Updating calculator weights from checkpoints

[LarsSchaaf]

If you want to see performance changes throughout epochs, you can load a single model and then update the weights from former checkpoints.

To do:

• create test: where you compare the output from loading two separate models or updating based on their corresponding checkpoints.

[RokasEl]

What's the use case of doing:

calc.update_weights_from_checkpoint(LOAD_PATH)

compared to:

calc = MACECalculator(model_paths=LOAD_PATH)

?

If there is a genuine case, I think it would be better to modularize the __init__ of the calculator to use a load_weights function and use that for both initializing the calculator, and updating the weights inplace.

[LarsSchaaf]

The difference is that one loads .model s and this one can load checkpoints .pt files, ie just state_dicts

        Example:
            >>> atoms = read('path/to/atoms_file.xyz')
            >>> atoms.calc = MACECalculator('path/to/mace_model.model')
            >>> print("Energy before:", atoms.get_potential_energy())
            >>> atoms.calc.update_weights_from_checkpoint('path/to/checkpoint.pt')
            >>> print("Energy after:", atoms.get_potential_energy())

[LarsSchaaf]

Note:

• state_dict changes when using cuEquivariance, so can only update models with checkpoints with same cuequivariance setting
• compiled models also don't work atm