8da6767273
- domain.rs: atomic instance counter for unique Linear weight seeds (C3) - rapid_adapt.rs: adapt() returns Result instead of panicking (C5), bounded calibration buffer with max_buffer_frames cap (F1-HIGH), validate lora_rank >= 1 (F10) - geometry.rs: 24-bit PRNG precision matching f32 mantissa (C2) - virtual_aug.rs: guard against room_scale=0 division-by-zero (F6) - signal/lib.rs: re-export AmplitudeStats from hardware_norm (W1) - train/lib.rs: crate-root re-exports for all MERIDIAN types (W2) All 201 tests pass (96 unit + 24 integration + 18 subcarrier + 10 metrics + 7 doctests + 105 signal + 10 validation + 1 signal doctest). Co-Authored-By: claude-flow <ruv@ruv.net>
366 lines
13 KiB
Rust
366 lines
13 KiB
Rust
//! MERIDIAN Phase 3 -- Geometry Encoder with FiLM Conditioning (ADR-027).
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//!
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//! Permutation-invariant encoding of AP positions into a 64-dim geometry
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//! vector, plus FiLM layers for conditioning backbone features on room
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//! geometry. Pure Rust, no external dependencies beyond the workspace.
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use serde::{Deserialize, Serialize};
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const GEOMETRY_DIM: usize = 64;
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const NUM_COORDS: usize = 3;
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// ---------------------------------------------------------------------------
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// Linear layer (pure Rust)
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// ---------------------------------------------------------------------------
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/// Fully-connected layer: `y = x W^T + b`. Row-major weights `[out, in]`.
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#[derive(Debug, Clone)]
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struct Linear {
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weights: Vec<f32>,
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bias: Vec<f32>,
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in_f: usize,
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out_f: usize,
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}
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impl Linear {
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/// Kaiming-uniform init: U(-k, k), k = sqrt(1/in_f).
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fn new(in_f: usize, out_f: usize, seed: u64) -> Self {
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let k = (1.0 / in_f as f32).sqrt();
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Linear {
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weights: det_uniform(in_f * out_f, -k, k, seed),
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bias: vec![0.0; out_f],
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in_f,
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out_f,
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}
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}
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fn forward(&self, x: &[f32]) -> Vec<f32> {
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debug_assert_eq!(x.len(), self.in_f);
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let mut y = self.bias.clone();
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for j in 0..self.out_f {
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let off = j * self.in_f;
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let mut s = 0.0f32;
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for i in 0..self.in_f {
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s += x[i] * self.weights[off + i];
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}
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y[j] += s;
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}
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y
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}
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}
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/// Deterministic xorshift64 uniform in `[lo, hi)`.
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/// Uses 24-bit precision (matching f32 mantissa) for uniform distribution.
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fn det_uniform(n: usize, lo: f32, hi: f32, seed: u64) -> Vec<f32> {
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let r = hi - lo;
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let mut s = seed.wrapping_add(0x9E37_79B9_7F4A_7C15);
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(0..n)
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.map(|_| {
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s ^= s << 13;
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s ^= s >> 7;
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s ^= s << 17;
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lo + (s >> 40) as f32 / (1u64 << 24) as f32 * r
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})
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.collect()
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}
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fn relu(v: &mut [f32]) {
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for x in v.iter_mut() {
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if *x < 0.0 { *x = 0.0; }
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}
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}
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// ---------------------------------------------------------------------------
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// MeridianGeometryConfig
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// ---------------------------------------------------------------------------
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/// Configuration for the MERIDIAN geometry encoder and FiLM layers.
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct MeridianGeometryConfig {
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/// Number of Fourier frequency bands (default 10).
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pub n_frequencies: usize,
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/// Spatial scale factor, 1.0 = metres (default 1.0).
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pub scale: f32,
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/// Output embedding dimension (default 64).
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pub geometry_dim: usize,
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/// Random seed for weight init (default 42).
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pub seed: u64,
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}
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impl Default for MeridianGeometryConfig {
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fn default() -> Self {
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MeridianGeometryConfig { n_frequencies: 10, scale: 1.0, geometry_dim: GEOMETRY_DIM, seed: 42 }
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}
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}
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// ---------------------------------------------------------------------------
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// FourierPositionalEncoding
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// ---------------------------------------------------------------------------
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/// Fourier positional encoding for 3-D coordinates.
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///
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/// Per coordinate: `[sin(2^0*pi*x), cos(2^0*pi*x), ..., sin(2^(L-1)*pi*x),
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/// cos(2^(L-1)*pi*x)]`. Zero-padded to `geometry_dim`.
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pub struct FourierPositionalEncoding {
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n_frequencies: usize,
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scale: f32,
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output_dim: usize,
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}
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impl FourierPositionalEncoding {
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/// Create from config.
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pub fn new(cfg: &MeridianGeometryConfig) -> Self {
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FourierPositionalEncoding { n_frequencies: cfg.n_frequencies, scale: cfg.scale, output_dim: cfg.geometry_dim }
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}
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/// Encode `[x, y, z]` into a fixed-length vector of `geometry_dim` elements.
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pub fn encode(&self, coords: &[f32; 3]) -> Vec<f32> {
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let raw = NUM_COORDS * 2 * self.n_frequencies;
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let mut enc = Vec::with_capacity(raw.max(self.output_dim));
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for &c in coords {
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let sc = c * self.scale;
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for l in 0..self.n_frequencies {
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let f = (2.0f32).powi(l as i32) * std::f32::consts::PI * sc;
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enc.push(f.sin());
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enc.push(f.cos());
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}
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}
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enc.resize(self.output_dim, 0.0);
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enc
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}
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}
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// ---------------------------------------------------------------------------
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// DeepSets
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// ---------------------------------------------------------------------------
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/// Permutation-invariant set encoder: phi each element, mean-pool, then rho.
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pub struct DeepSets {
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phi: Linear,
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rho: Linear,
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dim: usize,
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}
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impl DeepSets {
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/// Create from config.
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pub fn new(cfg: &MeridianGeometryConfig) -> Self {
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let d = cfg.geometry_dim;
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DeepSets { phi: Linear::new(d, d, cfg.seed.wrapping_add(1)), rho: Linear::new(d, d, cfg.seed.wrapping_add(2)), dim: d }
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}
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/// Encode a set of embeddings (each of length `geometry_dim`) into one vector.
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pub fn encode(&self, ap_embeddings: &[Vec<f32>]) -> Vec<f32> {
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assert!(!ap_embeddings.is_empty(), "DeepSets: input set must be non-empty");
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let n = ap_embeddings.len() as f32;
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let mut pooled = vec![0.0f32; self.dim];
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for emb in ap_embeddings {
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debug_assert_eq!(emb.len(), self.dim);
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let mut t = self.phi.forward(emb);
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relu(&mut t);
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for (p, v) in pooled.iter_mut().zip(t.iter()) { *p += *v; }
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}
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for p in pooled.iter_mut() { *p /= n; }
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let mut out = self.rho.forward(&pooled);
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relu(&mut out);
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out
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}
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}
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// ---------------------------------------------------------------------------
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// GeometryEncoder
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// ---------------------------------------------------------------------------
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/// End-to-end encoder: AP positions -> 64-dim geometry vector.
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pub struct GeometryEncoder {
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pos_embed: FourierPositionalEncoding,
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set_encoder: DeepSets,
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}
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impl GeometryEncoder {
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/// Build from config.
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pub fn new(cfg: &MeridianGeometryConfig) -> Self {
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GeometryEncoder { pos_embed: FourierPositionalEncoding::new(cfg), set_encoder: DeepSets::new(cfg) }
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}
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/// Encode variable-count AP positions `[x,y,z]` into a fixed-dim vector.
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pub fn encode(&self, ap_positions: &[[f32; 3]]) -> Vec<f32> {
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let embs: Vec<Vec<f32>> = ap_positions.iter().map(|p| self.pos_embed.encode(p)).collect();
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self.set_encoder.encode(&embs)
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}
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}
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// ---------------------------------------------------------------------------
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// FilmLayer
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// ---------------------------------------------------------------------------
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/// Feature-wise Linear Modulation: `output = gamma(g) * h + beta(g)`.
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pub struct FilmLayer {
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gamma_proj: Linear,
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beta_proj: Linear,
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}
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impl FilmLayer {
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/// Create a FiLM layer. Gamma bias is initialised to 1.0 (identity).
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pub fn new(cfg: &MeridianGeometryConfig) -> Self {
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let d = cfg.geometry_dim;
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let mut gamma_proj = Linear::new(d, d, cfg.seed.wrapping_add(3));
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for b in gamma_proj.bias.iter_mut() { *b = 1.0; }
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FilmLayer { gamma_proj, beta_proj: Linear::new(d, d, cfg.seed.wrapping_add(4)) }
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}
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/// Modulate `features` by `geometry`: `gamma(geometry) * features + beta(geometry)`.
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pub fn modulate(&self, features: &[f32], geometry: &[f32]) -> Vec<f32> {
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let gamma = self.gamma_proj.forward(geometry);
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let beta = self.beta_proj.forward(geometry);
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features.iter().zip(gamma.iter()).zip(beta.iter()).map(|((&f, &g), &b)| g * f + b).collect()
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}
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}
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// ---------------------------------------------------------------------------
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// Tests
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// ---------------------------------------------------------------------------
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#[cfg(test)]
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mod tests {
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use super::*;
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fn cfg() -> MeridianGeometryConfig { MeridianGeometryConfig::default() }
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#[test]
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fn fourier_output_dimension_is_64() {
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let c = cfg();
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let out = FourierPositionalEncoding::new(&c).encode(&[1.0, 2.0, 3.0]);
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assert_eq!(out.len(), c.geometry_dim);
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}
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#[test]
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fn fourier_different_coords_different_outputs() {
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let enc = FourierPositionalEncoding::new(&cfg());
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let a = enc.encode(&[0.0, 0.0, 0.0]);
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let b = enc.encode(&[1.0, 0.0, 0.0]);
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let c = enc.encode(&[0.0, 1.0, 0.0]);
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let d = enc.encode(&[0.0, 0.0, 1.0]);
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assert_ne!(a, b); assert_ne!(a, c); assert_ne!(a, d); assert_ne!(b, c);
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}
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#[test]
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fn fourier_values_bounded() {
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let out = FourierPositionalEncoding::new(&cfg()).encode(&[5.5, -3.2, 0.1]);
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for &v in &out { assert!(v.abs() <= 1.0 + 1e-6, "got {v}"); }
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}
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#[test]
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fn deepsets_permutation_invariant() {
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let c = cfg();
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let enc = FourierPositionalEncoding::new(&c);
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let ds = DeepSets::new(&c);
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let (a, b, d) = (enc.encode(&[1.0,0.0,0.0]), enc.encode(&[0.0,2.0,0.0]), enc.encode(&[0.0,0.0,3.0]));
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let abc = ds.encode(&[a.clone(), b.clone(), d.clone()]);
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let cba = ds.encode(&[d.clone(), b.clone(), a.clone()]);
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let bac = ds.encode(&[b.clone(), a.clone(), d.clone()]);
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for i in 0..c.geometry_dim {
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assert!((abc[i] - cba[i]).abs() < 1e-5, "dim {i}: abc={} cba={}", abc[i], cba[i]);
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assert!((abc[i] - bac[i]).abs() < 1e-5, "dim {i}: abc={} bac={}", abc[i], bac[i]);
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}
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}
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#[test]
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fn deepsets_variable_ap_count() {
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let c = cfg();
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let enc = FourierPositionalEncoding::new(&c);
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let ds = DeepSets::new(&c);
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let one = ds.encode(&[enc.encode(&[1.0,0.0,0.0])]);
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assert_eq!(one.len(), c.geometry_dim);
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let three = ds.encode(&[enc.encode(&[1.0,0.0,0.0]), enc.encode(&[0.0,2.0,0.0]), enc.encode(&[0.0,0.0,3.0])]);
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assert_eq!(three.len(), c.geometry_dim);
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let six = ds.encode(&[
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enc.encode(&[1.0,0.0,0.0]), enc.encode(&[0.0,2.0,0.0]), enc.encode(&[0.0,0.0,3.0]),
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enc.encode(&[-1.0,0.0,0.0]), enc.encode(&[0.0,-2.0,0.0]), enc.encode(&[0.0,0.0,-3.0]),
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]);
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assert_eq!(six.len(), c.geometry_dim);
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assert_ne!(one, three); assert_ne!(three, six);
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}
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#[test]
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fn geometry_encoder_end_to_end() {
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let c = cfg();
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let g = GeometryEncoder::new(&c).encode(&[[1.0,0.0,2.5],[0.0,3.0,2.5],[-2.0,1.0,2.5]]);
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assert_eq!(g.len(), c.geometry_dim);
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for &v in &g { assert!(v.is_finite()); }
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}
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#[test]
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fn geometry_encoder_single_ap() {
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let c = cfg();
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assert_eq!(GeometryEncoder::new(&c).encode(&[[0.0,0.0,0.0]]).len(), c.geometry_dim);
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}
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#[test]
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fn film_identity_when_geometry_zero() {
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let c = cfg();
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let film = FilmLayer::new(&c);
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let feat = vec![1.0f32; c.geometry_dim];
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let out = film.modulate(&feat, &vec![0.0f32; c.geometry_dim]);
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assert_eq!(out.len(), c.geometry_dim);
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// gamma_proj(0) = bias = [1.0], beta_proj(0) = bias = [0.0] => identity
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for i in 0..c.geometry_dim {
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assert!((out[i] - feat[i]).abs() < 1e-5, "dim {i}: expected {}, got {}", feat[i], out[i]);
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}
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}
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#[test]
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fn film_nontrivial_modulation() {
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let c = cfg();
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let film = FilmLayer::new(&c);
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let feat: Vec<f32> = (0..c.geometry_dim).map(|i| i as f32 * 0.1).collect();
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let geom: Vec<f32> = (0..c.geometry_dim).map(|i| (i as f32 - 32.0) * 0.01).collect();
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let out = film.modulate(&feat, &geom);
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assert_eq!(out.len(), c.geometry_dim);
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assert!(out.iter().zip(feat.iter()).any(|(o, f)| (o - f).abs() > 1e-6));
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for &v in &out { assert!(v.is_finite()); }
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}
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#[test]
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fn film_explicit_gamma_beta() {
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let c = MeridianGeometryConfig { geometry_dim: 4, ..cfg() };
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let mut film = FilmLayer::new(&c);
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film.gamma_proj.weights = vec![0.0; 16];
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film.gamma_proj.bias = vec![2.0, 3.0, 0.5, 1.0];
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film.beta_proj.weights = vec![0.0; 16];
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film.beta_proj.bias = vec![10.0, 20.0, 30.0, 40.0];
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let out = film.modulate(&[1.0, 2.0, 3.0, 4.0], &[999.0; 4]);
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let exp = [12.0, 26.0, 31.5, 44.0];
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for i in 0..4 { assert!((out[i] - exp[i]).abs() < 1e-5, "dim {i}"); }
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}
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#[test]
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fn config_defaults() {
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let c = MeridianGeometryConfig::default();
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assert_eq!(c.n_frequencies, 10);
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assert!((c.scale - 1.0).abs() < 1e-6);
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assert_eq!(c.geometry_dim, 64);
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assert_eq!(c.seed, 42);
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}
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#[test]
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fn config_serde_round_trip() {
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let c = MeridianGeometryConfig { n_frequencies: 8, scale: 0.5, geometry_dim: 32, seed: 123 };
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let j = serde_json::to_string(&c).unwrap();
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let d: MeridianGeometryConfig = serde_json::from_str(&j).unwrap();
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assert_eq!(d.n_frequencies, 8); assert!((d.scale - 0.5).abs() < 1e-6);
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assert_eq!(d.geometry_dim, 32); assert_eq!(d.seed, 123);
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}
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#[test]
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fn linear_forward_dim() {
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assert_eq!(Linear::new(8, 4, 0).forward(&vec![1.0; 8]).len(), 4);
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}
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#[test]
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fn linear_zero_input_gives_bias() {
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let lin = Linear::new(4, 3, 0);
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let out = lin.forward(&[0.0; 4]);
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for i in 0..3 { assert!((out[i] - lin.bias[i]).abs() < 1e-6); }
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}
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}
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