| Docker files for downstream evaluation, CUDA 11.2.. | |
| GCP CUDA is 11.0, but we use CUDA 11.2 to get latest TF | |
| This includes torch 1.9 and tf 2.6.0. We use 1.19.2 numpy for tf 2.6.0 | |
| We use a simple hack to get tf 2.4.2 to play nice with CUDA 11.2: | |
| (https://medium.com/mlearning-ai/tensorflow-2-4-with-cuda-11-2-gpu-training-fix-87f205215419) | |
| ln -s /usr/local/cuda-11.2/targets/x86_64-linux/lib/libcusolver.so.11 \ | |
| /usr/local/cuda-11.2/targets/x86_64-linux/lib/libcusolver.so.10 | |
| LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/cuda-11.2/targets/x86_64-linux/lib" | |
| If you want to rebuild these dockers from the repository root: | |
| ./docker/build.sh to create and push. | |