安装gpu版本的tensorflow-2.11

参考：
https://medium.com/nerd-for-tech/installing-tensorflow-with-gpu-acceleration-on-linux-f3f55dd15a9

1.在环境中安装cuda和cudnn

conda install -c conda-forge cudatoolkit=11.2.2 cudnn=8.1.0

2. 环境变量

conda activate tf

# Create the directories to place our activation and deacivation scripts in
mkdir -p $CONDA_PREFIX/etc/conda/activate.d
mkdir -p $CONDA_PREFIX/etc/conda/deactivate.d

# Add commands to the scripts
printf 'export OLD_LD_LIBRARY_PATH=${LD_LIBRARY_PATH}\nexport LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:${CONDA_PREFIX}/lib/\n' > $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh
printf 'export LD_LIBRARY_PATH=${OLD_LD_LIBRARY_PATH}\nunset OLD_LD_LIBRARY_PATH\n' > $CONDA_PREFIX/etc/conda/deactivate.d/env_vars.sh

# Run the script once
source $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh

3. 安装tensorflow

pip install --upgrade pip
pip install tensorflow==2.11

4. 测试能否使用GPU

python -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"

显示tensorflow和numpy版本冲突

下面降低numpy版本即可

再次测试，成功