66 lines
2 KiB
TypeScript
66 lines
2 KiB
TypeScript
|
import { expect, test } from 'bun:test';
|
||
|
|
import { Spine } from '../src/engine/spine';
|
||
|
|
import type { WasmIML } from '../src/engine/wasm-iml';
|
||
|
|
import { InputLayer } from '../src/inputs/input-layer';
|
||
|
|
import { XYPadSource } from '../src/inputs/xy-pad-source';
|
||
|
|
|
||
|
|
function makeFakeIml(outputSize = 20): WasmIML {
|
||
|
|
return {
|
||
|
|
architecture: {
|
||
|
|
inputSize: 2,
|
||
|
|
hidden: [0, 0, 0] as [number, number, number],
|
||
|
|
outputSize,
|
||
|
|
numLayers: 3,
|
||
|
|
},
|
||
|
|
setInputConfig: () => {},
|
||
|
|
setOutputConfig: () => {},
|
||
|
|
setOutputFreezeMask: () => {},
|
||
|
|
resetInput: () => {},
|
||
|
|
resetOutput: () => {},
|
||
|
|
processInput: (x: number, y: number) => ({ x, y, frozen: false }),
|
||
|
|
setInput: () => {},
|
||
|
|
processInto: (buf: Float32Array) => buf.fill(0.25),
|
||
|
|
processOutput: () => {},
|
||
|
|
} as unknown as WasmIML;
|
||
|
|
}
|
||
|
|
|
||
|
|
test('live inference publishes through the output channel without notifying state subscribers', () => {
|
||
|
|
const spine = new Spine();
|
||
|
|
spine.attach(makeFakeIml(), null);
|
||
|
|
spine.setState({ outputSize: 20 });
|
||
|
|
let stateNotifications = 0;
|
||
|
|
let outputNotifications = 0;
|
||
|
|
spine.subscribe(() => stateNotifications++);
|
||
|
|
spine.subscribeOutputs(() => outputNotifications++);
|
||
|
|
|
||
|
|
spine.setInputs([0.2, 0.8]);
|
||
|
|
spine.setInputs([0.3, 0.7]);
|
||
|
|
|
||
|
|
expect(stateNotifications).toBe(0);
|
||
|
|
expect(outputNotifications).toBe(1);
|
||
|
|
expect(spine.outputVersion()).toBe(2);
|
||
|
|
expect(Array.from(spine.outputs())).toEqual(new Array(20).fill(0.25));
|
||
|
|
});
|
||
|
|
|
||
|
|
test('InputLayer reuses its reduced input vector across animation frames', () => {
|
||
|
|
const layer = new InputLayer();
|
||
|
|
const source = new XYPadSource();
|
||
|
|
const writes: ReadonlyArray<number>[] = [];
|
||
|
|
layer.attach({
|
||
|
|
architecture: { inputSize: 2 },
|
||
|
|
setInputs: (values) => writes.push(values),
|
||
|
|
});
|
||
|
|
layer.setSources([source]);
|
||
|
|
|
||
|
|
source.pushAxes(0.2, 0.8);
|
||
|
|
layer.frame();
|
||
|
|
source.pushAxes(0.3, 0.7);
|
||
|
|
layer.frame();
|
||
|
|
|
||
|
|
expect(writes).toHaveLength(2);
|
||
|
|
expect(writes[0]).toBe(writes[1]);
|
||
|
|
expect(Array.from(writes[1])).toEqual(
|
||
|
|
Array.from(new Float32Array([0.3, 0.7])),
|
||
|
|
);
|
||
|
|
});
|