fix: strip leaked Technique-5 block hooks across runs (quality drift)

build_enhancements registered forward/forward-pre hooks directly on the
shared diffusion_model blocks but only removed them on scene-transition
sigma jumps, never at end-of-sampling. Single-scene runs (and the final
scene of multi-scene runs) thus left hooks installed; because ModelPatcher
clones share the underlying blocks, every subsequent generation stacked
another set, each lerp-ing block output toward a previous run's stale
reference tensor -> progressive corruption that survived Session Reset and
deleting refinements/ (the leak is in-process, not on disk) and only
cleared on a full restart.

Tag every installed hook (_FUNPACK_HOOK_TAG) and add strip_funpack_block_hooks
to pop only tagged entries from each block's hook stores (idempotent, leaves
foreign hooks intact). Strip at the top of build_enhancements and defensively
at FunPackLTXAVSceneChainSampler.sample() so accumulation is bounded to zero.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

ltx_enhancements.py

@@ -940,6 +940,53 @@ def _is_ltx_model(model):
     return False
 
 
+# ---------------------------------------------------------------------------
+# Block-hook leak guard
+# ---------------------------------------------------------------------------
+# Technique-5 forward hooks (see _register_hooks) attach directly to the SHARED
+# diffusion blocks. They are removed on a scene-transition sigma jump, but NOT at
+# end-of-sampling, so a single-scene run (or the final scene of a multi-scene run)
+# leaves them installed. Since the blocks are shared across ModelPatcher clones,
+# the next generation stacks another set — over many gens this compounds into
+# progressive output corruption that survives Session Reset and deleting
+# refinements/ (the hooks live in-process, not on disk). We tag every installed
+# hook and strip any leftovers at the start of each run so accumulation is bounded
+# to a single set and removed before the next sampling pass.
+_FUNPACK_HOOK_TAG = "_funpack_enh_hook"
+
+
+def _funpack_locate_blocks(model):
+    diff = getattr(getattr(model, "model", None), "diffusion_model", None)
+    if diff is None:
+        return None
+    for attr in ("transformer_blocks", "blocks", "joint_blocks", "layers"):
+        candidate = getattr(diff, attr, None)
+        if isinstance(candidate, torch.nn.ModuleList) and len(candidate) >= 28:
+            return candidate
+    return None
+
+
+def strip_funpack_block_hooks(model):
+    """Remove forward / forward-pre hooks this module installed on the shared
+    diffusion blocks in a previous run. Idempotent; safe to call every run."""
+    bl = _funpack_locate_blocks(model)
+    if bl is None:
+        return 0
+    removed = 0
+    for block in bl:
+        for store in (getattr(block, "_forward_hooks", None),
+                      getattr(block, "_forward_pre_hooks", None)):
+            if not store:
+                continue
+            for hid in [hid for hid, fn in list(store.items())
+                        if getattr(fn, _FUNPACK_HOOK_TAG, False)]:
+                store.pop(hid, None)
+                removed += 1
+    if removed:
+        print(f"[FunPackEnhancements] Stripped {removed} leaked block hook(s) from a previous run")
+    return removed
+
+
 # ---------------------------------------------------------------------------
 # Main enhancement builder
 # ---------------------------------------------------------------------------
@@ -965,6 +1012,10 @@ def build_enhancements(model, rating_profile, temporal_style, refinement_key, re
 
     model = model.clone()
 
+    # Strip any block hooks leaked by a previous run before installing fresh ones,
+    # so they cannot stack across generations (see _FUNPACK_HOOK_TAG note above).
+    strip_funpack_block_hooks(model)
+
     # --- VF score for temperature modulation ---
     vf_score = None
     if conditioning is not None and refinement_key:
@@ -1221,6 +1272,7 @@ def build_enhancements(model, rating_profile, temporal_style, refinement_key, re
                         return injected
                     except Exception:
                         return None
+                setattr(_hook, _FUNPACK_HOOK_TAG, True)
                 return _hook
 
             def _make_incontext_hooks(block_idx, buf, lazy_ref, strength, gate, s_state):
@@ -1272,6 +1324,8 @@ def build_enhancements(model, rating_profile, temporal_style, refinement_key, re
                     except Exception:
                         return None
 
+                setattr(_pre, _FUNPACK_HOOK_TAG, True)
+                setattr(_post, _FUNPACK_HOOK_TAG, True)
                 return _pre, _post
 
             for idx, (buf, lazy_ref, strength, gate) in _hook_block_params.items():

samplers.py

@@ -3472,6 +3472,19 @@ class FunPackLTXAVSceneChainSampler:
         if negative is None:
             negative = []
 
+        # Defensively strip any enhancement block hooks left on the shared diffusion
+        # model by a previous run (build_enhancements only removes them on scene
+        # transitions, not at end-of-sampling). This covers runs that don't go through
+        # build_enhancements, so stale hooks can't fire on an unenhanced generation.
+        try:
+            try:
+                from .ltx_enhancements import strip_funpack_block_hooks
+            except ImportError:
+                from ltx_enhancements import strip_funpack_block_hooks
+            strip_funpack_block_hooks(model)
+        except Exception as _e:
+            print(f"[FunPackLTXAVSceneChainSampler] hook strip failed: {_e}")
+
         # Decode-time noise (folded in from LTXV's Set VAE Decoder Noise per the boundary law:
         # the Chain Sampler owns IMAGES decode, so this lives here, not on a separate node).
         # Stamp settings onto a shallow copy of the VAE so we never mutate the shared input.