/**
 * Pure-TypeScript numeric kernel: a seeded RNG, sigmoid, and Float32 vector ops.
 * No dependencies. Deterministic given a seed so training and the eval gate are
 * reproducible (a flaky, unseeded SGD would make model promotion non-auditable).
 */
/** Deterministic, fast PRNG (mulberry32) in [0, 1). */
export declare function mulberry32(seed: number): () => number;
/** Sigmoid via lookup table; saturates to 0/1 beyond ±6. */
export declare function sigmoid(x: number): number;
/** Dot product of two dim-length rows at the given offsets. */
export declare function dot(a: Float32Array, ao: number, b: Float32Array, bo: number, dim: number): number;
/** L2 norm of a dim-length row. */
export declare function norm(a: Float32Array, ao: number, dim: number): number;
/** Cosine similarity of two dim-length rows. */
export declare function cosine(a: Float32Array, ao: number, b: Float32Array, bo: number, dim: number): number;
/** Return a row-normalized copy of a vocab×dim matrix (unit L2 per row). */
export declare function l2NormalizeRows(vectors: Float32Array, rows: number, dim: number): Float32Array;
export declare function f32ToBase64(a: Float32Array): string;
export declare function base64ToF32(s: string): Float32Array;