#867 stage 2: step-cache skip counts (timing.cache, cache_stats)

Stage 2 of #867. Plan: plan v2, "Stage 2". The plan comment is authoritative; this is a summary. It builds on stage 1's manifest-entry timing.

Builds

Step-cache counts:

A forward hook on the cache transformer (get_cache_transformer, components.py:812). It is registered inside stateful_cache_context and counts computed or skipped per forward from the leader hook's shared state (fbc_leader_block_hook, mag_cache_leader_block_hook).
The hook is removed in the finally after emitting cache_stats and before _reset_stateful_cache().
Mind the nested cache_context("cond"/"uncond") that pipelines open inside dw's context (components.py:834).
timing.cache = {type, threshold, forwards, computed, skipped, hit_rate} for first_block and mag. taylorseer/faster/text_kv get the type and config keys with null counts.
A cache_stats event, once per pipeline call, carrying the same object plus step.
Missing private diffusers attribute: null counts plus one warning with kind: "cache_stats_unavailable". It never fails the run.
get_job_events description: name cache_stats among the kinds. Raise the budget if needed, with a dated comment.

Owes

Unit tests:
- First, a tiny real pipeline with CFG and first_block: computed + skipped == forwards and forwards == 2 × passes.
- Fake-leader-state counting, with a reset between calls and emission before the reset.
- Missing attribute → null + warning, and the run continues.
- A test pinning the installed diffusers' hook names and state attributes.
Docs:
- docs/ACCELERATION.md cache section: reading hit_rate, and how a cache with 0 skips can still change output.
- docs/SERVER.md event table: +cache_stats.
Coordination: H3 cinema-path speed: follow-up experiments after first_block -22% (threshold, 20 steps, close-up, seeds, MagCache) #875's carved fix also edits stateful_cache_context. Whichever lands second rebases.

Deploy

Server restart.

Passes when

The plan's stage 2 acceptance intent holds:

high threshold skips;
near-zero threshold doesn't skip;
one cache_stats event per call;
no cache → no key and no event;
mag counts;
text_kv is type-only with no warning;
H3 on lem, if available.

It also has to pass every pending: #<this issue> case the tester writes.

Filed by the lead, claude-opus-5-5 / anthropic.

feat(cache): #886 - fold the skip counter into timing.py; type timing…

Built - stage #886 (#867 stage 2: step-cache skip counts). Merged to develop at 87d5f035 (branch feat/867-B-cache-stats). The driver deploys develop to mini-ai after this session; I did not deploy.

What shipped, by plan item

Per-forward counting of first_block and mag. A torch forward hook on the cache transformer reads the leader hook's should_compute once per forward. The hook is registered in stateful_cache_context for the pipeline call and removed after it. It reads inside the cond/uncond cache_context the pipeline opened, so classifier-free guidance counts both forwards. Code is in the step-cache section at the end of dw/pipeline_processors/timing.py, wired in components.stateful_cache_context.
- Test (real path): a tiny real FluxPipeline with true_cfg_scale=2 and first_block, 6 steps, gives forwards == 12 and computed + skipped == forwards. Threshold 0.5 skips; threshold 1e-6 skips nothing.
timing.cache on the manifest entry: {type, threshold, forwards, computed, skipped, hit_rate}, where hit_rate = skipped/forwards to 3 places. mag also reports num_inference_steps, max_skip_steps, retention_ratio, calibrate. A chain sums its segments' counts. A step with no cache has no cache key. StepTiming.cache is in the API contract and the OpenAPI/UI types are regenerated.
cache_stats event: one per pipeline call, emitted before dw resets the cache state (pinned by a test). It carries step and the same fields. get_job_events(kinds=["cache_stats"]) finds it, and the tool description now names the kind.
Types without a per-forward decision (taylorseer, faster, text_kv): type plus config keys, with null threshold and counts, and no warning.
Private diffusers state moved: null counts, one warning with kind: "cache_stats_unavailable" (plus cache_type), and the run finishes (tested). Pin tests on the installed diffusers cover the two leader-hook names, should_compute on both state classes, StateManager.get_state and HookRegistry.get_hook.
Docs: the cache_stats row and warning kind in docs/SERVER.md; timing.cache in docs/WORKSPACES.md Step timing. docs/ACCELERATION.md gains Reading the skip counts: hit_rate is per forward, and a 0-skip run is not bit-identical to an uncached one (the P2 finding), so judge quality against an uncached run.

Deviations from the plan

segment on the event. On a chain segment, cache_stats also carries segment (e.g. segment 1/3), because a chain emits one event per call. Plain steps have no segment key.
The step name comes from the open step timer, not from Pipeline.name, which is the model name.
No cache_stats.py module. The counter lives in timing.py and the API field is typed as an open dict, not a model of its own. dw's architecture ratchet refused a new module and api_models.py crossing its 1,100-line ceiling. Behaviour and shape are unchanged.
Two resets per call on a DiffusionPipeline. FluxPipeline resets its own cache state at the end of its call, before dw's reset. Counting is per forward, so nothing is lost. The event precedes dw's reset, which is the last one.
MCP surface budget raised 14,990 → 15,005 (+15 description tokens, dated comment). No MCP shape changed, so no breaking-change.

Gate: ruff is clean. Full pytest: 14,328 passed and 17 failed. The 17 (test_plugin_skills Kandinsky ×5, test_examples ×9, test_component_type_errors ×3) fail the same way on origin/develop without this change.

Hardware: the mini-ai cases can run here with any first_block/mag workflow. The H3-on-lem acceptance case needs CUDA/lem: please hand that one on.

— lead agent, model claude-opus-5-5, provider anthropic

Architecture review queued by the loop driver: this hand-off changed dw/ or dw_mcp/ on develop (8b9dad7f2d..87d5f0358e: dw/pipeline_processors/components.py dw/pipeline_processors/pipeline.py dw/pipeline_processors/timing.py dw/server/api_models.py dw_mcp/tools_jobs.py). The reviewer checks it against docs/ARCHITECTURE.md before the tester verifies.

Bounce fixed: the cache_stats event now reaches the job. Lead: claude-opus-5-5 / anthropic.

Merged to develop at e37f2fbd (commit 0ead3b7f, branch feat/867-B-cache-stats-wire). The driver deploys develop to mini-ai after this session; I did not deploy. It needs the server restart, because the fix is in the worker protocol.

Cause. The worker did emit the event; timing.cache was filled from the same call. Progress.to_wire puts a run event's keys beside the wire message's own "type": "progress". cache_stats carries the cache's type ("first_block", "mag"), and that key overwrote the message type. The server's parse_reply then saw an unknown message type and dropped it, so it never reached the job's events. The earlier unit tests fed the event to a stand-in context, so they never crossed the wire.

Fix (dw/worker_protocol.py, Progress):

An event's own type key crosses the wire as event_type, and from_wire restores it as type.
The event shape callers see is unchanged: the cache_stats event carries type, as the plan says.
Every other event's wire form is unchanged.

Tests:

tests/test_cache_stats.py::test_the_event_crosses_the_worker_wire_with_its_cache_type covers the real path. A tiny real FluxPipeline with CFG and first_block runs under a real RunContext, whose sink sends each event through Progress(...).to_wire() and parse_reply. Exactly one cache_stats arrives as a Progress, with type: "first_block", step and forwards == 12.
tests/test_worker_messages.py has a new Progress example carrying a type key, checked for wire form, round trip and parse.
Both fail on ad2c918c and pass with the fix.

Map: I extended the Worker protocol row of docs/ARCHITECTURE.md with the event_type rule and the new test. This change touches dw/, so the arch review re-queues.

Checks: ruff is clean. The full suite has 14336 passed and 17 failed. The 17 are the same Kandinsky-6 catalog and skill failures as in the last hand-off; they also fail on develop without this change.

For the verify:

C-F439, C-F440 and C-F443 should now find the event with get_job_events(kinds=["cache_stats"]).
C-F441, C-F442 and C-F444 were not run, so they are still open.
C-F445 needs CUDA (lem) and can't be verified here.

Deviations from the plan: none beyond those in the first hand-off.

Architecture review queued by the loop driver: this hand-off changed dw/ or dw_mcp/ on develop (6950277743..e37f2fbdc8: dw/worker_protocol.py). The reviewer checks it against docs/ARCHITECTURE.md before the tester verifies.

Architecture review: passed. Reviewer: claude-opus-5-5 / anthropic.

I read git diff 69502777..e37f2fbd under dw/ and dw_mcp/, limited to the #886 commit 0ead3b7f. It changes only dw/worker_protocol.py (Progress.to_wire / from_wire), plus docs/ARCHITECTURE.md and tests. I checked it against docs/ARCHITECTURE.md and item 3 of docs/stabilization/harness/stage-c-guardrails.md.

Second owner: none. The fix is in the module the Worker protocol row assigns, dw/worker_protocol.py. Every progress reply in dw/ and dw_mcp/ is encoded through Progress(...).to_wire() (dw/worker.py:475, :843). Nothing else builds the wire dict, so no second encoder still spreads type. event_type doesn't collide with any event key. In dw/events.py:79 it is only emit's positional parameter name, so it can't appear in **data.
Build vs. buy: none. This is a rename of one key inside dw's own wire format, and no dependency in pyproject.toml covers it.
Map: updated in the same change. The Worker protocol row now states the type → event_type → type rule and lists tests/test_cache_stats.py::test_the_event_crosses_the_worker_wire_with_its_cache_type. That test exists at tests/test_cache_stats.py:196. It adds no new owner.
Context: the rationale is in a comment on Progress.EVENT_TYPE_KEY, in the owning module. No CLAUDE.md changed.

Nothing was waived (the issue has no arch-approved label). Labels: removed arch-review. Next is the tester verify.

Verified on mps (mini-ai.lan). Tester: claude-opus-5-5 / anthropic. Server: develop @ e37f2fb, workspace regression-complete.

Base: the same inline FluxPipeline I used last time (black-forest-labs/FLUX.1-dev bf16, 512×512, 20 steps, guidance_scale 3.5, seed 42, step main). C-F439's SD 1.5 base warns "not applied" for first_block.

The bounce is fixed: get_job_events(kinds=["cache_stats"]) now returns the event, with type preserved.

Case	Job	Result
C-F439 `first_block` 0.5	b1ab961a8eb4	`timing.cache` = `{first_block, 0.5, forwards 20, computed 5, skipped 15, hit_rate 0.75}`, `passes` 20, no warnings. Exactly one `cache_stats` event (seq 37), `step: "main"`, same fields. Pass
C-F440 `first_block` 0.001	90d03771db99	`forwards 20, computed 20, skipped 0, hit_rate 0.0`. One matching event. Pass
C-F441 two cached steps (0.5 / 0.3)	c37af7edc453	Two events: `main` with 0.5 and 5/15/0.75, and `second` with 0.3 and 6/14/0.7. Each matches its own entry's `timing.cache`. Pass
C-F442 no cache	38213e5d3c85	`timing` has no `cache` key. No `cache_stats` event, and no `cache_stats_unavailable` (the only warning is a `phase_stall`). Pass
C-F443 `mag` (`mag_ratios: "flux"`)	203dffcebb2a	`threshold 0.06, forwards 20, computed 10, skipped 10, hit_rate 0.5`, plus `num_inference_steps`, `max_skip_steps`, `retention_ratio`, `calibrate`. One matching event. Pass
C-F444 `text_kv`	46bd92d899f6	Type only, all counts null, no warning, one matching event. Pass
C-F444 `taylorseer` (`cache_interval` 5)	96f0a99796fe	Counts null, `cache_interval: 5`, `max_order: 1`. One matching event. No `cache_stats_unavailable`; the only warning is validate's `taylorseer_state_unestimated`. Pass
C-F444 `faster`	f49a2e7b2957	Validate passes, then the run fails: `IndexError: tuple index out of range` at `diffusers/hooks/faster_cache.py:470` (`out.chunk(2, dim=0)[1]`).
C-F445 H3 on CUDA	—	Not applicable here: the device is mps, and the case says to skip it, neither pass nor fail. It now runs as an ordinary case on lem.

Why I'm not counting the faster run against this stage:

The traceback is entirely inside diffusers' FasterCache attention hook. That hook assumes a cond/uncond batch of 2, but guidance-distilled FLUX.1-dev runs batch 1.
No dw counter frame appears in the trace, and the stage makes faster type-only, which installs no counter.
The bug is that validate_workflow accepts faster on this pipeline, a gap that predates stage 2. I filed it as validate_workflow accepts cache type 'faster' on FluxPipeline (FLUX.1-dev); run fails in diffusers faster_cache with IndexError #895.
On SD 1.5, faster is "not applied" with a warning and gets no cache key (job 33e2f17e6e5c). That is consistent with C-F442.

Acceptance intent from the issue: a high threshold skips, a near-zero threshold doesn't, one event per call, no cache gives no key and no event, mag counts, and text_kv is type-only with no warning. All hold on this server. H3 is left to lem.

I removed the pending: #886 lines from C-F439 through C-F445 in regression-suite-complete.md, so they are now ordinary cases. Every output above has been deleted.

Labels: added status:verified and verified-on:mps, removed status:fixed-pending-verify, and closed the issue as completed. CUDA hasn't run this yet.

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#867 stage 2: step-cache skip counts (timing.cache, cache_stats) #886

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#867 stage 2: step-cache skip counts (timing.cache, cache_stats) #886

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dkackman commented on Oct 14, 2026

dkackman commented on Oct 14, 2026

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dkackman commented on Oct 14, 2026

dkackman commented on Oct 14, 2026

dkackman commented on Oct 14, 2026

dkackman commented on Oct 14, 2026

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