The absence of "cell" and "pbc" in the batch dictionary affects LMP execution

[jed-hacker]

In extensions.py, the Python checks (e.g., aligning devices via pbc_tensor = data["pbc"].to(device=data["cell"].device)) and the explicit initialization of pbc and cell are only necessary when training the model in pure Python workflows. However, when invoking MACE through LAMMPS (e.g., via pair_style mliap), the values of cell and pbc are automatically derived from the LAMMPS input script (e.g., *.lammps file) and passed correctly through the MLIAP interface. In this LAMMPS-driven execution path, there is no need to check for or manually initialize cell and pbc in the batch dictionary. We kindly suggest the authors consider implementing separate code paths for LAMMPS-based inference and native Python-based training to handle these cases appropriately.

[Xiaoyu-Wang-Stone]

I'd like to clarify two aspects about this issue:

1. Python Training/Inference Workflow
   In pure Python workflows (e.g., training or MACECalculator), the pbc and cell values come from the AtomicData objects created from ASE Atoms configurations.
   The device alignment check in extensions.py line is necessary to compute the LR energy with Ewald summation:
   pbc_tensor = data["pbc"].to(device=data["cell"].device)

2. MACELES in LAMMPS
   The current LAMMPS_MLIAP_MACE implementation doesn't extract pbc and cell from LAMMPS. This causes MACELES to crash when it tries to access these required keys.

I'm checking how to pass cell info to LES in LAMMPS MLIAP at my end at this moment.
Would explicitly extracting box from LAMMPS be a reasonable approach, or is there a better way?