Affinity checkpoint comparison

Pass --save-all-checkpoints to mhcflurry class1-train-pan-allele-models to retain both terminal and minimum-validation-loss weights from each training trajectory. restore_best_weights still selects the primary prediction state. Checkpoint NPZ files are stored under checkpoints/terminal/ and checkpoints/best/, with relative paths in the training manifest.

Materialize an alternative state as a separate predictor:

mhcflurry train materialize-affinity-checkpoint \
    --models-dir models.unselected.combined \
    --policy best \
    --out-models-dir models.unselected.best

The command records source hashes and selection provenance and removes stale calibration and optimization metadata. A missing requested checkpoint is an error. Repeat ensemble selection and calibration before treating the new predictor as a replacement for the original; compare both on identical rows.

Training save/load, multiprocessing and continuation preserve checkpoint sidecars. Release inference exports omit them and load only the selected primary state. Keep the original training directory to revisit checkpoint selection. The 2.3.0 affinity weights use terminal checkpoints; retaining best-loss states does not imply that they improved the released ensemble.