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name: training-configs description: "Construct and troubleshoot SchNetPack spktrain and spkpredict Hydra commands, training recipes, logging, callbacks, checkpoints, and prediction outputs." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

SchNetPack Training Configs

Use this sub-skill when the task is to build, explain, or debug SchNetPack spktrain or spkpredict commands and Hydra configuration overrides.

Route Here For

• spktrain commands for QM9, MD17, rMD17, or custom ASE database training.
• Hydra override syntax, config groups, slash-vs-dot semantics, and adding optional groups or new keys.
• Trainer, logger, callback, optimizer, scheduler, run directory, checkpoint, and resume settings.
• spkpredict commands for a trained model directory, ASE DB input, cutoff, prediction output, and checkpoint selection.
• Safe command validation using --help, config printing, bounded fast_dev_run, or tiny split limits.

Route Elsewhere

• Dataset creation, ASE DB schemas, units, splits, and property preparation: ../data-pipelines/SKILL.md.
• Model architecture internals, representation choices, output modules, and custom modules: ../models-atomistic/SKILL.md.
• ASE calculators, deployment, MD, uncertainty, or LAMMPS use after a model is trained: ../interfaces-md/SKILL.md.

Fast Decision Guide

• For command-line syntax and config composition, start with Hydra CLI.
• For QM9, MD17/rMD17, custom-data, trainer, logger, callback, and checkpoint recipes, use Training recipes.
• For inference over an ASE database from a trained run, use Prediction.
• For common CLI/config failures, use Troubleshooting.

Safety Defaults

• Do not run long training, dataset downloads, GPU jobs, or native tests as a smoke check.
• Prefer spktrain ... --help or spkpredict --help to inspect resolved configs without training.
• For bounded execution only when explicitly requested, add trainer.fast_dev_run=true, tiny data.num_train/data.num_val, and explicit local run.data_dir, run.path, and run.id values.