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
原文地址：https://blog.csdn.net/qq_64671439/article/details/143083185
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