- giant/sample.py: fix every sampler's call convention against
Stage1Model/Stage2OneShot's actual forward signatures (was still
calling model(x, t, cond_cont, cond_cat) positionally); add
sample_secondaries_ar (free-running AR loop, unsnapped history feature)
and sample_stage1/sample_stage2/resolve_n_sec dispatch helpers that read
each stage's generator_kind/decoder off the model instance itself.
- giant/particles.py: decode_topn_class (argmax + other_policy) and
decode_embedding_nearest (L1-snap + distance) turn a secondary's
"onehot"/"embedding" type prediction into a concrete PDG.
- giant/rollout.py: decode_secondary_identity routes all three
particle_type.target values to real mass/charge; per-stage generator
dispatch (drops the single shared `mode` string, adds ddpm support);
L1DistCollector accumulates the §11.3 embedding-distance diagnostic.
- giant/cli.py: drop the onehot/embedding-target rejection gate (narrowed
to the still-unimplemented conditioning.particle/material.type=onehot
axis); fix the dead model_cfg.get("mode") bug in predict/rollout.
- giant/analysis/: new type_embedding_l1_distance PlotSpec, wired through
the rollout YAML sidecar (no live-model call needed, unlike
router_gating -- the histogram is already pre-aggregated at rollout
time).
- Un-xfail every test that was blocked on this step (test_rollout.py,
test_flow.py, test_wgan.py, test_phase2.py, test_router.py,
test_validate.py); add test_sample.py, test_type_embedding_distance.py.
Known follow-up: giant/validate.py still unpacks the training val-batch
as a stale 6-tuple and doesn't use the new per-stage dispatch, so
marginal validation during training degrades gracefully with a warning
rather than working -- not in this step's scope.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Decomposes the ten permutation classes in giant/model/network.py into
the reusable parts from docs/v0.3.0-design.md §5: ConditionEncoder (now
independently configurable per particle/material axis), ContextAdapter,
Trunk/MonolithicTrunk/RoutedTrunk/ExpertTrunk, and the stage classes
Stage1Model/Stage2OneShot/CriticModel (Stage2Autoregressive stubbed,
raises NotImplementedError until step 4/5). build_models/build_critics
now return a dict keyed by stage and accept the new nested config shape,
with routed WGAN reachable for the first time (the old --mode wgan
--router rejection is gone) and stage2_model.router.tie_to_stage1
sharing a literal Router instance.
A v0.2 checkpoint's flat model_config auto-migrates via
_migrate_legacy_model_config + migrate_legacy_state_dict, preserving the
n_sec_head's attachment to Stage1Model (legacy_owner="stage1", design
doc §4.1). tests/test_migration_v02_v03.py proves this bit-identical
against a frozen v0.2 snapshot (tests/legacy/network_v02_snapshot.py)
for both flow and wgan, both conditioning modes.
scripts/check_migration_v02_v03.py is the real-checkpoint counterpart
for a portal machine with /ceph access.
giant/model/schedule.py's flow-matching/DDPM loss helpers are updated
to the new model-call convention (t as a keyword). giant/sample.py,
giant/rollout.py, and giant/validate.py are not yet updated (deferred
to design doc step 6) — their exercising tests are marked xfail with
that reasoning rather than silently broken.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
- make_seed_frontier only resolves particle mass/charge in "physical"
mode, so "embedding"-mode rollouts no longer crash on a seed PDG code
giant.particles can't resolve (the TERM_UNKNOWN_PDG gate now handles it).
- nearest_known_pdg skips unresolvable candidate PDG codes instead of
raising and killing the whole rollout/predict run.
- predict/rollout fail with a clear message when a checkpoint predates
the sec_phys normalizer, instead of a bare KeyError.
- validate_marginals' phys_kl degrades to NaN (matching the
energy_fraction_kl pattern) instead of crashing when a validated batch
has zero secondaries on either side.
- Correct CLAUDE.md's stale claim that the materials table is unfilled.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
lars