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add atom energy bias to type embedding energy #1592

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merged 3 commits into from
Mar 25, 2022

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@njzjz njzjz commented Mar 24, 2022

Fix #684, where systems have different atom_numb. After this fix, RMSE of energy should be quickly decreased in the very beginning.

Fix deepmodeling#684, where systems have different `atom_numb`. After this fix, RMSE should be quickly decreased in the very beginning.
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codecov-commenter commented Mar 24, 2022

Codecov Report

Merging #1592 (c91bad6) into devel (c49533e) will decrease coverage by 0.00%.
The diff coverage is 80.00%.

@@            Coverage Diff             @@
##            devel    #1592      +/-   ##
==========================================
- Coverage   76.75%   76.75%   -0.01%     
==========================================
  Files          93       93              
  Lines        7790     7794       +4     
==========================================
+ Hits         5979     5982       +3     
- Misses       1811     1812       +1     
Impacted Files Coverage Δ
deepmd/fit/ener.py 92.24% <80.00%> (-0.31%) ⬇️

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@wanghan-iapcm wanghan-iapcm requested a review from iProzd March 25, 2022 01:32
@wanghan-iapcm wanghan-iapcm merged commit c17873d into deepmodeling:devel Mar 25, 2022
@njzjz njzjz deleted the type-embd-bias branch March 25, 2022 04:57
njzjz added a commit to njzjz/deepmd-kit that referenced this pull request Mar 28, 2022
Following deepmodeling#1592, I noticed that constants cannot be recovered when restart training.
amcadmus pushed a commit that referenced this pull request Mar 29, 2022
* convert constants (which may change) to variables

Following #1592, I noticed that constants cannot be recovered when restart training.

* add dtype to variables

* cast int32

* bugfix

* init atom_ener
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[BUG] Loss of energy and force failed to decline with type-embedding
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