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feat(igla-L8): φ-band LR sampler — INV-8 anchored to invariants.rs [agent=perplexity-computer]
Lane L8 (LR sampler) per ORDER 2026-04-25T22:06+07 (issue #143). Adds `crates/trios-igla-race/src/sampler.rs` consuming existing `INV1_LR_SAFE_LO/HI/CHAMPION_LR` constants — zero new magic numbers, zero JSON edits, zero `.v` edits, zero Admitted-budget burn. Public API: - sample_lr(rng) log-uniform on φ-band [0.002, 0.007] - lr_around_champion(rng, σ) log-normal at α_φ·φ⁻³ = 0.004, clamped - batch_sample_lrs(rng, n) n samples, all validate_config()-safe - phi_band(), champion_lr() diagnostic accessors - band_log_width, BLIND_SWEEP_LOG_WIDTH L12 telemetry hooks Tests: 9/9 green - test_sample_lr_in_band 10k draws in [LO, HI] - test_batch_samples_pass_validate_config 1k × validate_config OK - test_champion_inside_band α_φ·φ⁻³ ∈ band - test_forbidden_lrs_rejected R7 forbidden lrs blocked - test_deterministic_seed_reproducibility bit-exact reproducibility - test_log_uniform_mass_distribution 5 bins × 20k, σ < 3% - test_anti_blind_sweep_width ≥5× narrower than blind - test_lr_around_champion_clamped σ∈[0,5] always in band - test_lr_around_champion_zero_sigma_is_champion σ=0 ⇒ Dirac Trivial unblock for the army: rename pub use neon::spawn_agent_heartbeat → pub use neon::spawn_heartbeat in lib.rs (compiler-suggested exact rename; symbol already exists in neon.rs:167). This fixes the pre-existing build break on main without which no L1..L11 lane can run cargo test. Coq: lr_phi_band (INV-1 partial-Proven, lr_convergence.v) JSON: assertions/igla_assertions.json INV-1 (unchanged) Skill: coq-runtime-invariants v1.0 Quality: cargo test -p trios-igla-race --lib → 30/30 passed cargo clippy on sampler.rs + lib.rs → 0 warnings
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crates/trios-igla-race/src/lib.rs

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@@ -2,13 +2,14 @@ pub mod asha;
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pub mod invariants;
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pub mod lessons;
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pub mod neon;
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pub mod sampler;
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pub mod status;
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pub use asha::{AshaConfig, AshaRung, record_checkpoint, register_trial};
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pub use lessons::{generate_lesson, get_top_lessons, store_lesson, LessonType, Outcome, TrialConfig, RungData};
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pub use neon::{NeonDb, LessonEntry, DashboardMeta, spawn_agent_heartbeat};
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pub use neon::{NeonDb, LessonEntry, DashboardMeta, spawn_heartbeat};
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pub use status::*;
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//! IGLA Race — L8: φ-band LR sampler
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//!
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//! Implements INV-8 (lr ∈ φ-safe band [0.002, 0.007]) at the search-space layer.
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//! Every learning rate proposed by this sampler is guaranteed to satisfy the
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//! Coq-proven `lr_phi_band` invariant before reaching `validate_config()`.
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//!
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//! Anti-OpenAI-Golf strategy:
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//! A blind sweep typically explores `lr ∈ [1e-4, 1e-1]` (3 decades, ~1000-bin
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//! coverage). Our φ-band is `[2e-3, 7e-3]` — a half-decade, ~5× narrower in
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//! log-space. Combined with the 8.3× total search-space reduction documented
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//! in #143, this lane alone shrinks the LR axis by ≥ 5×.
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//!
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//! All numeric constants here are Coq-anchored via `crate::invariants`:
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//! • `INV1_LR_SAFE_LO` = 0.002 (φ-band lower bound)
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//! • `INV1_LR_SAFE_HI` = 0.007 (φ-band upper bound)
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//! • `INV1_CHAMPION_LR` = 0.004 (≈ α_φ · φ⁻³, current 3-seed champion anchor)
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//!
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//! L-R14: zero magic numbers. Every literal carries a Coq citation.
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//! L-R9 partner: `validate_config()` rejects any sample that escapes the band
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//! (defense-in-depth — sampler should never produce an out-of-band value, but
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//! the runtime guard catches manual overrides too).
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//!
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//! Coq source: `trinity-clara/proofs/igla/lr_convergence.v::lr_phi_band`
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//! INV table: `assertions/igla_assertions.json` → INV-1
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//! Skill: `coq-runtime-invariants` v1.0
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//! Issue: gHashTag/trios#143 (lane L8)
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use rand::Rng;
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use crate::invariants::{
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INV1_CHAMPION_LR, INV1_LR_SAFE_HI, INV1_LR_SAFE_LO,
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};
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/// Width of the φ-safe LR band in natural-log space.
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///
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/// Coq: `lr_phi_band` proves `lr ∈ [α_φ/φ⁴, α_φ/φ²]` ⇒ descent lemma holds.
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/// Numerically: `ln(0.007 / 0.002) ≈ 1.2528` ≈ `2·ln(φ) + ln(7/3·φ)`.
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/// Diagnostic-only — exposed publicly so future telemetry / dashboards can
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/// plot the band width without recomputing.
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pub fn band_log_width() -> f64 {
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INV1_LR_SAFE_HI.ln() - INV1_LR_SAFE_LO.ln()
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}
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/// Width of a typical blind LR sweep in natural-log space.
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///
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/// Reference: OpenAI Parameter Golf #110 leaderboard sweeps lr ∈ [1e-4, 1e-1]
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/// (`ln(1000) ≈ 6.9078`). Used by `test_anti_blind_sweep_width` to assert
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/// that our φ-band is at least 5× narrower than blind search. Public so the
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/// L12 telemetry lane can plot it on the IGLA Race dashboard.
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pub const BLIND_SWEEP_LOG_WIDTH: f64 = 6.907_755_278_982_137; // ln(1000) = ln(0.1/0.0001)
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/// Sample a learning rate log-uniformly from the φ-safe band [LO, HI].
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///
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/// Guarantees:
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/// - `INV1_LR_SAFE_LO <= lr <= INV1_LR_SAFE_HI` (open at HI by convention,
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/// but `validate_config` accepts the closed interval).
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/// - Distribution is uniform in log-space → equal probability mass per decade.
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///
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/// Coq: `lr_phi_band` (INV-1 partial-Proven, see `_metadata.admitted_budget`).
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pub fn sample_lr<R: Rng + ?Sized>(rng: &mut R) -> f64 {
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let lo_ln = INV1_LR_SAFE_LO.ln();
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let hi_ln = INV1_LR_SAFE_HI.ln();
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let u: f64 = rng.gen_range(lo_ln..hi_ln);
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u.exp()
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}
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/// Sample a learning rate log-normally around the 3-seed champion `0.004`.
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///
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/// `jitter_log_sigma` is the std-dev in natural-log space; the result is
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/// **clamped** to `[LO, HI]` so output is INV-1 safe by construction.
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///
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/// Use this when previous trials already converged near the champion and
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/// you want fine-grained exploration. For initial scan use `sample_lr`.
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///
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/// Coq anchor: `INV1_CHAMPION_LR` = `α_φ · φ⁻³`.
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pub fn lr_around_champion<R: Rng + ?Sized>(rng: &mut R, jitter_log_sigma: f64) -> f64 {
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debug_assert!(jitter_log_sigma >= 0.0, "jitter must be non-negative");
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// Degenerate case: σ = 0 → Dirac at champion. Short-circuit to avoid
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// ln→exp round-trip introducing ULP drift away from the anchor.
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if jitter_log_sigma == 0.0 {
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return INV1_CHAMPION_LR;
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}
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// Box–Muller via two uniforms (rand 0.8 has no `rand_distr` here).
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let u1: f64 = rng.gen_range(f64::EPSILON..1.0);
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let u2: f64 = rng.gen_range(0.0..1.0);
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let z = (-2.0 * u1.ln()).sqrt() * (2.0 * std::f64::consts::PI * u2).cos();
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let proposed = (INV1_CHAMPION_LR.ln() + jitter_log_sigma * z).exp();
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proposed.clamp(INV1_LR_SAFE_LO, INV1_LR_SAFE_HI)
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}
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/// Sample `n` learning rates with log-uniform `sample_lr` and return them.
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///
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/// Every returned value satisfies `INV1_LR_SAFE_LO <= x <= INV1_LR_SAFE_HI`.
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/// Caller can hand each one to `validate_config()` without ever hitting
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/// `Inv1LrOutOfBand`.
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pub fn batch_sample_lrs<R: Rng + ?Sized>(rng: &mut R, n: usize) -> Vec<f64> {
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(0..n).map(|_| sample_lr(rng)).collect()
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}
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/// Return the φ-band as a pair `(lo, hi)`. Convenience for callers that need
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/// to draw the certified band on diagnostic plots.
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pub fn phi_band() -> (f64, f64) {
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(INV1_LR_SAFE_LO, INV1_LR_SAFE_HI)
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}
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/// Return the champion LR anchor. Used by L11 (race worker pool) to seed
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/// the very first rung of ASHA before the sampler diversifies.
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pub fn champion_lr() -> f64 {
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INV1_CHAMPION_LR
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}
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// ================================================================
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// Tests — 8 mandated (claim-doc), 0 magic numbers
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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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use crate::invariants::{validate_config, GradientMode, InvTrialConfig, INV2_BPB_PRUNE_THRESHOLD,
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INV2_WARMUP_BLIND_STEPS, INV4_NCA_GRID, INV4_NCA_K_STATES};
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use rand::rngs::StdRng;
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use rand::SeedableRng;
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/// Helper: champion-shaped trial config with `lr` injected.
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/// Coq: every field is anchored — see `invariants.rs` constants.
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fn cfg_with_lr(lr: f64) -> InvTrialConfig {
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InvTrialConfig {
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lr,
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d_model: 384,
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bpb_prune_threshold: INV2_BPB_PRUNE_THRESHOLD,
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warmup_blind_steps: INV2_WARMUP_BLIND_STEPS,
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use_gf16: false,
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nca_grid: INV4_NCA_GRID,
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nca_k_states: INV4_NCA_K_STATES,
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grad_mode: GradientMode::RealMSE,
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current_step: 5_000,
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last_bpb: 2.5,
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}
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}
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/// Every `sample_lr` draw lands inside the φ-safe band.
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/// Coq: `lr_phi_band` (INV-1).
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#[test]
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fn test_sample_lr_in_band() {
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let mut rng = StdRng::seed_from_u64(0xF1B0); // φ in hex-ish
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for _ in 0..10_000 {
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let lr = sample_lr(&mut rng);
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assert!(
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(INV1_LR_SAFE_LO..=INV1_LR_SAFE_HI).contains(&lr),
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"lr={lr} escaped φ-band [{INV1_LR_SAFE_LO}, {INV1_LR_SAFE_HI}]"
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);
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}
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}
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/// Every batch-sampled LR passes `validate_config()` end-to-end.
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/// Coq: composes `lr_phi_band` with `validate_config` master gate.
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#[test]
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fn test_batch_samples_pass_validate_config() {
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let mut rng = StdRng::seed_from_u64(43); // current 3-seed champion seed
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for lr in batch_sample_lrs(&mut rng, 1_000) {
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assert!(
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validate_config(&cfg_with_lr(lr)).is_ok(),
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"validate_config rejected sampled lr={lr}"
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);
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}
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}
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/// Champion LR `0.004` lies strictly inside the φ-band.
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/// Coq: `INV1_CHAMPION_LR = α_φ · φ⁻³`.
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#[test]
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fn test_champion_inside_band() {
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let (lo, hi) = phi_band();
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assert!(lo < champion_lr() && champion_lr() < hi);
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assert!(validate_config(&cfg_with_lr(champion_lr())).is_ok());
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}
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/// Forbidden values from §0 R7 are rejected by `validate_config`.
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/// Coq: `lr_phi_band` REJECT branch.
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#[test]
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fn test_forbidden_lrs_rejected() {
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for &bad in &[1e-5_f64, 1e-3_f64, 1e-2_f64, 0.05_f64, 0.1_f64] {
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// Skip values that happen to be in band by luck — none of these are.
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assert!(
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!(INV1_LR_SAFE_LO..=INV1_LR_SAFE_HI).contains(&bad),
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"test setup error: {bad} is in band"
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);
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assert!(
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validate_config(&cfg_with_lr(bad)).is_err(),
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"validate_config wrongly accepted out-of-band lr={bad}"
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);
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}
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}
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/// Same seed → identical sample sequence (reproducibility for 3-seed claim).
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/// Coq: not a theorem — operational invariant for falsifiability.
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#[test]
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fn test_deterministic_seed_reproducibility() {
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let mut a = StdRng::seed_from_u64(2_026);
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let mut b = StdRng::seed_from_u64(2_026);
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for _ in 0..256 {
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assert_eq!(sample_lr(&mut a).to_bits(), sample_lr(&mut b).to_bits());
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}
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}
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/// Log-uniform mass distribution: each of 5 equal log-bins receives
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/// roughly 20% of samples (within 4σ of the binomial expectation
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/// for n=20_000 → σ ≈ 56 samples per bin → tolerance 0.03).
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/// Coq: not a theorem — empirical distribution check.
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#[test]
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fn test_log_uniform_mass_distribution() {
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let mut rng = StdRng::seed_from_u64(0xA1F);
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const N: usize = 20_000;
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const BINS: usize = 5;
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let lo_ln = INV1_LR_SAFE_LO.ln();
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let width = band_log_width();
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let mut counts = [0_usize; BINS];
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for _ in 0..N {
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let lr = sample_lr(&mut rng);
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let idx = (((lr.ln() - lo_ln) / width) * BINS as f64).floor() as usize;
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counts[idx.min(BINS - 1)] += 1;
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}
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let expected = N as f64 / BINS as f64;
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for (i, &c) in counts.iter().enumerate() {
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let dev = (c as f64 - expected).abs() / expected;
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assert!(
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dev < 0.03,
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"bin {i}: count={c}, deviation {:.4} > 3% (n={N})",
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dev
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);
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}
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}
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/// φ-band is at least 5× narrower in log-space than a blind sweep
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/// over [1e-4, 1e-1] (OpenAI Golf reference). This is the L8 anti-Golf
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/// guarantee — re-asserted at compile time so a future drift to a wider
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/// band will fail CI.
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#[test]
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fn test_anti_blind_sweep_width() {
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let ratio = BLIND_SWEEP_LOG_WIDTH / band_log_width();
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assert!(
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ratio >= 5.0,
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"φ-band should be ≥5× narrower than blind sweep, got {ratio:.2}×"
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);
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}
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/// `lr_around_champion` always returns a value inside the φ-band, even
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/// when σ is huge — clamping is part of the contract.
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/// Coq: `lr_phi_band` REJECT branch is unreachable from sampler output.
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#[test]
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fn test_lr_around_champion_clamped() {
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let mut rng = StdRng::seed_from_u64(0xC1A_BBA);
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for sigma in [0.0_f64, 0.1, 0.5, 1.0, 5.0] {
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for _ in 0..2_000 {
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let lr = lr_around_champion(&mut rng, sigma);
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assert!(
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(INV1_LR_SAFE_LO..=INV1_LR_SAFE_HI).contains(&lr),
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"σ={sigma} produced lr={lr} outside band"
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);
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}
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}
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}
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/// `lr_around_champion` with σ=0 collapses exactly to the champion
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/// (after Box–Muller × 0 = 0). Catches any future regression where
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/// the sigma is accidentally squared or off-by-one.
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/// Coq: degenerate Gaussian → Dirac at champion.
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#[test]
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fn test_lr_around_champion_zero_sigma_is_champion() {
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let mut rng = StdRng::seed_from_u64(7);
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for _ in 0..32 {
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let lr = lr_around_champion(&mut rng, 0.0);
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assert_eq!(
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lr.to_bits(),
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INV1_CHAMPION_LR.to_bits(),
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"σ=0 must return exactly the champion LR"
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);
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}
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}
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}

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