curr.mtp
train.cfg
None
mlp train curr.mtp train.cfg --max-iter=500 --trained-opt-name=curr.mtp --curr-pot-name=curr.mtp --stress-weight=5e-4 --force-weight=5e-3
Trains the potential in curr.mtp
on the data in train.cfg
. [GLWH Nov 26 2020] In other words, this is the fit. This is the part a potential is fitted to the energies, forces, and stresses in a group of vasp calculations.
curr.mtp
train.cfg
train.cfg
temp.cfg
temp.cfg
state.als
mlp calc-grade curr.mtp train.cfg train.cfg temp.cfg --nbh-weight=0.0 --energy-weight=1.0
Calculates the MV Grade of train.cfg
and sets up the state.als
file. [GLWH Nov 26 2020] The MV grade isn't needed. But the als
file stores the active learning set.
mlip.ini
curr.mtp
catalog.cfg
relaxed.cfg_*
unrelaxed.cfg_*
selected.cfg_*
Note: The _*
signifies that there will probably be multiple files, depending on the number of processes you are running the command with.
[GLWH Nov 26 2020]
For me the output files are B-preselected.cfg_#. And watch out! If you run this command twice in a row, without deleting B-preselected.cfg
it appends to the file. Gotcha!
mlp relax mlip.ini --force-tolerance=1e-3 --stress-tolerace=1e-2 --max-step=0.03 --cfg-filename=catalog.cfg --save-relaxed=relaxed.cfg --save-unrelaxed=unrelaxed.cfg
This is sort of the heart of the MTP algorithm. It attempts to relax the structures in catalog.cfg
to an equilibrium state.
If it fails to do so, within a certain tolerance of estimated error, the structures that break this tolerance are collected. [GLWH Nov 26 2020] Some (or all of these preselected structures will be added to the training set. This selection is done in the next step: select-add.
curr.mtp
train.cfg
selected.cfg
state.als
Note: selected.cfg
is a concatenation of all selected.cfg_*
from the previous step
diff.cfg
active_set.cfg
mlp select-add curr.mtp train.cfg selected.cfg diff.cfg --select-threshold=3.0 --nbh-weight=0.0 --energy-weight=1.0 --als-filename=state.als --selected-filename=active_set.cfg
This step selects files from selected.cfg
to run in VASP. These will then be added to the training set and the process starts again.
"This often happens when there are too few configurations in the database - there is a condition that the error on each iteration should decrease, but when there are too little configurations, severe overfitting occurs and the iterative algorithm cannot decrease the error due to round-off errors. Can be safely ignored and forgotten about when you expand the training database sufficiently large. Not easy to detect automatically, though." - Alexander Shapeev
This error occurs when you have an input in an mlp
command but the file it refers to is not there. For example, if you see MLIP: ERROR: Error reading .mtp file
, then your mtp file is missing.
It is especially important to look out for AutoGR errors because if AutoGR fails, VASP will automatically generate KPOINTS for you, and most likely not at the same KPOINT density you want.
This one hopefully will be fixed soon in the AutoGR code.
This has an unknown cause, but could be caused by ... (maybe add some more info here that I don't know).