v0.3.0 step 6: sample.py/rollout.py AR generation + class->PDG decode

- 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>

tests/test_validate.py

@@ -1,5 +1,4 @@
 import numpy as np
-import pytest
 import torch
 
 from giant.constants import COND_DIM, K_MAX, SEC_SLOT_DIM, X_DIM
@@ -49,15 +48,6 @@ def _zero_secondaries_loader(B=4, n_batches=2):
     return batches
 
 
-@pytest.mark.xfail(
-    reason=(
-        "giant/validate.py isn't updated yet — it calls the stage models "
-        "(sample_secondaries et al.) with the old positional convention, "
-        "which doesn't match Stage1Model/Stage2OneShot's new forward "
-        "signature. Deferred to docs/v0.3.0-design.md step 6/§10."
-    ),
-    strict=False,
-)
 def test_validate_marginals_all_zero_secondaries_returns_nan_phys_kl(monkeypatch):
     """If n_sec_pred collapses to 0 across the whole validated set (realistic
     during early/unstable training), phys_kl must degrade to NaN instead of