Works through docs/v0.3.0-followups.md item by item, closing the gap
between the design doc and the shipped v0.3.0-stage2-autoregressive code:
1. validate.py: 7-tuple batch unpacking, sample_stage1/sample_stage2
dispatch, stage-2 particle-type-class marginal.
2. Stage-prefixed --stage1-*/--stage2-* CLI flags for train/new-run.
3. Thread stage2_model.k_max through loader/transforms/dataset/pipeline/
train instead of the hardcoded K_MAX constant.
4. Mixed conditioning.particle.type / conditioning.material.type support
end-to-end (data pipeline + dwarf warm-cache).
5. conditioning.share_stages = true: one shared ConditionEncoder instance
across both stages.
6. stage2_model.generator = "ddpm" formally deferred into design doc §11.2
(was silently unimplemented).
7. giant predict/rollout: implement conditioning.*.type = "onehot" via the
checkpoint's saved pdg_topn_map/mat_topn_map.
8. network.py's checkpoint-path model_config migration now fails loudly on
non-zero legacy expert_hidden_dim/expert_n_blocks, matching config.py's
TOML-load path (§4.2).
9. validate_config now rejects stage2_model.n_sec.mode = "truth" for a
rollout-capable checkpoint (§9).
Also cleared all pre-existing `ty check` noise (44 -> 0 diagnostics),
mostly a test-helper dict-unpack pattern that made every unrelated
constructor keyword look like a type error.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
- run_create_manifest gains --force; it previously overwrote an
existing manifest (including holdout.manifest, which
check_holdout_overlap exists specifically to protect) with no
warning or backup on a second run.
- _git_user_name only caught OSError, not subprocess.TimeoutExpired (a
SubprocessError, not an OSError) — a slow/loaded shared portal
machine could crash `dwarf bump-gen`/`bump-schema` instead of
degrading to by=None as intended.
- `dwarf convert --jobs`/`make-root --jobs` now warn (never block) when
the requested count exceeds ~1/4 of the machine's CPUs, matching the
same shared-machine etiquette check added to giant train in the
previous commit.
- The Conditioning enum was independently redefined in both
giant/cli.py and scripts/dwarf.py; moved to a single
giant.config.Conditioning both now import, removing the drift risk
of a third conditioning mode being added to one but not the other.
Each fix has a regression test.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Lets the vocab maps, event-id split index, and normalizer stats be
warmed once for a dataset (right after `dwarf convert`, or before a
`dwarf hparam-scan` sweep) without needing to also start training.
Extracts the setup-stage logic out of giant/pipeline.py:run_train_job
into a standalone run_setup_stage() (returning a SetupStageResult),
reused by both run_train_job and the new dwarf command's
scripts/warm_setup_cache.py — a behavior-preserving refactor, covered
by the existing test_pipeline.py suite.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Replace the five separately-hyphenated uv entry points (steps-to-parquet,
steps-to-parquet-parallel, migrate-geant-steps, bump-dataset-version,
create-root-files) plus the unregistered hparam_scan.py with one `dwarf`
command exposing convert/migrate/bump-gen/bump-schema/status/
update-manifest/create-manifest/make-root/hparam-scan as subcommands.
Each scripts/*.py module now only holds argparse-free business logic;
scripts/dwarf.py wires it up with Typer, matching giant/cli.py's style.
`dwarf convert` merges the old serial/parallel conversion scripts behind
a --jobs flag (default 1: sequential with plain -o; >1: dataset-layout
fan-out via subprocess).
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
lars