conda create -n tf2.4 python=3.8
conda activate tf2.4
conda install cudatoolkit=11.0
pip3 install tensorflow==2.4
download cudnn8.0.5 for cuda11.0
tar -xzvf cudnn-11.0-linux-x64-v8.0.4.*.tgz
cp cuda/lib64/* ~/.conda/envs/tf2.4/lib/
conda create -n tf1.12 python=3.6
conda activate tf1.12
conda install cudatoolkit=9.0
pip3 install tensorflow-gpu==1.12
https://developer.nvidia.com/rdp/cudnn-archive Download cuDNN v7.0.5 (Dec 5, 2017), for CUDA 9.0
tar -zxvf cudnn-9.0-linux-x64-v7.tgz
cp cuda/lib64/* ~/.conda/envs/tf1.12/lib/
cp cuda/include/* ~/.conda/envs/tf1.12/include/
测试 tf.test.is_gpu_available()