coleygroup / molpal

active learning for accelerated high-throughput virtual screening
MIT License
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[BUG]: Not compatible with the latest Ray/Pytorch-Lightning versions #47

Open sunhwan opened 1 year ago

sunhwan commented 1 year ago

Describe the bug If the package is installed by following the instruction on README.md, the main CLI script fails to run due to incompatibility to ray and pytorch-lightning version as of Apr. 2023. I suspect there has been a major version change in both Ray and Pytorch-lightning.

I fixed this by pinning pytorch-lightning and ray narrowly in the environment.yml file.

name: molpal

channels:
  - nvidia
  - pytorch
  - conda-forge
  - defaults

dependencies:
  - python=3.9
  - pytorch=1.13.1
  - pytorch-cuda=11.7
  - pip
  - pip:
    - configargparse
    - h5py
    - numpy
    - ray >= 1.11,<2.0
    - ray[tune]
    - rdkit
    - pytorch-lightning == 1.5.10
    - scikit-learn
    - tensorflow
    - tensorflow-addons
    - tqdm
DavidSchallerNuvisan commented 5 months ago

Thanks so much for the updated environment.

We additionally identified a GPU memory issue with the required ray version (29624).

With every iteration the GPU memory increases when using MPNN as model. One can prevent this with @ray.remote(max_calls=1) at L92).