| # Download folding resources | |
| wget -N --no-check-certificate -P openfold/resources \ | |
| https://git.scicore.unibas.ch/schwede/openstructure/-/raw/7102c63615b64735c4941278d92b554ec94415f8/modules/mol/alg/src/stereo_chemical_props.txt | |
| # Certain tests need access to this file | |
| mkdir -p tests/test_data/alphafold/common | |
| ln -rs openfold/resources/stereo_chemical_props.txt tests/test_data/alphafold/common | |
| # Decompress test data | |
| gunzip -c tests/test_data/sample_feats.pickle.gz > tests/test_data/sample_feats.pickle | |
| python setup.py install | |
| echo "Download CUTLASS, required for Deepspeed Evoformer attention kernel" | |
| git clone https://github.com/NVIDIA/cutlass --branch v3.6.0 --depth 1 | |
| conda env config vars set CUTLASS_PATH=$PWD/cutlass | |
| # This setting is used to fix a worker assignment issue during data loading | |
| conda env config vars set KMP_AFFINITY=none | |
| export LIBRARY_PATH=$CONDA_PREFIX/lib:$LIBRARY_PATH | |
| export LD_LIBRARY_PATH=$CONDA_PREFIX/lib:$LD_LIBRARY_PATH | |