v0.3.0 post-implementation audit: resolve all 9 tracked discrepancies

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>

tests/test_transforms.py

@@ -426,7 +426,13 @@ def test_build_features_embedding_mode_zero_fills_physical_columns():
     data = _minimal_step_data(3)
     pdg_map, mat_map = {11: 0}, {"PbWO4": 0}
 
-    cond_cont, *_ = build_features(data, pdg_map, mat_map, conditioning="embedding")
+    cond_cont, *_ = build_features(
+        data,
+        pdg_map,
+        mat_map,
+        particle_conditioning="embedding",
+        material_conditioning="embedding",
+    )
 
     assert cond_cont.shape[1] == COND_DIM
     np.testing.assert_allclose(cond_cont[:, COND_DIM_BASE:], 0.0)
@@ -438,7 +444,13 @@ def test_build_features_physical_mode_shape_and_values(fake_material_props):
     data = _minimal_step_data(3)
     pdg_map, mat_map = {11: 0}, {"PbWO4": 0}
 
-    cond_cont, *_ = build_features(data, pdg_map, mat_map, conditioning="physical")
+    cond_cont, *_ = build_features(
+        data,
+        pdg_map,
+        mat_map,
+        particle_conditioning="physical",
+        material_conditioning="physical",
+    )
 
     assert cond_cont.shape[1] == COND_DIM
     mass, charge = particle_mass_charge(11)
@@ -461,7 +473,13 @@ def test_build_features_physical_mode_unfilled_material_raises():
     pdg_map, mat_map = {11: 0}, {"G4_LYSO": 0}
 
     with pytest.raises(MaterialPropertiesNotFilledError):
-        build_features(data, pdg_map, mat_map, conditioning="physical")
+        build_features(
+            data,
+            pdg_map,
+            mat_map,
+            particle_conditioning="physical",
+            material_conditioning="physical",
+        )
 
 
 def test_build_cond_features_mass_charge_override(fake_material_props):
@@ -474,7 +492,13 @@ def test_build_cond_features_mass_charge_override(fake_material_props):
     data["charge"] = np.array([2.0, -2.0], dtype=np.float32)
     pdg_map, mat_map = {11: 0}, {"PbWO4": 0}
 
-    cond_cont, _ = build_cond_features(data, pdg_map, mat_map, conditioning="physical")
+    cond_cont, _ = build_cond_features(
+        data,
+        pdg_map,
+        mat_map,
+        particle_conditioning="physical",
+        material_conditioning="physical",
+    )
 
     np.testing.assert_allclose(
         cond_cont[:, COND_DIM_BASE], log_transform(np.array([123.0, 456.0]))
@@ -494,7 +518,12 @@ def test_build_cond_features_pads_legacy_normalizer_in_embedding_mode():
     legacy_norm.std = np.ones(COND_DIM_BASE, dtype=np.float32)
 
     cond_cont, _ = build_cond_features(
-        data, pdg_map, mat_map, cond_normalizer=legacy_norm, conditioning="embedding"
+        data,
+        pdg_map,
+        mat_map,
+        cond_normalizer=legacy_norm,
+        particle_conditioning="embedding",
+        material_conditioning="embedding",
     )
 
     assert cond_cont.shape[-1] == COND_DIM
@@ -521,7 +550,8 @@ def test_build_cond_features_rejects_legacy_normalizer_in_physical_mode(
             pdg_map,
             mat_map,
             cond_normalizer=legacy_norm,
-            conditioning="physical",
+            particle_conditioning="physical",
+            material_conditioning="physical",
         )
 
 
@@ -610,13 +640,23 @@ def test_build_cond_features_physical_mode_tolerates_out_of_vocab_pdg_and_materi
     }
 
     cond_cont, cond_cat = build_cond_features(
-        data, pdg_map, mat_map, conditioning="physical"
+        data,
+        pdg_map,
+        mat_map,
+        particle_conditioning="physical",
+        material_conditioning="physical",
     )
     assert cond_cont.shape[-1] == COND_DIM
     np.testing.assert_array_equal(cond_cat, [[0, 0]])  # dummy indices, no raise
 
     with pytest.raises(KeyError):
-        build_cond_features(data, pdg_map, mat_map, conditioning="embedding")
+        build_cond_features(
+            data,
+            pdg_map,
+            mat_map,
+            particle_conditioning="embedding",
+            material_conditioning="embedding",
+        )
 
 
 # ── _WelfordAccumulator ──────────────────────────────────────────────────────