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1.1.2

mir-group/flare

版本发布时间: 2022-08-10 09:58:08

mir-group/flare最新发布版本:1.3.3(2022-12-20 05:00:27)

What's Changed

Full Changelog: https://github.com/mir-group/flare/compare/1.0.0...1.1.2

Offline training

  1. Compute and print mean absolute error at each step (frame), not only at steps where a frame is added to SGP.
  2. Add data distribution statistics at the end of the training, summarizing how many frames are picked up from each dataset

Bug fixing

  1. Fix a lammps calculator bug of prism cell
  2. Fix the on-the-fly MAE calculation and logging when any of energy/forces/stress is excluded for training.
  3. Allow DFT calculator to be saved as json in the checkpoint, in case some can be non-pickable
  4. Add atom_indices into the dict of dumped SGP

Other features and tutorials

  1. Add timer for each part in OTF training log
  2. Add mapped uncertainty to the build_map method in SGP_Calculator
  3. Add python interface to support customized descriptors. Check the tutorial here
  4. Add a tutorial for computing thermal conductivity from flare + Phoebe. Check the tutorial here

Backward compatibility notices

  1. In the yaml file for offline training, the parameters in FakeDFT can be removed since they are redundant
dft_calc:
     name: FakeDFT
     kwargs: 
         filename: fake_dft.xyz
         format: extxyz
         index: ":"
         io_kwargs: {}

change to

dft_calc:
     name: FakeDFT
     kwargs: {} 
     params: {}
  1. In the yaml file for offline training, the filename changes to filenames, allowing user to list multiple files as datasets.
 otf: 
     md_engine: Fake
     md_kwargs: 
         filename: fake_dft.xyz

change to

 otf: 
     md_engine: Fake
     md_kwargs: 
         filenames: [fake_dft_1.xyz, fake_dft_2.xyz]

Then at the end of the training, the log file will report how many frames are selected to add to SGP from fake_dft_1.xyz, fake_dft_2.xyz, respectively.

  1. In the yaml file for online or offline training, set up a lower bound of DFT calls for training hyperparameters
otf:
    freeze_hyps: 10

change to

otf:
    train_hyps: [1, 10]          # [a, b] represents training hyps when the number of DFT frames SGP has collected is between a and b

Compatible LAMMPS version

Stable release 29 September 2021

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