feat(video): step caching for HunyuanVideo-1.5 (MagCache auto, FBCache registry) + int8 trim fix

HunyuanVideo-1.5 loads previously logged 'fbcache unavailable (Model class
HunyuanVideo15TransformerBlock not registered)': diffusers 0.39 ships FBCache
block metadata for HunyuanVideo 1.0 but not 1.5, although the 1.5 DiT is fully
cache-shaped (CacheMixin, homogeneous residual-additive dual-stream blocks,
cache_context per guidance branch). Register the missing metadata at engage
time (deferring to a native registration when a future diffusers ships one).

Measured on a B200 (720p t2v, 1280x720, 33 frames, seed 42), FBCache is fast
but not shippable for this family: 1.44x at 30 steps / 2.41x at 50 steps, at
LPIPS 0.43-0.54 vs the same uncached stack with a +5..8 luma drift (no skip
cap or error budget, so the trajectory derails into a different clip). MagCache
(same registry metadata, also dispatched via enable_cache) is bounded by
design and lands the win: 1.49x end-to-end at 50 steps at LPIPS 0.147 with the
same composition, 1.21x at LPIPS 0.071 on the 480p model. Ship magcache as the
per-family AUTO cache mode for hunyuanvideo-1.5 / -720p with 50-step
calibrated per-family mag_ratios (cond/uncond curves agree within 0.014,
30 vs 50-step calibration within 0.027 after interpolation); every other
family keeps fbcache, and explicit fbcache/magcache requests are honored.
The auto toggle re-engages magcache on a step-count change so the ratio curve
is re-interpolated over the actual schedule.

Two production bugs fixed along the way:
- diffusers' HookRegistry caches its child-registry list, so enabling a cache
  AFTER any uncached generation (the auto off-to-on toggle) left the new block
  hooks without a context ('No context is set' on the first cached forward).
  Invalidate the stale cache after every enable_cache.
- An explicit int8 DiT request crashed under the padded-text trim: torchao's
  int8 dynamic path returns a zero-token (M=0) input unprojected (t2v byt5 /
  image streams -> cond-type add shape crash) and torch._int_mm requires
  M > 16 (an empty negative prompt trims to ~6 tokens -> TokenRefiner crash).
  Add per-family int8 excludes for the text-stream linears (context_embedder*,
  image_embedder, add_q/k/v_proj, to_add_out, ff_context); they run at tens of
  tokens vs the ~32k video stream, so the exclusion costs nothing measurable.

Bench: trim lever key (trim_off / eager_trim isolation configs), int8_cudnn +
shipped_nocache rows, --cache-threshold, warmup timing, per-config frame
persistence for offline LPIPS rescoring, and the loader's per-family auto
cache mode mirrored. Full 720p matrix recorded: reference 481.6s ->
trim+cudnn+compile 35.4s -> shipped default with TE/VAE quant + magcache
24.9s (19.4x, peak VRAM 89.4 -> 81.8 GB), int8 latency-neutral (dense auto
policy confirmed), compile 1.56x per step, trim 13.5x per step at production
shapes.

Validated end to end through the real VideoBackend: load resolves
transformer_cache=magcache with trim + compile + cudnn, generation
re-interpolates 50 -> 30 steps, auto-disengages below 20 steps, re-engages
after an uncached generation, unload restores globals. Hermetic tests cover
the registration, the child-cache invalidation, magcache engage/threshold/
no-curve/no-steps paths, auto-mode routing, toggle re-interpolation, and the
family int8 excludes.
This commit is contained in:
Daniel Han 2026-07-10 10:47:03 +00:00
commit c998183cc2
6 changed files with 637 additions and 50 deletions

View file

@ -356,3 +356,273 @@ def test_toggle_noop_without_cache_support(monkeypatch):
def test_toggle_noop_without_transformer():
assert maybe_toggle_step_cache(types.SimpleNamespace(), steps = 28) is None
# ── FBCache block-metadata registration (HunyuanVideo-1.5) ─────────────────────────
from core.inference.diffusion_cache import ( # noqa: E402
_ensure_block_metadata_registered,
_invalidate_child_registry_cache,
)
def _stub_hunyuan15_registry(monkeypatch):
"""Stub the two diffusers modules the registration helper imports: the FBCache
metadata registry (diffusers.hooks._helpers) and the HunyuanVideo-1.5 transformer
module carrying the block class. Returns (registry_cls, block_cls)."""
class _Metadata:
def __init__(
self,
return_hidden_states_index = None,
return_encoder_hidden_states_index = None,
):
self.return_hidden_states_index = return_hidden_states_index
self.return_encoder_hidden_states_index = return_encoder_hidden_states_index
class _Registry:
registry: dict = {}
@classmethod
def get(cls, model_class):
if model_class not in cls.registry:
raise ValueError(f"Model class {model_class} not registered.")
return cls.registry[model_class]
@classmethod
def register(cls, model_class, metadata):
cls.registry[model_class] = metadata
class HunyuanVideo15TransformerBlock: # the sentinel block class
pass
helpers = types.ModuleType("diffusers.hooks._helpers")
helpers.TransformerBlockMetadata = _Metadata
helpers.TransformerBlockRegistry = _Registry
monkeypatch.setitem(sys.modules, "diffusers.hooks._helpers", helpers)
blocks = types.ModuleType(
"diffusers.models.transformers.transformer_hunyuan_video15"
)
blocks.HunyuanVideo15TransformerBlock = HunyuanVideo15TransformerBlock
monkeypatch.setitem(
sys.modules,
"diffusers.models.transformers.transformer_hunyuan_video15",
blocks,
)
return _Registry, HunyuanVideo15TransformerBlock
class HunyuanVideo15Transformer3DModel(_MixinTransformer):
"""A CacheMixin-style fake whose CLASS NAME keys the extra-metadata table."""
def test_hunyuan15_block_metadata_is_registered(monkeypatch):
registry, block_cls = _stub_hunyuan15_registry(monkeypatch)
_ensure_block_metadata_registered(HunyuanVideo15Transformer3DModel())
meta = registry.registry[block_cls]
# The 1.5 dual-stream block returns (hidden_states, encoder_hidden_states) -- the
# same layout as the natively registered HunyuanVideo 1.0 block.
assert meta.return_hidden_states_index == 0
assert meta.return_encoder_hidden_states_index == 1
def test_hunyuan15_registration_defers_to_a_native_one(monkeypatch):
# A diffusers release that ships the registration natively must win: the helper
# probes TransformerBlockRegistry.get first and never overwrites.
registry, block_cls = _stub_hunyuan15_registry(monkeypatch)
native = object()
registry.registry[block_cls] = native
_ensure_block_metadata_registered(HunyuanVideo15Transformer3DModel())
assert registry.registry[block_cls] is native
def test_registration_noop_for_other_families(monkeypatch):
registry, _ = _stub_hunyuan15_registry(monkeypatch)
_ensure_block_metadata_registered(_MixinTransformer())
assert registry.registry == {}
def test_registration_failure_is_swallowed(monkeypatch):
# diffusers internals moved / import fails -> best-effort no-op; enable_cache then
# surfaces its own error and the load runs uncached, exactly as before the patch.
monkeypatch.setitem(sys.modules, "diffusers.hooks._helpers", None)
_ensure_block_metadata_registered(HunyuanVideo15Transformer3DModel()) # no raise
# ── stale child-registry invalidation after enable_cache ───────────────────────────
def test_invalidate_child_registry_cache_clears_stale_list():
# An UNCACHED generation's cache_context call froze an EMPTY child list on the
# transformer's HookRegistry; enable_cache installs block hooks _set_context would
# then never reach ("No context is set" on the first cached forward). The helper
# drops the stale cache so the next cache_context rebuilds it over the new hooks.
t = _MixinTransformer()
t._diffusers_hook = types.SimpleNamespace(_child_registries_cache = [])
_invalidate_child_registry_cache(t)
assert t._diffusers_hook._child_registries_cache is None
def test_invalidate_child_registry_cache_noops():
_invalidate_child_registry_cache(_MixinTransformer()) # no _diffusers_hook
t = _MixinTransformer()
t._diffusers_hook = types.SimpleNamespace(_child_registries_cache = None)
_invalidate_child_registry_cache(t) # nothing cached yet
assert t._diffusers_hook._child_registries_cache is None
def test_apply_step_cache_registers_and_invalidates_for_hunyuan15(monkeypatch):
_stub_diffusers(monkeypatch)
registry, block_cls = _stub_hunyuan15_registry(monkeypatch)
t = HunyuanVideo15Transformer3DModel()
t._diffusers_hook = types.SimpleNamespace(_child_registries_cache = [])
engaged = apply_step_cache(_pipe(t), mode = "fbcache")
assert engaged == TC_FBCACHE
assert t.enabled_with.threshold == DEFAULT_FBCACHE_THRESHOLD
assert block_cls in registry.registry # metadata registered before enable_cache
assert t._diffusers_hook._child_registries_cache is None # stale cache dropped
# ── magcache mode (per-family auto cache) ──────────────────────────────────────────
from core.inference.diffusion_cache import ( # noqa: E402
DEFAULT_MAGCACHE_THRESHOLD,
MAGCACHE_MAX_SKIP_STEPS,
MAGCACHE_RETENTION_RATIO,
TC_MAGCACHE,
_MAGCACHE_FAMILY_RATIOS,
auto_cache_mode,
)
class _MagConfig:
def __init__(
self,
threshold,
max_skip_steps,
retention_ratio,
num_inference_steps,
mag_ratios,
):
self.threshold = threshold
self.max_skip_steps = max_skip_steps
self.retention_ratio = retention_ratio
self.num_inference_steps = num_inference_steps
self.mag_ratios = mag_ratios
def _stub_diffusers_with_magcache(monkeypatch):
_stub_diffusers(monkeypatch)
hooks = sys.modules["diffusers.hooks"]
hooks.MagCacheConfig = _MagConfig
def test_normalize_accepts_magcache():
assert normalize_transformer_cache("magcache") == TC_MAGCACHE
assert normalize_transformer_cache("MagCache") == TC_MAGCACHE
def test_auto_cache_mode_per_family():
# HunyuanVideo-1.5: FBCache free-runs (no cap / no error budget) and derails the
# trajectory (measured LPIPS 0.54 at its default threshold), so auto engages the
# bounded MagCache there; every other family keeps the measured FBCache default.
assert auto_cache_mode("hunyuanvideo-1.5") == TC_MAGCACHE
assert auto_cache_mode("hunyuanvideo-1.5-720p") == TC_MAGCACHE
assert auto_cache_mode("HunyuanVideo-1.5-720p") == TC_MAGCACHE
for other in (None, "", "flux", "wan2.2-ti2v-5b", "ltx-2", "z-image"):
assert auto_cache_mode(other) == TC_FBCACHE
def test_magcache_families_have_calibrated_ratios():
# Every family the auto policy routes to magcache must ship a calibrated curve, or
# the auto default silently runs uncached (apply_step_cache checks the table).
from core.inference.diffusion_cache import _FAMILY_AUTO_CACHE_MODE
for fam, mode in _FAMILY_AUTO_CACHE_MODE.items():
if mode == TC_MAGCACHE:
ratios = _MAGCACHE_FAMILY_RATIOS[fam]
assert len(ratios) == 50 # the default 50-step schedule they were calibrated on
assert all(0.5 < r < 1.5 for r in ratios)
def test_magcache_engages_with_family_curve(monkeypatch):
_stub_diffusers_with_magcache(monkeypatch)
t = _MixinTransformer()
engaged = apply_step_cache(
_pipe(t), mode = "magcache", family = "hunyuanvideo-1.5-720p", steps = 50
)
assert engaged == TC_MAGCACHE
cfg = t.enabled_with
assert cfg.threshold == DEFAULT_MAGCACHE_THRESHOLD
assert cfg.max_skip_steps == MAGCACHE_MAX_SKIP_STEPS
assert cfg.retention_ratio == MAGCACHE_RETENTION_RATIO
assert cfg.num_inference_steps == 50
assert cfg.mag_ratios == list(_MAGCACHE_FAMILY_RATIOS["hunyuanvideo-1.5-720p"])
# The marker carries the step count so the auto toggle re-engages on a change.
assert t._unsloth_step_cache == f"magcache@{DEFAULT_MAGCACHE_THRESHOLD}#s50"
def test_magcache_without_calibration_runs_uncached(monkeypatch):
# No silent FBCache fallback: the family was routed to magcache exactly because
# FBCache derails it, so an uncalibrated family must run uncached instead.
_stub_diffusers_with_magcache(monkeypatch)
t = _MixinTransformer()
assert apply_step_cache(_pipe(t), mode = "magcache", family = "flux", steps = 50) is None
assert t.enabled_with is None
def test_magcache_without_steps_runs_uncached(monkeypatch):
_stub_diffusers_with_magcache(monkeypatch)
t = _MixinTransformer()
assert (
apply_step_cache(_pipe(t), mode = "magcache", family = "hunyuanvideo-1.5-720p") is None
)
assert t.enabled_with is None
def test_magcache_explicit_threshold_wins(monkeypatch):
_stub_diffusers_with_magcache(monkeypatch)
t = _MixinTransformer()
apply_step_cache(
_pipe(t), mode = "magcache", family = "hunyuanvideo-1.5-720p", steps = 30,
threshold = 0.24,
)
assert t.enabled_with.threshold == 0.24
def test_toggle_engages_family_magcache(monkeypatch):
_stub_diffusers_with_magcache(monkeypatch)
t = _ToggleTransformer()
mode = maybe_toggle_step_cache(
_pipe(t), steps = 30, mode = TC_MAGCACHE, family = "hunyuanvideo-1.5-720p"
)
assert mode == TC_MAGCACHE and t.enables == 1
assert t.enabled_with.num_inference_steps == 30
def test_toggle_magcache_reengages_on_step_change(monkeypatch):
# MagCache interpolates its calibrated curve over the CONFIGURED step count, so a
# step-count change must disable + re-enable; the same count stays idempotent.
_stub_diffusers_with_magcache(monkeypatch)
t = _ToggleTransformer()
maybe_toggle_step_cache(
_pipe(t), steps = 30, mode = TC_MAGCACHE, family = "hunyuanvideo-1.5-720p"
)
maybe_toggle_step_cache(
_pipe(t), steps = 30, mode = TC_MAGCACHE, family = "hunyuanvideo-1.5-720p"
)
assert t.enables == 1 and t.disables == 0 # idempotent at the same count
mode = maybe_toggle_step_cache(
_pipe(t), steps = 50, mode = TC_MAGCACHE, family = "hunyuanvideo-1.5-720p"
)
assert mode == TC_MAGCACHE and t.disables == 1 and t.enables == 2
assert t.enabled_with.num_inference_steps == 50
def test_toggle_magcache_disengages_below_bar(monkeypatch):
_stub_diffusers_with_magcache(monkeypatch)
t = _ToggleTransformer()
maybe_toggle_step_cache(
_pipe(t), steps = 30, mode = TC_MAGCACHE, family = "hunyuanvideo-1.5-720p"
)
mode = maybe_toggle_step_cache(
_pipe(t), steps = 8, mode = TC_MAGCACHE, family = "hunyuanvideo-1.5-720p"
)
assert mode is None and t.disables == 1