Make config dataclasses the single source of truth for DEFAULT_CONFIG
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DEFAULT_CONFIG and build_models/build_critics/StageSpec.from_config's
inline .get(key, default) fallbacks had already drifted: two keys
(stage2_model.decoder, stage2_model.particle_type.target) resolved
differently depending on whether a config dict came from
merge_cli_overrides (fully populated, correct) or was hand-built and
partial (fell back to stale v0.2-shaped literals). Introduce frozen
dataclasses (GiantConfig and its nested blocks) in giant/config.py as
the actual single declaration of every default; DEFAULT_CONFIG is now
generated from them instead of hand-maintained, and build_models,
build_critics, and StageSpec.from_config consume the dataclasses
instead of duplicating literal fallbacks, so this class of drift can't
recur. Router/n_sec sub-blocks keep an `extra` catch-all for their
genuinely dynamic keys (composed-router axes, runtime-seeded
centers_init, legacy_owner).

Fixing the fallback surfaced the same latent bug in two existing
partial-config callers that had been silently depending on it: a
test fixture in test_train.py and scripts/warm_setup_cache.py's
minimal cfg (now merged against DEFAULT_CONFIG instead of hand-rolled,
closing the gap for good). See issues.md Issue 1.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
This commit is contained in:
2026-08-12 14:35:14 +02:00
co-authored by Claude Sonnet 5
parent 55332db67a
commit 9bf5874308
8 changed files with 963 additions and 369 deletions
+74
View File
@@ -27,6 +27,80 @@ def test_conditioning_enum_has_onehot():
}
# ---------------------------------------------------------------------------
# Config dataclasses (issues.md Issue 1)
# ---------------------------------------------------------------------------
def test_giant_config_to_dict_matches_default_config():
"""DEFAULT_CONFIG is generated from GiantConfig().to_dict() (not
hand-maintained), so the two cannot structurally drift apart — but this
pins the *equality* too, catching e.g. a stray in-place mutation of
DEFAULT_CONFIG added elsewhere after import."""
assert gconfig.GiantConfig().to_dict() == gconfig.DEFAULT_CONFIG
@pytest.mark.parametrize(
"cls",
[
gconfig.ConditioningAxisConfig,
gconfig.ConditioningConfig,
gconfig.FlowConfig,
gconfig.DdpmConfig,
gconfig.Stage1WganConfig,
gconfig.Stage2WganConfig,
gconfig.RouterConfig,
gconfig.Stage2RouterConfig,
gconfig.NSecConfig,
gconfig.ParticleTypeConfig,
gconfig.AutoregressiveConfig,
gconfig.Stage1ModelConfig,
gconfig.Stage2ModelConfig,
gconfig.TrainConfig,
gconfig.GiantConfig,
],
)
def test_config_dataclass_from_dict_round_trips_through_to_dict(cls):
assert cls.from_dict(cls().to_dict()) == cls()
assert cls.from_dict(None) == cls()
def test_stage2_model_config_defaults_match_documented_v030_intent():
"""The two keys issues.md Issue 1 found drifted between DEFAULT_CONFIG
and build_models/StageSpec.from_config's own .get(key, default)
fallbacks — pinned directly against the dataclass that is now their
shared single source of truth."""
spec = gconfig.Stage2ModelConfig()
assert spec.decoder == "autoregressive"
assert spec.particle_type.target == "onehot"
def test_router_config_extra_round_trips_composed_axis_keys():
d = {"enabled": True, "type": "composed", "axis0_type": "energy", "axis0_n_experts": 4}
router = gconfig.RouterConfig.from_dict(d)
assert router.enabled is True
assert router.extra == {"axis0_type": "energy", "axis0_n_experts": 4}
assert router.to_dict()["axis0_type"] == "energy"
def test_stage2_router_config_tie_to_stage1_not_leaked_into_extra():
router = gconfig.Stage2RouterConfig.from_dict({"tie_to_stage1": True})
assert router.tie_to_stage1 is True
assert "tie_to_stage1" not in router.extra
def test_stage1_router_config_has_no_tie_to_stage1_key():
"""Stage 1's router schema must not gain stage 2's tie_to_stage1 key —
that would change every future run's saved config.toml shape."""
assert "tie_to_stage1" not in gconfig.RouterConfig().to_dict()
def test_n_sec_config_extra_round_trips_legacy_owner():
n_sec = gconfig.NSecConfig.from_dict({"mode": "head", "legacy_owner": "stage1"})
assert n_sec.legacy_owner == "stage1"
assert n_sec.to_dict() == {"mode": "head", "lambda": 0.1, "legacy_owner": "stage1"}
# ---------------------------------------------------------------------------
# _deep_merge
# ---------------------------------------------------------------------------