The operator's call: "there should be one default learning rate and one
default max iterations and they should both be configurable at runtime."
There were SIX copies, not the four the audit described, and they did not
agree:
nisps/ml/mlp.hpp no-arg train() hardcoding 1.f / 1000u / 0.001f —
and firmware's ONLY training path calls exactly
this, so firmware had no runtime knob at all
wasm-iml.ts train() and trainAsync() TS default params (x2)
engine-api.ts learningRate ?? 1.0, with no maxIterations knob
vcv/src/iml.hpp 200 / 0.1 / 0.00001 — silently divergent
external_synth_midi.hpp its own kDefaultLearningRate/kDefaultMaxIterations
schemas/modes/*.json x9, identical, read by nobody at runtime
Now: schemas/ml_defaults.json is the single declaration (validated against a
sibling meta-schema, matching the midi_device.schema.json convention), codegen
emits it to C++ and TS in the same run, and MLPCore carries a TrainConfig whose
default member initialisers read the generated constant.
set_train_config()/nisps_ml_set_train_config() make it runtime-overridable on
every target; the explicit-argument train() overload is untouched. min_error
joins the tuple — it was duplicated identically and belongs with the other two.
The per-mode ml block loses default_learning_rate/default_max_iterations.
default_spread stays (genuinely wired on both targets) and input_channels stays
(codegen-time validated, real information for sound_analysis_midi).
VCV BEHAVIOUR CHANGE, deliberate: MEMLNaut.cpp constructs IML positionally and
relies on those defaults, so the module moves to 1000/1.0/0.001 — 5x the max
iterations, 10x the learning rate, and a 100x looser early-stop threshold. The
old values were never justified anywhere; they arrived with fbc68eb alongside
an unrelated module rewrite and no tuning rationale. Firmware and WASM have
shipped 1.0/1000 all along. It is now runtime-settable if this turns out worse.
The generated header lands in nisps/ml/generated/, not nisps/modes/generated/
where the rest of codegen output lives: training hyperparameters are an ML
fact, and nisps/ml sits below nisps/modes, so emitting them there would make
mlp.hpp include upward. The agent that built this flagged the directory-crossing
rather than hiding it; this is the fix. CI's generated-freshness gate learns the
new directory.
Gates: run-all-tests.sh ALL GREEN — 4/4 ctest, parity PASS (max delta 2.38e-7),
lint clean, manifold typecheck + 17 unit + 33 e2e (which exercise train() and
trainAsync() through a real browser).
Phase 2, S35. Two real defects from one root cause, both confirmed by trace
rather than taken from the audit:
1. Divergence. WasmIML built its TS Dataset mirror with a cap of 100 while
every addExample() ALSO pushed into the C++ FIFO ring, capped at 128. Since
train() reads the C++ ring and trainAsync() reads the TS mirror, past 100
examples the two trained on different datasets — silently.
2. Latent OOB read. nisps_ml_train sizes its sample-weight span by the C++
side's example_count() (up to 128), but wasm-iml.ts allocates that heap
buffer from the TS dataset's size (<=100). Once the ring exceeds the mirror,
the span reads past the end of the caller's allocation.
Fix: name the capacity ONCE as nisps::ml::kDefaultMaxExamples = 128, used by
FixedStorage's default template arg, DynamicStorage's default ctor arg, and the
MLP<> alias (which is the only real FixedStorage instantiation path and carried
its own independent 128 literal — the last copy of this dual truth). Expose it
through nisps_ml_describe and have the TS side read it instead of hardcoding.
Dataset's constructor default is removed entirely: a default was what invited
this bug class, and the sole call site now always supplies the describe() value.
ABI NOTE: this extends nisps_ml_describe from a 6-int to a 7-int descriptor.
nisps_ml_describe always writes 7 ints regardless of the caller's buffer, so
every call site had to grow in the same change or it would overflow the WASM
heap by 4 bytes per call. All five sites updated: three in wasm-iml.ts (init
defaults, init per-instance, reshape re-describe — the finding said there were
two), one in wasm-worker.ts, one in tests/cpp/parity_wasm.mjs. The parity
harness's expected-dims check now also pins the new max_examples slot.
Regression test: tests/cpp/test_mlp_storage_defaults.cpp — pins the two storage
policies to one constant, and drives MLPCore<DynamicStorage> exactly as
bindings.cpp does past the old TS cap, asserting it saturates at 128 and not at
100. Fail-before/pass-after confirmed by temporarily setting the constant to
100: 2 failures, named. Reverted: green.
Audit correction: the cited dataset.ts:81 is the FIFO eviction check; the
hardcoded default was at dataset.ts:45.
Gates: run-all-tests.sh ALL GREEN, parity PASS.
Phase 1 group 4 (S33, S34, L54).
- S33: removed 12 dead entries across the full 5-layer registration chain
(bindings.cpp KEEPALIVE -> EXPORTED_FUNCTIONS -> the NispsModule declaration
table -> the WasmIML wrapper -> the EngineApi facade): nisps_ml_reset,
example_count, move_weights, feedback_learning_paused, feedback_drag,
jolt_lr_scale, jolt_tick_lr_ramp, pipeline_state_size/save_state/load_state,
feedback_placing and feedback_state. Each was grepped against manifold/src,
manifold/tests, the e2e specs, manifold/tests/wasm-load.ts and
tests/cpp/parity_wasm.mjs — the parity gate builds its own API via cwrap and
is a real consumer, so it counts.
KEPT deliberately: EXPORTED_RUNTIME's heap views + ccall/cwrap (the parity
harness and wasm-load.ts depend on them), and nisps_ml_feedback_static_output,
whose C export IS called directly by parity_wasm.mjs even though no TS
wrapper reaches it. Also dropped parity_wasm.mjs's moveWeights cwrap, which
was declared but never invoked.
- S34: deleted the publishWeights_ channel — EngineSink.setWeights,
Spine.setWeights/weights()/liveWeights and every call site. It ran a C->heap
copy plus a fresh Float32Array allocation at up to 200 Hz into a field
nothing read. getWeights survives for persistence and the debug probe.
- L54: worklet loader — deleted the unused imports object, the 'c' branch,
exMap and the duplicate second loop, and replaced the silent `() => 0` stub
with one that throws, so a missing import fails loudly instead of returning
plausible zeros into the audio path.
manifold/public/nisps.{js,wasm} rebuilt with the trimmed export list (emcc
3.1.69, the CI-pinned version) and committed — the freshness gate added in
Phase 0 requires it, and the webhook ships this artifact to production.
Gates: run-all-tests.sh ALL GREEN, parity 1273 floats within 1e-5.
Operator-approved ABI change (P2 stop-point). The WASM MLP is now
MLPCore<DynamicStorage>:
- nisps_ml_create(input, output, hidden[3], n, seed) honours its args;
non-positive/null fall back to the historical 32→[10,14,18]→126, so
every pre-P2 caller (manifold, worker, parity harness) stays
bit-identical. Invalid/oversized dims (>4096) → null.
- NEW nisps_ml_reshape(ml, in, out, hidden, n, spread): fresh net at the
new dims, warm-started via nisps/ml/warm_start.hpp (overlapping region
copied; rest keeps spread init); feedback controller re-created (state
resets — reset-on-reshape modal is the front-end contract). Failure
leaves the old net untouched.
- nisps_ml_describe(ml, out): takes the handle; null reports defaults.
- FeedbackController got the same storage split: algorithms in
FeedbackControllerCore<FbStorage>; FixedFeedbackStorage keeps firmware/
tests source-identical via the old alias; DynamicFeedbackStorage (one
arena) sizes to the runtime net. Firmware .text unchanged (122692).
- MLHandle: per-instance scratch vectors; dropped the dead 2MB
batch_out_scratch.
- TS: types.ts decls (+_nisps_ml_reshape), wasm-iml re-describes the
created instance, worker carries a shape-contract note for P2.3.
Verified: ctest 4/4 incl. new warm-start grow/shrink test; reshape ABI
smoke (dims honoured, overlap survives, invalid rejected, outputs
bounded); parity PASS unchanged (2.4e-7); lint clean; manifold 9 unit +
20 e2e green; firmware .text 122692 (+0.30% vs pre-P2 baseline).
Wire the modular input layer into the Console and reshape the browser
engine so input axes are genuine independent dimensions.
Inputs (manifold/src/inputs/):
- gamepad-source: emit press+release edges with standard-mapping labels
(enables hold-and-move); single/double-stick already present.
- midi-input-source: single-device selection + batch "MIDI Learn"
(every CC swept while armed becomes an axis); notes stay discrete.
- input-layer: compose() forwards each axis 1:1 (no mean-blend);
add onReducedInput so the manifold tracks gamepad/MIDI position.
- types: InputAction.phase, InputMode.
Console (manifold/src/console/):
- ConsoleApp: bind gamepad buttons to verdicts (RB up / LB down /
X randomise / Y nudge / B undo / A-hold reposition); mirror composed
position onto the manifold.
- Drawers: rebuilt Inputs drawer (source picker, gamepad legend, MIDI
device picker + batch-learn flow, learned-control meters).
Engine (nisps/wasm, manifold/src/engine):
- DefaultMLP widened MLP<2,..> -> MLP<32,..> (32 = MAX_AXES); each
active axis gets a dedicated slot, unused slots held at 0 (inert).
Rebuilt nisps.wasm (playground + manifold).
- spine/engine-api: setInputs writes the full N-D vector (was dropping
arr[2+]); primary pair keeps the 2-D pipeline; process() re-ticks the
whole vector via spine.reprocess().
Tests:
- parity_check/parity_wasm: ParityMLP -> 32 inputs, widen example bufs.
- CMakeLists: build parity binary with -ffp-contract=off so native
matches FMA-free WASM (training amplified the gap past 1e-5).
Inputs dock is still an exclusive picker; mixing toggles, reshape modal,
and the >2-D slider view (inputs-spec.md) are groundwork-laid but not
yet wired. See docs/redesign/midi-gamepad-inputs-worklog.md.
Stream 7 wires nisps/ml + nisps/engines into the playground via Emscripten.
Highlights:
- nisps/wasm/bindings.cpp: flat C API per architecture.md §6.2. Fixed-arch
MLP<2, 10, 14, 18, 126>; engine string→type dispatch table with NoOp
fallback.
- scripts/build-wasm.sh: emcc invocation, MODULARIZE=1, exports listed
explicitly; produces playground/public/nisps.{js,wasm}.
- playground/src/ml/wasm-iml.ts: main-thread MLP host (sync inference,
sync training, RL ops, weights I/O, layer stats, localStorage).
- playground/src/ml/wasm-worker.ts: disposable Web Worker for off-thread
async training, owns its own WASM instance.
- playground/src/ml/dataset.ts: Float32Array-backed FIFO with sample-weight
modes (uniform/global/local/combined). Port of legacy dataset.js.
- playground/src/audio/engine-host.ts: AudioContext + AudioWorkletNode
lifecycle, with start/stop/setEngine/setParams.
- playground/src/audio/worklet/nisps-processor.ts: WASM-loading
AudioWorkletProcessor that runs engine.process_block per 128-sample
block. Loads its own WASM instance from main-thread-supplied bytes
(no fetch in worklet).
- playground/src/stores/ml-store.ts: wired stub methods to WasmIML
singleton; lazy initialize().
- playground/src/debug/probe.ts: window.__nisps now calls real WasmIML
via the store; lazy-init on first use.
Verified:
- bash scripts/build-wasm.sh succeeds (94 KB nisps.wasm)
- bun run typecheck OK
- bun run build OK (production bundle)
- vite dev server serves /nisps.{js,wasm} with COOP/COEP
Known limitation: WASM is fixed at one MLP shape. Multi-arch deferred —
documented in nisps/wasm/README.md.
