深度学习之安装pytorch（GPU版本，cuda为11）————conda安装+镜像

建立虚拟环境：

conda create -n new_torch(自己取一个) python==3.7

填上镜像信息

conda config --add channels http://mirror.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/
conda config --add channels http://mirror.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
conda config --add channels http://mirror.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
conda config --append channels http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/
conda config --set show_channel_urls yes
conda config --set ssl_verify false

conda安装torch

conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=11.1

其他相关依赖包

pip install opencv-python  pillow matplotlib scipy pandas scikit-learn tqdm scikit-image imutils PyYAML  seaborn easydict  ipython imageio  jieba -i https://pypi.tuna.tsinghua.edu.cn/simple/
pip install numpy==1.21 -i https://pypi.tuna.tsinghua.edu.cn/simple/

测试

import torch

if __name__ == '__main__':
    print("Support CUDA ?: ", torch.cuda.is_available())
    x = torch.Tensor([1.0])
    xx = x.cuda()
    print(xx)

    y = torch.randn(2, 3)
    yy = y.cuda()
    print(yy)

    zz = xx + yy
    print(zz)

    # CUDNN TEST
    from torch.backends import cudnn

    print("Support cudnn ?: ", cudnn.is_acceptable(xx))