# SPDX-License-Identifier: AGPL-3.0-only # Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0 """Hermetic CPU tests for opt-in step caching (First-Block-Cache). ``diffusers`` is stubbed via ``sys.modules`` (the module under test imports ``FirstBlockCacheConfig`` lazily), and the pipeline is a fake that records the engaged config. So normalisation, the CacheMixin (``enable_cache``) gating, threshold selection, and the best-effort failure handling are all exercised without torch or a real diffusers model. """ from __future__ import annotations import sys import types import pytest from core.inference.diffusion_cache import ( DEFAULT_FBCACHE_THRESHOLD, QUANT_FBCACHE_THRESHOLD, TC_FBCACHE, apply_step_cache, normalize_transformer_cache, ) # ── normalize_transformer_cache ──────────────────────────────────────────────────── def test_normalize_disabled_values_are_none(): for value in (None, "", " ", "none", "off", "OFF", "None"): assert normalize_transformer_cache(value) is None def test_normalize_fbcache_and_casing(): assert normalize_transformer_cache("fbcache") == TC_FBCACHE assert normalize_transformer_cache("FBCache") == TC_FBCACHE assert normalize_transformer_cache(" fbcache ") == TC_FBCACHE def test_normalize_rejects_unknown(): with pytest.raises(ValueError): normalize_transformer_cache("deepcache") # ── apply_step_cache ─────────────────────────────────────────────────────────────── class _Config: def __init__(self, threshold): self.threshold = threshold class _MixinTransformer: """A CacheMixin-style transformer: exposes ``enable_cache``.""" def __init__(self, *, fail = False): self.fail = fail self.enabled_with = None def enable_cache(self, config): if self.fail: raise RuntimeError("block signature not recognised") self.enabled_with = config class _NonCacheMixinTransformer: """A transformer with no ``enable_cache`` (not a CacheMixin) -> must run uncached. Its pipeline opens no ``cache_context``, so installing FBCache would crash at generation; the load runs uncached instead (e.g. Z-Image).""" class _CtxPipe: """A pipeline whose denoise loop opens ``transformer.cache_context(...)`` (like FluxPipeline) -- the First-Block-Cache hook needs it, so FBCache may engage here.""" def __init__(self, transformer): self.transformer = transformer def __call__(self, *args, **kwargs): with self.transformer.cache_context("cond"): return None class _NoCtxPipe: """A pipeline that never enters a caching context (like FluxKontextPipeline / img2img / inpaint / controlnet, which reuse the CacheMixin FluxTransformer2DModel): FBCache must NOT engage or the hook raises "No context is set" on the first forward.""" def __init__(self, transformer): self.transformer = transformer def __call__(self, *args, **kwargs): return None def _pipe(transformer): return _CtxPipe(transformer) def _stub_diffusers(monkeypatch, *, hook_recorder = None): diffusers = types.ModuleType("diffusers") diffusers.FirstBlockCacheConfig = _Config monkeypatch.setitem(sys.modules, "diffusers", diffusers) hooks = types.ModuleType("diffusers.hooks") def _apply_first_block_cache(transformer, config): if hook_recorder is not None: hook_recorder["transformer"] = transformer hook_recorder["config"] = config hooks.apply_first_block_cache = _apply_first_block_cache monkeypatch.setitem(sys.modules, "diffusers.hooks", hooks) def test_disabled_mode_is_noop(monkeypatch): _stub_diffusers(monkeypatch) t = _MixinTransformer() assert apply_step_cache(_pipe(t), mode = None) is None assert apply_step_cache(_pipe(t), mode = "off") is None assert t.enabled_with is None def test_enable_cache_path_default_threshold(monkeypatch): _stub_diffusers(monkeypatch) t = _MixinTransformer() engaged = apply_step_cache(_pipe(t), mode = "fbcache") assert engaged == TC_FBCACHE assert t.enabled_with.threshold == DEFAULT_FBCACHE_THRESHOLD assert t._unsloth_step_cache == f"fbcache@{DEFAULT_FBCACHE_THRESHOLD}" def test_quant_active_raises_default_threshold(monkeypatch): _stub_diffusers(monkeypatch) t = _MixinTransformer() apply_step_cache(_pipe(t), mode = "fbcache", quant_active = True) assert t.enabled_with.threshold == QUANT_FBCACHE_THRESHOLD def test_explicit_threshold_overrides_quant(monkeypatch): _stub_diffusers(monkeypatch) t = _MixinTransformer() apply_step_cache(_pipe(t), mode = "fbcache", threshold = 0.2, quant_active = True) assert t.enabled_with.threshold == 0.2 def test_non_cachemixin_runs_uncached(monkeypatch): # A transformer without enable_cache (e.g. Z-Image) must NOT install the standalone hook: its # pipeline opens no cache_context, so it runs uncached instead of crashing at generation. rec: dict = {} _stub_diffusers(monkeypatch, hook_recorder = rec) t = _NonCacheMixinTransformer() assert apply_step_cache(_pipe(t), mode = "fbcache") is None assert rec == {} # the standalone hook was never called def test_pipeline_without_cache_context_runs_uncached(monkeypatch): # A CacheMixin transformer whose PIPELINE never opens a cache_context (Flux Kontext / img2img / # inpaint / controlnet reuse FluxTransformer2DModel) must run uncached, else the First-Block-Cache # hook raises "No context is set" on the first forward. _stub_diffusers(monkeypatch) t = _MixinTransformer() assert apply_step_cache(_NoCtxPipe(t), mode = "fbcache") is None assert t.enabled_with is None # enable_cache was never called def test_incompatible_model_runs_uncached(monkeypatch): # enable_cache raising (e.g. unrecognised block signature) must not fail the load. _stub_diffusers(monkeypatch) t = _MixinTransformer(fail = True) assert apply_step_cache(_pipe(t), mode = "fbcache") is None def test_enable_cache_failure_rolls_back_partial_hooks(monkeypatch): # enable_cache can raise after hooking some blocks; the reported-uncached model must not actually # run half-cached, so the failure path calls disable_cache. _stub_diffusers(monkeypatch) t = _MixinTransformer(fail = True) t.disabled = False t.disable_cache = lambda: setattr(t, "disabled", True) assert apply_step_cache(_pipe(t), mode = "fbcache") is None assert t.disabled is True def test_config_import_falls_back_to_hooks_module(monkeypatch): # Older diffusers exports FirstBlockCacheConfig only from diffusers.hooks. diffusers = types.ModuleType("diffusers") # no FirstBlockCacheConfig attribute monkeypatch.setitem(sys.modules, "diffusers", diffusers) hooks = types.ModuleType("diffusers.hooks") hooks.FirstBlockCacheConfig = _Config monkeypatch.setitem(sys.modules, "diffusers.hooks", hooks) t = _MixinTransformer() assert apply_step_cache(_pipe(t), mode = "fbcache") == TC_FBCACHE assert t.enabled_with.threshold == DEFAULT_FBCACHE_THRESHOLD def test_missing_transformer_is_none(monkeypatch): _stub_diffusers(monkeypatch) pipe = types.SimpleNamespace(transformer = None) assert apply_step_cache(pipe, mode = "fbcache") is None def test_diffusers_unavailable_runs_uncached(monkeypatch): # No diffusers import: best-effort returns None and the load proceeds uncached. Block the hooks # module too, since the config import falls back to it and a real earlier import may have left it # cached in sys.modules. monkeypatch.setitem(sys.modules, "diffusers", None) monkeypatch.setitem(sys.modules, "diffusers.hooks", None) t = _MixinTransformer() assert apply_step_cache(_pipe(t), mode = "fbcache") is None # ── the auto policy: normalize("auto") + generation-time toggling ────────────────── from core.inference.diffusion_cache import ( # noqa: E402 FBCACHE_MIN_STEPS, TC_AUTO, effective_denoise_steps, effective_request_strength, maybe_toggle_step_cache, ) # ── effective_denoise_steps (strength-aware step count for the auto policy) ───────── def test_effective_steps_txt2img_is_full_count(): # No strength (txt2img / reference) -> the full requested step count. assert effective_denoise_steps(28, None) == 28 assert effective_denoise_steps(28, 1.0) == 28 # full redraw denoises every step def test_effective_steps_low_strength_shrinks_below_the_bar(): # A 28-step upscale at strength 0.35 denoises int(9.8) = 9 steps (diffusers floors the product), # below FBCACHE_MIN_STEPS, so the auto policy must NOT engage FBCache. eff = effective_denoise_steps(28, 0.35) assert eff == 9 assert eff < FBCACHE_MIN_STEPS def test_effective_request_strength_uses_pipe_default_when_omitted(): import inspect # txt2img or a pipe without the strength kwarg gives the full trajectory (None). assert effective_request_strength(None, False, True, 0.6) is None assert effective_request_strength(0.5, True, False, None) is None # img2img with an explicit strength -> that value. assert effective_request_strength(0.2, True, True, 0.6) == 0.2 # img2img with an OMITTED strength uses the pipe's own signature default, so the auto policy keys # on the real (short) trajectory: int(28 * 0.6) = 16 real steps, not 28. s = effective_request_strength(None, True, True, 0.6) assert s == 0.6 assert effective_denoise_steps(28, s) == 16 # A non-numeric signature default falls back to the full count. assert effective_request_strength(None, True, True, inspect.Parameter.empty) is None assert effective_request_strength(None, True, True, None) is None def test_effective_steps_matches_diffusers_get_timesteps(): # Mirror diffusers exactly: it denoises min(int(steps * strength), steps) steps (floored). for steps, strength in [(28, 0.35), (28, 0.8), (50, 0.5), (20, 0.99), (30, 0.1)]: expected = max(1, min(int(steps * strength), steps)) assert effective_denoise_steps(steps, strength) == expected def test_toggle_stays_off_for_low_strength_workflow(monkeypatch): # End to end: a 28-step request would engage FBCache, but at strength 0.35 the effective ~10 steps # keep it uncached. _stub_diffusers(monkeypatch) t = _ToggleTransformer() mode = maybe_toggle_step_cache(_pipe(t), steps = effective_denoise_steps(28, 0.35)) assert mode is None and t.enables == 0 class _ToggleTransformer(_MixinTransformer): """CacheMixin-style fake with the disable side too, counting transitions.""" def __init__(self): super().__init__() self.enables = 0 self.disables = 0 def enable_cache(self, config): super().enable_cache(config) self.enables += 1 def disable_cache(self): self.disables += 1 def test_normalize_auto_is_a_distinct_state(): assert normalize_transformer_cache("auto") == TC_AUTO assert normalize_transformer_cache(" AUTO ") == TC_AUTO def test_apply_treats_stray_auto_as_off(monkeypatch): # AUTO must be resolved by the loader; if it ever reaches the engage call the load runs uncached # instead of crashing. _stub_diffusers(monkeypatch) t = _MixinTransformer() assert apply_step_cache(_pipe(t), mode = "auto") is None assert t.enabled_with is None def test_toggle_engages_at_the_step_bar(monkeypatch): _stub_diffusers(monkeypatch) t = _ToggleTransformer() mode = maybe_toggle_step_cache(_pipe(t), steps = FBCACHE_MIN_STEPS) assert mode == TC_FBCACHE and t.enables == 1 assert t.enabled_with.threshold == DEFAULT_FBCACHE_THRESHOLD assert t._unsloth_step_cache def test_toggle_uses_quant_threshold(monkeypatch): _stub_diffusers(monkeypatch) t = _ToggleTransformer() maybe_toggle_step_cache(_pipe(t), steps = 28, quant_active = True) assert t.enabled_with.threshold == QUANT_FBCACHE_THRESHOLD def test_toggle_is_idempotent_when_engaged(monkeypatch): _stub_diffusers(monkeypatch) t = _ToggleTransformer() maybe_toggle_step_cache(_pipe(t), steps = 28) mode = maybe_toggle_step_cache(_pipe(t), steps = 28) assert mode == TC_FBCACHE and t.enables == 1 and t.disables == 0 def test_toggle_disengages_below_the_bar(monkeypatch): _stub_diffusers(monkeypatch) t = _ToggleTransformer() maybe_toggle_step_cache(_pipe(t), steps = 28) mode = maybe_toggle_step_cache(_pipe(t), steps = 8) assert mode is None and t.disables == 1 assert not t._unsloth_step_cache # and it stays off on repeat calls (no flapping disable calls). assert maybe_toggle_step_cache(_pipe(t), steps = 8) is None assert t.disables == 1 def test_toggle_reengages_after_a_disable(monkeypatch): _stub_diffusers(monkeypatch) t = _ToggleTransformer() maybe_toggle_step_cache(_pipe(t), steps = 28) maybe_toggle_step_cache(_pipe(t), steps = 8) mode = maybe_toggle_step_cache(_pipe(t), steps = 24) assert mode == TC_FBCACHE and t.enables == 2 def test_toggle_noop_without_cache_support(monkeypatch): _stub_diffusers(monkeypatch) t = _NonCacheMixinTransformer() assert maybe_toggle_step_cache(_pipe(t), steps = 28) is None assert maybe_toggle_step_cache(_pipe(t), steps = 8) is None def test_toggle_noop_without_transformer(): assert maybe_toggle_step_cache(types.SimpleNamespace(), steps = 28) is None # ── compiled cache-hook inners (regional compile x step cache composition) ────────── import functools # noqa: E402 from core.inference.diffusion_cache import ( # noqa: E402 _compile_hooked_block_inners, _invalidate_child_registry_cache, _restore_hooked_block_inners, ) class _BoundInner: """Provides a plain bound method for fn_ref.original_forward (__self__ present).""" def forward(self, *args, **kwargs): return "eager" def _hooked_block( *, compiled = True, hook_name = "fbc_block_hook", bound = True, ): inner = _BoundInner() orig = inner.forward if bound else functools.partial(_BoundInner.forward, inner) hook = types.SimpleNamespace(fn_ref = types.SimpleNamespace(original_forward = orig)) block = types.SimpleNamespace( _diffusers_hook = types.SimpleNamespace(hooks = {hook_name: hook}), _compiled_call_impl = object() if compiled else None, ) return block, hook, orig def _fake_dit(blocks): return types.SimpleNamespace(modules = lambda: [types.SimpleNamespace()] + blocks) def _stub_torch_compile(monkeypatch): compiled_calls = [] def _compile(fn, **kwargs): compiled_calls.append((fn, kwargs)) wrapper = lambda *a, **k: fn(*a, **k) # noqa: E731 wrapper._unsloth_test_compiled_of = fn return wrapper torch = types.ModuleType("torch") torch.compile = _compile monkeypatch.setitem(sys.modules, "torch", torch) return compiled_calls def test_arming_swaps_inner_for_compiled_wrapper(monkeypatch): calls = _stub_torch_compile(monkeypatch) block, hook, orig = _hooked_block() assert _compile_hooked_block_inners(_fake_dit([block])) == 1 assert hook.fn_ref.original_forward is not orig assert hook.fn_ref.original_forward._unsloth_test_compiled_of is orig assert hook._unsloth_orig_inner is orig # The inner compile must match the cache-active tier: graph-breakable + dynamic. assert calls[0][1] == {"fullgraph": False, "dynamic": True} def test_arming_is_idempotent(monkeypatch): _stub_torch_compile(monkeypatch) block, hook, _ = _hooked_block() dit = _fake_dit([block]) assert _compile_hooked_block_inners(dit) == 1 once = hook.fn_ref.original_forward assert _compile_hooked_block_inners(dit) == 0 # marker short-circuits assert hook.fn_ref.original_forward is once def test_arming_skips_uncompiled_blocks(monkeypatch): # An eager-tier load has no _compiled_call_impl: the hook must stay untouched (compiling the inner # would ADD compile where the user chose eager). _stub_torch_compile(monkeypatch) block, hook, orig = _hooked_block(compiled = False) assert _compile_hooked_block_inners(_fake_dit([block])) == 0 assert hook.fn_ref.original_forward is orig def test_arming_skips_partial_captured_inner(monkeypatch): # A stacked hook chain (e.g. group offload) captures a functools.partial, not the plain bound # method; arming would compile the wrong layer of the chain. _stub_torch_compile(monkeypatch) block, hook, orig = _hooked_block(bound = False) assert _compile_hooked_block_inners(_fake_dit([block])) == 0 assert hook.fn_ref.original_forward is orig def test_arming_covers_every_cache_hook_family(monkeypatch): # FBCache is the image cache today, but the hook-name table already covers the MagCache layout # (same fn_ref shape), so a future mode arms for free. _stub_torch_compile(monkeypatch) names = ( "mag_cache_leader_block_hook", "mag_cache_block_hook", "fbc_leader_block_hook", "fbc_block_hook", ) blocks = [_hooked_block(hook_name = n)[0] for n in names] assert _compile_hooked_block_inners(_fake_dit(blocks)) == len(names) def test_restore_puts_the_exact_original_back(monkeypatch): _stub_torch_compile(monkeypatch) block, hook, orig = _hooked_block() dit = _fake_dit([block]) _compile_hooked_block_inners(dit) _restore_hooked_block_inners(dit) assert hook.fn_ref.original_forward is orig assert hook._unsloth_orig_inner is None def test_restore_tolerates_fakes_without_modules(): _restore_hooked_block_inners(_MixinTransformer()) # no .modules(): no-op def test_apply_step_cache_arms_compiled_blocks_on_toggle(monkeypatch): # The generation-time toggle engages the cache AFTER the load already compiled the blocks, so # apply_step_cache must arm the fresh hooks itself. _stub_diffusers(monkeypatch) _stub_torch_compile(monkeypatch) block, hook, orig = _hooked_block() class _T(_MixinTransformer): def modules(self): return [block] t = _T() engaged = apply_step_cache(_pipe(t), mode = "fbcache") assert engaged == TC_FBCACHE assert hook.fn_ref.original_forward is not orig assert hook._unsloth_orig_inner is orig def test_toggle_disable_restores_inners_before_disable(monkeypatch): # remove_hook splices fn_ref.original_forward back into module.forward, so the compiled wrapper # must be swapped out BEFORE disable_cache runs. _stub_diffusers(monkeypatch) order = [] class _T(_ToggleTransformer): def disable_cache(self): super().disable_cache() order.append("disable") def modules(self): order.append("restore-walk") return [] t = _T() maybe_toggle_step_cache(_pipe(t), steps = 28) mode = maybe_toggle_step_cache(_pipe(t), steps = 8) assert mode is None and t.disables == 1 assert order[-2:] == ["restore-walk", "disable"] def test_enable_failure_restores_inners_before_partial_disable(monkeypatch): # enable_cache can fail after hooking (and arming) some blocks; the partial-hook cleanup must # un-arm them before disable_cache splices original_forward back. _stub_diffusers(monkeypatch) order = [] class _T(_ToggleTransformer): def enable_cache(self, config): raise RuntimeError("block signature not recognised") def disable_cache(self): super().disable_cache() order.append("disable") def modules(self): order.append("restore-walk") return [] t = _T() assert apply_step_cache(_pipe(t), mode = "fbcache") is None assert order == ["restore-walk", "disable"] # ── stale child-registry cache invalidation (mid-session enable) ──────────────────── def test_enable_invalidates_stale_child_registry_cache(monkeypatch): # diffusers 0.39 caches the child-registry list on first cache_context use, and an UNCACHED # generation already populates it (empty), so a later toggle-time enable_cache would install hooks # the context never reaches ("No context is set"). _stub_diffusers(monkeypatch) t = _MixinTransformer() t._diffusers_hook = types.SimpleNamespace(_child_registries_cache = ["stale"]) assert apply_step_cache(_pipe(t), mode = "fbcache") == TC_FBCACHE assert t._diffusers_hook._child_registries_cache is None def test_invalidate_child_registry_cache_tolerates_absence(): _invalidate_child_registry_cache(types.SimpleNamespace()) # no registry: no-op reg = types.SimpleNamespace(_child_registries_cache = None) _invalidate_child_registry_cache(types.SimpleNamespace(_diffusers_hook = reg)) assert reg._child_registries_cache is None