官方的tensorflow1.1x只支持cuda10.0和cudnn7，如何在更高的版本cuda和cudnn8使用tensorflow1.1x呢？最简单的方法是使用nvidia修改维护的tensorflow NGC镜像：
GitHub - NVIDIA/tensorflow: An Open Source Machine Learning Framework for Everyone
TensorFlow User Guide :: NVIDIA Deep Learning Frameworks Documentation
RTX3080+Ubuntu18.04+cuda11.1+cudnn8.0.4+TensorFlow1.15.4+PyTorch1.7.0环境配置_wu496963386的博客-CSDN博客
版本关系
TensorFlow Release Notes :: NVIDIA Deep Learning Frameworks Documentation
直接使用镜像
docker pull nvcr.io/nvidia/tensorflow:21.06-tf1-py3 # example of use 21.06-tf1-py3
rebuild tensorflow
TensorFlow User Guide :: NVIDIA Deep Learning Frameworks Documentation
FROM nvcr.io/nvidia/tensorflow:21.08
# Bring in changes from outside container to /tmp
# (assumes my-tensorflow-modifications.patch is in same directory as Dockerfile)
COPY my-tensorflow-modifications.patch /tmp
# Change working directory to TensorFlow source path
WORKDIR /opt/tensorflow
# Apply modifications
RUN cd tensorflow-source \
&& patch -p1 < /tmp/my-tensorflow-modifications.patch
# Rebuild TensorFlow
RUN ./nvbuild.sh
# Reset working directory
WORKDIR /workspace也就是在镜像里面包含了重新编译tf的代码和流程。