Some confusion about training other properties on custom data

[ldhkc]

Dear Dr. Niklas Gebauer,

I've recently been using your project to train a custom dataset and trying to apply it on new attributes. During this process, I encountered some doubts about property training, especially how to handle custom properties that are not included in schnetpack's properties.py file.

My understanding is that the data training part of the project mainly relies on the atomic coordinates and atomic number information of the molecules. schnetpack seems to be trained mainly on its built-in properties (such as force, energy, energy gap, etc.). Therefore, I would like to ask a few questions:

1. Processing of custom attributes: If the data I want to train contains custom attributes that are not within the scope defined by schnetpack, do I need to modify some .py files in the schnetpack package (for example, define custom data like qm9.py kind)? Or is it enough to just convert the custom dataset into ASE database format and add all the necessary information (atomic coordinates, atomic numbers and custom properties)?
2. Adjustment of configuration files: Under the guidance of your tutorial, I understand that I do not need to modify any files inside schnetpack. My steps are to convert the custom data set into ASE database format and add all the atomic coordinates, atomic numbers, and custom attributes into it. After that I should use the template config file you provided and fill in those sections marked ??? based on the comments. Is this understanding correct?
3. Attribute prediction process: For deep learning models, before predicting custom attributes, the model needs to correctly identify these attributes. Can you elaborate on how the model outputs its predictions? Specifically, what is the output process of attribute predicted values?
4. Verify the accuracy of predictions: Can I generate molecules from a model trained on a custom data set, and then select a subset of them to verify the accuracy of the predictions through quantum chemical calculations? I'm a bit confused by this attribute prediction process and would love your guidance. Thank you very much for taking the time out of your busy schedule to read my question and hope to get your reply.

good luck,

[ldhkc]