FAQ

Frequently asked questions or encountered issues when running OpenFold.

Setup

  • When running unit tests (e.g. ./scripts/run_unit_tests.sh), I see an error such as

    ImportError: version GLIBCXX_3.4.30 not found

    Solution: Make sure that the $LD_LIBRARY_PATH environment has been set to include the conda path, e.g. export $LD_LIBRARY_PATH=$CONDA_PREFIX/lib:$LD_LIBRARY_PATH

  • I see a CUDA mismatch error, eg.

The detected CUDA version (11.8) mismatches the version that was used to compile
PyTorch (12.1). Please make sure to use the same CUDA versions.

Solution: Ensure that your system’s CUDA driver and toolkit match your intended OpenFold installation (CUDA 11 by default). You can check the CUDA driver version with a command such as nvidia-smi

  • I get some error involving fatal error: cuda_runtime.h: No such file or directory and or ninja: build stopped: subcommand failed..

Solution: Something went wrong with setting up some of the custom kernels. Try running install_third_party_dependencies.sh again or try python3 setup.py install from inside the OpenFold folder. Make sure to prepend the conda environment as described above before running this.

Training

  • My model training is hanging on the data loading step:

    Solution: While each system is different, a few general suggestions: - Check your $KMP_AFFINITY environment setting and see if it is suitable for your system. - Adjust the number of data workers used to prepare data with the --num_workers setting. Increasing the number could help with dataset processing speed. However, to many workers could cause an OOM issue.

  • When I reload my pretrained model weights or checkpoints, I get RuntimeError: Error(s) in loading state_dict for OpenFoldWrapper: Unexpected key(s) in state_dict:

    Solution: This suggests that your checkpoint / model weights are in OpenFold v1 format with outdated model layer names. Convert your weights/checkpoints following this guide.