Commit graph

2 commits

Author SHA1 Message Date
w1n5t0n
f225c7c2a6 feat(wasm): add batch inference, extended training, pin mask, eval loss, and layer stats bindings
Five new C functions for the WASM module:
- nisps_mlp_infer_batch: N-point batch inference in a single call
- nisps_mlp_train_ex: training with per-iteration loss history output
- nisps_mlp_move_weights_ex: moveWeights with output pin mask to skip pinned nodes
- nisps_mlp_eval_loss: compute MSE loss without updating weights
- nisps_mlp_get_layer_stats: per-layer weight magnitude, dead, and saturation stats
2026-04-03 17:11:49 +01:00
w1n5t0n
f8983c4806 feat(playground): replace JS ML engine with WASM nisps-core
Compile nisps-core C++ MLP to WASM (36KB) and use it as the ML engine
in the playground, replacing the JavaScript port for inference, training,
and weight manipulation.

- Add extern "C" WASM bindings with spread-aware drawWeights/moveWeights
- WasmIML class is a drop-in replacement for the JS IML
- Inference runs on main thread via WASM (fast, synchronous)
- Training runs in a Web Worker with its own WASM instance (non-blocking)
- Interactive training (thumbs-up, train button) no longer freezes UI/audio
- Preset loading and state restore still use sync training
2026-03-23 23:23:07 +02:00