feat: add normalizer configs and statistics to the checkpoint for streamlined inference#217
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feat: add normalizer configs and statistics to the checkpoint for streamlined inference#217Ndles wants to merge 3 commits into
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Add an extension to checkpoint writer to store normalizer configs and statistics. This allows to load a checkpoint in isolation from the dataset and run inference.
Adds
noether.inference.Run, a Hydra-free Python API for loading a trained run interactively. Construct from a run directory; pull the model, dataset, or field normalizers via three independent lazy methods:run.model()- instantiate + load checkpoint weights. Config + checkpoint only.run.normalizers()- build field normalizers from the dataset class's STATS_FILE without instantiating the dataset itself. Useful for applying a trained model to data that isn't packaged as a noether Dataset.run.dataset()- instantiate the dataset (the only path that needs the original data files).Adds an interactive notebook showcasing how to load a checkpoint directly, as well as new
noether.inference.Run