==1.5.0 torchvision==0.6.0 cudatoolkit=10.1  # CUDA 10.1
conda install pytorch==1.5.0 torchvision==0.6.0 cudatoolkit=9.2  # CUDA 9.2
conda install pytorch==1.5.0 torchvision==0.6.0 cpuonly  # CPU 版本
# pip
pip install torch==1.5.0+cu102 torchvision==0.6.0+cu102 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 10.2
pip install torch==1.5.0+cu101 torchvision==0.6.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 10.1
pip install torch==1.5.0+cu92 torchvision==0.6.0+cu92 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 9.2
pip install torch==1.5.0+cpu torchvision==0.6.0+cpu -f https://download.pytorch.org/whl/torch_stable.html  # CPU 版本

12. Pytorch 1.5.1

# conda
conda install pytorch==1.5.1 torchvision==0.6.1 cudatoolkit=10.2  # CUDA 10.2
conda install pytorch==1.5.1 torchvision==0.6.1 cudatoolkit=10.1  # CUDA 10.1
conda install pytorch==1.5.1 torchvision==0.6.1 cudatoolkit=9.2  # CUDA 9.2
conda install pytorch==1.5.1 torchvision==0.6.1 cpuonly  # CPU 版本
# pip
pip install torch==1.5.1+cu102 torchvision==0.6.1+cu102 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 10.2
pip install torch==1.5.1+cu101 torchvision==0.6.1+cu101 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 10.1
pip install torch==1.5.1+cu92 torchvision==0.6.1+cu92 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 9.2
pip install torch==1.5.1+cpu torchvision==0.6.1+cpu -f https://download.pytorch.org/whl/torch_stable.html  # CPU 版本

13. Pytorch 1.6.0

# conda
conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.2  # CUDA 10.2
conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.1  # CUDA 10.1
conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=9.2  # CUDA 9.2
conda install pytorch==1.6.0 torchvision==0.7.0 cpuonly  # CPU 版本
# pip
pip install torch==1.6.0+cu102 torchvision==0.7.0+cu102 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 10.2
pip install torch==1.6.0+cu101 torchvision==0.7.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 10.1
pip install torch==1.6.0+cu92 torchvision==0.7.0+cu92 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 9.2
pip install torch==1.6.0+cpu torchvision==0.7.0+cpu -f https://download.pytorch.org/whl/torch_stable.html  # CPU 版本

14. Pytorch 1.7.0

# conda
conda install pytorch==1.7.0 torchvision==0.8.0 cudatoolkit=11.0  # CUDA 11.0
conda install pytorch==1.7.0 torchvision==0.8.0 cudatoolkit=10.2  # CUDA 10.2
conda install pytorch==1.7.0 torchvision==0.8.0 cudatoolkit=10.1  # CUDA 10.1
conda install pytorch==1.7.0 torchvision==0.8.0 cudatoolkit=9.2  # CUDA 9.2
conda install pytorch==1.7.0 torchvision==0.8.0 cpuonly  # CPU 版本
# pip
pip install torch==1.7.0+cu110 torchvision==0.8.0+cu110 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 11.0
pip install torch==1.7.0+cu102 torchvision==0.8.0+cu102 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 10.2
pip install torch==1.7.0+cu101 torchvision==0.8.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 10.1
pip install torch==1.7.0+cu92 torchvision==0.8.0+cu92 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 9.2
pip install torch==1.7.0+cpu torchvision==0.8.0+cpu -f https://download.pytorch.org/whl/torch_stable.html  # CPU 版本

15. Pytorch 1.7.1

# conda
conda install pytorch==1.7.1 torchvision==0.8.2 cudatoolkit=11.0  # CUDA 11.0
conda install pytorch==1.7.1 torchvision==0.8.2 cudatoolkit=10.2  # CUDA 10.2
conda install pytorch==1.7.1 torchvision==0.8.2 cudatoolkit=10.1  # CUDA 10.1
conda install pytorch==1.7.1 torchvision==0.8.2 cudatoolkit=9.2  # CUDA 9.2
conda install pytorch==1.7.1 torchvision==0.8.2 cpuonly  # CPU 版本
# pip

pip install torch==1.7.1+cu110 torchvision==0.8.2+cu110 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 11.0
pip install torch==1.7.1 torchvision==0.8.2 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 10.2
pip install torch==1.7.1+cu101 torchvision==0.8.2+cu101 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 10.1
pip install torch==1.7.1+cu92 torchvision==0.8.2+cu92 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 9.2
pip install torch==1.7.1+cpu torchvision==0.8.2+cpu -f https://download.pytorch.org/whl/torch_stable.html  # CPU 版本

16. Pytorch 1.8.0

# conda
conda install pytorch==1.8.0 torchvision==0.9.0 cudatoolkit=11.1  # CUDA 11.1
conda install pytorch==1.8.0 torchvision==0.9.0 cudatoolkit=10.2  # CUDA 10.2
conda install pytorch==1.8.0 torchvision==0.9.0 cpuonly  # CPU 版本
# pip
pip install torch==1.8.0+cu111 torchvision==0.9.0+cu111 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 11.1
pip install torch==1.8.0+cu102 torchvision==0.9.0+cu102 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 10.2
pip install torch==1.8.0+cpu torchvision==0.9.0+cpu0 -f https://download.pytorch.org/whl/torch_stable.html  # CPU 版本

17. Pytorch 1.9.0

# conda
conda install pytorch==1.9.0 torchvision==0.10.0 cudatoolkit=11.1  # CUDA 11.1
conda install pytorch==1.9.0 torchvision==0.10.0 cudatoolkit=10.2  # CUDA 10.2
conda install pytorch==1.9.0 torchvision==0.10.0 cpuonly  # CPU 版本
# pip
pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 11.1
pip install torch==1.9.0+cu102 torchvision==0.10.0+cu102 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA 10.2
pip install torch==1.9.0+cpu torchvision==0.10.0+cpu -f https://download.pytorch.org/whl/torch_stable.html  # CPU 版本

18. Test whether the installation is successful

• CPU version test: Continue running python to enter the interactive environment and run them separately import torch. import torchvisionIf no error is reported, the installation is successful.
• GPU version test: Continue running python to enter the interactive environment, run them separately without import torchreporting import torchvisionan error, and run again print(torch.cuda.is_available()). If True is output, the installation is successful.