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@AlexDuvalinho AlexDuvalinho commented Apr 18, 2024

In this PR, we continue the work done on depfaenet and deup-depfaenet, integrating it into the active learning pipeline.

Aims:
(1) have a trained DepFAENet model fine-tuned on selected adsorbates, to predict the adsorption energies for catalyst-adsorbate pairs generated by GFlowNet
(2) have a deup-dataset which the intermediate representations of the above model, to train a Gaussian Process that measures uncertainty
(3) have a (v0) deup-depfaenet model that predicts uncertainty of the core DepFAENet model

Main changes of this PR are:

  • Fix cluster issues ✅
  • Update all associated configs and checkpoints relative to deup / depfaenet ✅
  • Train a DepFAENet model, without concatenation, with tag0 and with dropout ✅
  • Obtain a deup dataset with above model ✅
  • Train deup-depfaenet model that predicts the uncertainty ✅
  • Ensure that it can be integrated to the active learning repo ✅
  • Add a density estimator (q) for deup-faenet
  • Add GP or DKL (replacing mc dropout ?)

Information on best checkpoints are included in https://www.notion.so/Coding-Probabilistic-Surrogate-Model-328aece28af948f686fa91a2623d8635?pvs=4


From the uncertainty-depfaenet branch:

  • Import DepFAENet from disconnected_gnns Alvaro ✅
  • Adapt DepFAENet (dropout, etc.) and pre-train it on full data ✅
  • Re-train DepFAENet on selected adsorbates ✅
  • Create deup-dataset using MC dropout depfaenet ✅
  • Create Deup-DepFAENet ✅
  • Train deup-depfaenet on deup-dataset ✅
  • Active learning script to use deup-dataset ✅
  • Fix imports issue ✅
  • Allow FAENet Wrapper to keep track of hidden representations for active-learning part ✅

CAREFUL: only store graph-level rep in deup-dataset from now on. Need to change it if we want to perform MC dropout again (related to deup-faenet)

@AlexDuvalinho AlexDuvalinho marked this pull request as ready for review June 23, 2024 19:35
@AlexDuvalinho AlexDuvalinho requested a review from vict0rsch June 23, 2024 19:36
conda activate {env}
fi
{wandb_offline}
srun --gpus-per-task=1 --output={output} {python_command}
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Anyone knows why this disappeared?

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5 participants