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Error while reading old trained models and dimer descriptors issue #627
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the original command with correct spaces is this:
I thin this should work , if you place the The error you got says that although you asked to look for methane dimers, in which each of the 4 Hs are within 1.5A of the C, it could not find one of the Hs. are you sure your initial geometry file is correct? can you post your initial structure here? |
When I run the original command with corrected spaces (substituted
I get error:
With
I get error One of structures from the dataset I used to fit gap with A2_dimer descriptor:
Probably the dataset has no problems because I can successfuly train on it this model:
|
yes, that is a change, replace "ip_args" with "core_ip_args". a single frame of your training data doesn't help, because ONE of your frames triggered the error you reported, but we don't know which. can you send your entire training set? (or a subset of it which triggers the error about the atom not being found) |
the reason the simple training with the distance_Nb descriptor works is because it is not trying to find methane molecules. |
Dear QUIP developers,
I am going into details of Max Veit's paper https://pubs.acs.org/doi/abs/10.1021/acs.jctc.8b01242 and exploring the archives with the trained models, datasets, and training scripts published at https://www.repository.cam.ac.uk/items/f8cfd6c4-4323-4d29-b05d-177928150a45.
It looks like QUIP commands have changed since the paper publication. Regarding this, I have some questions:
when I am trying to use any trained model, I get error:
SYSTEM ABORT: Potential_read_params_xml: could not initialize potential from xml_label
Can I modify trained models files to use them?
I was trying to modify the training script for 6-D dimer GAP. I excluded
core_param_file
and excluded substitutedgeneral_dimer
descriptor withA2_dimer
keeping other parameters and training set the same, but got error:Seems like it is a problem with monomer cutoff, but when I increased those parameters it did not solve the problem. Unfortunately, I did not find detailed instructions on how to work with dimer descriptors. How can I solve this problem?
Training script I use:
The original training script from paper's supplementary material:
teach_sparseat_file=me-rigid-shortaug3-mp2-avqz-intnonan.xyz core_param_file={../empirical-pots/ljrep_quip_params.xml} core_ip_args={IPLJ} gap={ general_dimercutoff=6.0 cutoff_transition_width=1.0 signature_one={{61 11 1}} signature_two={{6 11 1 1}} monomer_one_cutoff=1.5monomer_two_cutoff=1.5atom_ordercheck=F strict=Fmpifind=T theta_uniform=1.0covariance_type=ARD_SE n_sparse=2000delta=0.02 sparse_method=CUR_COVARIANCE } default_sigma={0.0002 0.0020.0 0.0}sparse_jitter=1e-10 energy_parameter_name=energyforce_parameter_name=forcee0=0.0 gp_file=gp-merig-mp2-gendim-shortaug3.xml do_copy_at_file=F
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