- log_transform / _validate_unit_pre_dir now raise on non-finite input
instead of letting a NaN row silently poison the persisted normalizer
cache (norm < 1e-6 was always False for NaN, so the existing guard
never caught it).
- encode_secondaries warns when a row's secondary energies cumulatively
exceed e_sec, instead of silently saturating the overflowing slot's
stick-breaking logit via the _EPS floor.
- EVENT_ID_FILE_STRIDE overflow now raises instead of silently colliding
two files' event ids together (reintroducing train/val leakage).
- make_event_split(val_fraction=0.0) now actually holds out nothing,
instead of always forcing at least 1 validation event.
- setup_cache.save() is now serialized with a flock, since two
concurrent writers (a real scenario on this repo's shared
portal/condor machines) could otherwise race and silently drop one
writer's freshly-computed cache section.
- Documented (no behavior change) the pre_dir ≈ -ẑ antipodal rotation
singularity in _rodrigues_axis, which is real but inherent to any
single-valued local-frame convention.
Each fix has a regression test.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
NormalizerEntry.energy_reservoir_sample kept 100k raw energy values purely
to seed EnergyRouter centers via np.quantile at load time, which alone
accounted for most of the setup cache sidecar's ~2MB size (float32 values
round-tripped through Python floats serialize at full double precision).
Only a handful of quantile levels are ever read back, so collapse the
sample to a fixed 1001-point quantile grid at save time and interpolate
arbitrary levels from it at use time instead — about 100x smaller with
negligible (<0.001) error on the levels that matter. Bumps the cache
format version since old sidecars have no such grid to fall back on.
Each input parquet file is one Geant4 job (scripts/steps_to_parquet.py),
and a job's event_id numbering always restarts from 0 — so loading
multiple files together (a directory or .manifest) let same-numbered
events from different files collapse into one during the event index
scan and train/val split, corrupting both. Every per-file event_id now
gets offset by file index * EVENT_ID_FILE_STRIDE (giant/data/loader.py),
threaded through the setup-cache event index, the streaming dataset,
and predict/rollout seeding. Bumps the setup-cache format version so
stale sidecars computed pre-fix are invalidated.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Building the pdg/material vocab maps, the process map, and fitting the
Stage-1/Stage-2 normalizers all require scanning the training dataset
before a single epoch runs, which is wasted work whenever the same
data path is reused across runs (hyperparameter sweeps via `dwarf
hparam-scan`, repeated manual training attempts, ...). Persist those
setup-stage outputs to a JSON sidecar next to the input data
(giant/data/setup_cache.py), validated by a file fingerprint plus
fixed dimension constants and a manually-bumped format version before
reuse, with a soft warning (not a hard invalidation) on a git-hash
mismatch alone.
Also derives n_train_steps instantly from cached per-event row counts
instead of accumulating it during the normalizer scan, and always
collects the energy-router reservoir sample while the cache is being
populated (not only when the current run's router is energy-typed) so
a later run enabling --router-type energy never needs to rescan just
to seed expert centers.
New --cache-setup/--no-cache-setup (default on) and
--rebuild-setup-cache/--no-rebuild-setup-cache flags on `giant train`.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
lars