b21d9b671d1732c8d66fc9025e56b5f8489e67c4
5910 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
jgrusewski
|
e07c409950 |
revise(surfer): Phase 0 to CUDA-only per foxhunt architecture (CPU read-only)
Per feedback_cpu_is_read_only + pearl_cold_path_no_exception_to_gpu_drives + feedback_no_cpu_test_fallbacks: NO CPU compute paths even for validation/cold paths. Rewrites Phase 0 as CUDA kernels + Rust orchestration in crates/ml-alpha (reusing build.rs cubin pipeline, mapped-pinned, determinism): floor kernels (TSMOM signal, EWMA vol, portfolio backtest) + validation kernels (CPCV Sharpe, PBO, Deflated Sharpe). CPU only enumerates split masks + reads final gate scalars via mapped-pinned. GPU-oracle tests (no CPU reference). Runs on the local GPU. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
||
|
jgrusewski
|
565511c5f5 |
plan(surfer): Phase 0 — diversified-trend floor + validation harness
CPU-only/Python TDD plan: continuous-contract builder, TSMOM floor (1/3/12mo + inverse-vol + vol-target), validation harness (CPCV/purge/embargo + PBO + Deflated Sharpe + futures cost model), broad-universe data acquisition, and the decisive verdict run (does the floor clear SV gates OOS after costs?). Tasks A-C run immediately on local 4 instruments; D-E need Databento broad-universe history. No ML, no GPU, no cluster. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
||
|
jgrusewski
|
ce13a72ba1 |
docs(surfer): design spec — the surfer over an uncorrelated universe
Strategic pivot from seconds-horizon ES order-book RL (measured structurally unprofitable) to diversified days-to-weeks multi-asset ML trend. ML as bounded deviations from a deterministic diversified-trend floor; gated by CPCV/PBO/ Deflated-Sharpe. Phase 0 (build+validate the floor on Databento micros, CPU-only, no ML, no cluster) is the immediate decisive test. Synthesizes 8-agent omnisearch research (pearl_surfer_universe_build_synthesis). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
||
|
jgrusewski
|
44cbeef321 |
feat(scripts): cross-asset trend/lead-lag harness (6E/ES/NQ/ZN OHLCV)
Per-instrument time-series momentum + diversified trend portfolio + lead-lag, honest IS(2024)/OOS(2025) Sharpe on non-overlapping daily P&L. Verdict on 2y/4-instrument data: diversified trend portfolio IS Sharpe +1.98 (L10) -> OOS -0.50; per-instrument TSMOM sign-flips IS<->OOS; lead-lag ICs <0.11. No robust edge. Conclusion: 4 instruments x 2y is underpowered by 1-2 orders of magnitude for systematic edge discovery -- the bottleneck is data/universe, not model. Real progress needs a broad futures universe + decades, or a less-efficient order-book market (crypto). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
||
|
jgrusewski
|
292147090f |
feat(scripts): lower-frequency directional IC harness (intraday + daily + backtest)
Tests minutes-to-days directional predictability on ES OHLCV-1m where moves dwarf the spread: momentum/reversion IC (Pearson/Spearman/NW-t/OOS) + a non-overlapping daily contrarian backtest (IS/OOS Sharpe). Verdict on 2y ES (2024-25): intraday IC~0; daily mean-reversion IC looks large (-0.44 Spearman @20d) but is overlap-inflated + regime artifact -- honest non-overlapping backtest sign-flips IS<->OOS => no stable edge. Confirms no robustly capturable directional edge on 2y ES across all measured horizons. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
||
|
jgrusewski
|
343e90af54 |
feat(scripts): queue-aware passive-MM fill model (decisive viability test)
FIFO queue priority via price-level episodes: join back of queue, only trades advance, fill when same-side aggressor volume clears the queue. Re-measures markout + OFI-conditioning on ACTUALLY-WON (adversely-biased) fills. Verdict (Q1+Q2 2024 ES): ~40% fill rate; won-fill markout -0.50..-0.55t (winner's curse vs optimistic -0.40t); naive AND OFI-conditioned passive MM both NEGATIVE (-$1..-$2/fill). The optimistic Q2 OFI tilt was a win-every-queue artifact. Combined with the crossing result: no capturable seconds-horizon ES edge for a non-colocated participant. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
||
|
jgrusewski
|
f6745400ef |
feat(scripts): passive market-making markout/adverse-selection harness
Measures passive-MM economics on clean ES MBP-10: half-spread earned vs adverse-selection markout at horizons, plus OFI-conditioned selective quoting. Verdict on 2024 ES: adverse selection ~0.4 tick eats ~80% of the 0.5-tick half-spread => naive passive MM is break-even (optimistic, win-every-queue; realistically negative). OFI-conditioned selective quoting shows a consistent edge in Q2 (+$0.5/fill) but not Q1 => promising but unconfirmed; decisive next test is a realistic queue/fill model. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
||
|
jgrusewski
|
7b33533bc8 |
feat(scripts): OFI information-coefficient signal-validation harness
Measures best-level Order-Flow-Imbalance (Cont-Kukanov-Stoikov) predictive edge on clean ES MBP-10 vs forward returns: contemporaneous R², forward IC (Pearson/Spearman), sign-accuracy, Newey-West t-stat across horizons, and a CROSSING verdict (predicted move in ticks vs the 1-tick round-trip cost). No training/RL. Verdict on clean 2024 ES: OFI fwd IC tiny (~0.02, Q2 NW-t 3.7), predicted moves 0.01-0.06 ticks at 1-10s << 1-tick crossing cost (~20-100x gap) => spread-crossing directional strategy is structurally unprofitable. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
||
|
jgrusewski
|
fa3f723983 |
docs: Phase A verdict — RA-G1 PASS, RA-G3 starvation-limited on clean data; proceed to D2
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
||
|
jgrusewski
|
6df3284d0d |
fix(data): MBP-10 decoder corrupted the inside quote (level 0)
Both parse_mbp10_file and parse_mbp10_streaming wrote the single MBP-10 update event's (price,size) into levels[0] via update_level(0,...) and then copied the authoritative book from mbp10.levels[1..] — starting at index 1, so the corrupt L0 was never overwritten with the real mbp10.levels[0]. Result on real cluster data (ES.FUT 2025-Q1 front-month, 2M records): 14.9% crossed books, 40% wide-L0 (>5pt) spikes, vs the raw inside quote which is pristine (0.016% crossed, 0% wide, 0.25pt median). Every mid/microprice/spread/OFI-L0 feature, the mid-based MTM reward, and the LOB-sim fill reference read this phantom L0. Extract the level-copy into a tested helper apply_mbp10_record() that: - copies the full mbp10.levels[0..max] canonical post-update book (including L0, the inside quote); - preserves trade_count on Trade-action records (a LIVE encoder feature [17]=log1p(trade_count) + the inter-snapshot trade delta in the ml-alpha/ml-features loaders) — naively dropping update_level(0) would have silently zeroed it. Adds RED-verified unit tests for no-crossed-L0 and trade_count semantics. cargo test -p data --lib: 377 passed. Sidecars (.predecoded.bin) are mtime/size-keyed and will NOT auto- invalidate on this parser change — they must be regenerated separately (local + PVC). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
||
|
jgrusewski
|
31f858b5ea |
docs(superpowers): edge investigation decision record + F4-gating/reward-alignment specs & plans
Session 2026-06-05: investigation-first falsification gated the F4 oracle build (7-14 days) and walked back through the reward/edge question to a code-verified root cause — the MBP-10 decoder corrupts the inside quote (dbn_parser.rs:903 'for lvl in 1..max_lvl' never restores levels[0]), contaminating mid/feature/reward/fill locally and on the cluster PVC. - notes/2026-06-05-edge-investigation-decision-record.md: full 8-verdict arc (incl. 2 self-retractions) + next-session plan (confirm on PVC, fix parser, regenerate sidecars, re-audit on clean data). - specs: f4-oracle-pretraining (GATED), reward-pnl-alignment-restoration (superseded by the data-quality finding), bellman-target-foundation-reshape. - plans: reward-pnl-alignment-restoration-implementation, f2-q-centered-distill. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
||
|
jgrusewski
|
e57b076577 |
feat(scripts): reward-pnl alignment measurement harness (RA-G3 gate)
Computes Pearson(rewards.sum, trading.realized_pnl_usd_delta) + sign-agreement from a diag.jsonl. Exit 0 if Pearson >= 0.70 (RA-G3), 1 below, 2 on bad input. Reproduces the baseline 0.2775 / sign 0.655 measurement. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
||
|
jgrusewski
|
d8447475c9 |
feat(ml-alpha): Phase A — surfer-scaffold force-pin (slot 824 + kernel gate + env flag + diag)
Adds ISV slot 824 (RL_SURFER_SCAFFOLD_FORCE_PIN_INDEX) and a matching kernel early-return in rl_surfer_scaffold_controller.cu so that when FOXHUNT_PIN_SURFER_SCAFFOLD=1 is set, the controller leaves slot 753 at its 0.0 pure-pnl bootstrap instead of overwriting it every step. Without the pin, the 0.0 bootstrap was cosmetic — the unconditional write re-enabled all four Phase-5 non-potential shaping terms each step, giving Pearson(reward,pnl)=0.28 vs the 0.70 gate. Pin=OFF leaves behaviour fully unchanged (new branch only fires when slot 824 > 0.5). - isv_slots.rs: slot 824 constant + RL_SLOTS_END 824→825 + test - rl_surfer_scaffold_controller.cu: #define + early-return guard - integrated.rs: isv_constants 275→276 + env-gated bootstrap entry - eval_diag_emission.rs: rewards.surfer_scaffold_force_pin diag field + EXPECTED_LEAVES 746→747 Build: SQLX_OFFLINE=true cargo build -p ml-alpha --profile=dev-release OK Tests: 69 passed / 0 failed (force_pin_slot_allocated_below_end + all existing) Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
||
|
jgrusewski
|
7376b1c670 |
feat(ml-alpha): Phase 7b F5 engagement — bootstrap RL_F5_STATE_MASK_ENABLED to 1.0
Per Tier 1.5 mid-smoke verification (FOXHUNT_BAND_ENABLED=1, seed 42,
b=128, 2000+500): F2+F5+Option A combined is best-of-session on every
metric vs Phase 5 baseline AND F2-alone baseline.
## Empirical evidence (Tier 1.5, /tmp/foxhunt-phase7b-f5-tier15)
| Metric | Phase 5 | F2 alone | F2+F5+OptA |
|---------------------|-------------|-------------|-------------|
| eval pnl | -$444,225 | -$494,887 | -$415,237 |
| win_rate | 0.371 | 0.355 | 0.380 |
| sharpe_ann | -7.20 | -8.49 | -5.31 |
| action_entropy@1999 | 0.215 | 0.188 | 0.445 |
| profit_factor | 0.534 | 0.470 | 0.599 |
| max_drawdown_usd | (n/a) | (n/a) | $436k |
eval pnl improved $29k over Phase 5 and $80k over F2-alone.
action_entropy 2× higher than either baseline.
## F5 mechanism trajectory (verified working at scale)
step hold_frac_flat frac_batches_flat entropy
5 1.0 0.47 1.37 (session_risk tripped)
50 1.0 0.59 0.46 (still locked)
250 0.0 0.0 0.69 (session recovered; F5 active)
500 0.0 ~0.0 0.70
1000 0.0 ~0.0 0.54
1999 0.0 ~0.0 0.45
session_risk_check (hard safety, slot 540) correctly tripped early when
F5-forced opens lost money cold-start; by step ~250 it recovered and
F5 engaged. Net: most batches stay IN POSITION (F5 forces commitment
when flat), which is exactly the surfer→trend trade-off F5 was designed
to enable.
## F2 mechanism becomes ACTIVE under F5 forcing
f2_hinge_zero_rate dropped from 1.0 (F2-alone) to 0.909 — meaning ~9%
of action slots now show Q-advantage. F2 identified FlatFromShort as
modal target (target_argmax=4). The forced opens give Q outcomes to
discriminate against; F2 then captures the signal that Hold/Open were
mathematically silent without F5.
## What this commit does
Flips `RL_F5_STATE_MASK_ENABLED_INDEX` bootstrap from 0.0 → 1.0 so the
F5 state-conditional action mask + Option A gate-aware patches engage
by default. Flipping back to 0.0 (or any value ≤ 0.5) reverts to F2-only
behavior bit-equal with commit
|
||
|
jgrusewski
|
e82049c779 |
feat(ml-alpha): Phase 7b F5 Option A — gate-aware Hold suppression for confidence + FRD gates
When F5 state-conditional action availability mask (slot 823) is engaged AND
the position is flat, F5 has deliberately forced the agent into an opening
action by masking Hold (and other state-invalid actions) in `pi_logits`
pre-sample. Two downstream gates — `rl_confidence_gate` (slot 512..) and
`rl_frd_gate` (slot 516..) — silently overrode the sampled action back to
Hold at the same flat-state, neutralizing F5's surfer→trend choice-set
forcing and preventing F5-G1 (`hold_frac_flat == 0` from flat) from being
achieved at the agent layer.
Both kernels patched with the identical interop pattern:
const bool f5_engaged = (isv[RL_F5_STATE_MASK_ENABLED_INDEX] > 0.5f);
if (f5_engaged) skip the Hold override;
The existing `if (position_lots != 0) return;` early-return in both kernels
already restricts the override site to flat batches, so the check on the F5
master gate alone is sufficient — no new position read needed. When F5 is
disabled (slot 823 == 0.0, the production default) the original code path
runs verbatim, preserving Phase 7a bit-equality.
Scope (per Phase 7b follow-up):
* `rl_confidence_gate.cu` — Hold-override at `conf < threshold` gated on
`!f5_engaged`; fired-count increments only when the override actually fires.
* `rl_frd_gate.cu` — short-circuits before entry-quality computation when
`f5_engaged`; the long/short Hold-override branches are skipped entirely.
NOT touched (per Option A scope constraint):
* `rl_session_risk_check.cu` — hard DD-limit safety. When F5-driven losses
trip the session PnL EMA breaker, it correctly overrides opens-from-flat
back to Hold; this is the documented "pro trader stops trading when down
their limit" semantics and must persist regardless of F5 state.
* `rl_min_hold_check.cu` — only fires for in-position batches; not on the
F5-relevant flat-state path.
Verification (RTX 3050, `test_data/futures-baseline-mid/`):
* `cargo build --release --example alpha_rl_train -p ml-alpha` — clean.
* `./scripts/determinism-check.sh --quick` (defaults, F5 OFF) — DETERMINISTIC
across 200 train rows: same-seed bit-equal at slot 823 = 0.0.
* `FOXHUNT_BAND_ENABLED=1 ./scripts/determinism-check.sh --quick` (F5 OFF) —
DETERMINISTIC across 200 train rows.
* `phase_5_invariants + band_invariants + multi_head_policy_invariants +
eval_diag_emission --ignored` — 33/33 PASS (3 + 11 + 18 + 1).
* F5 ON 50-step smoke (slot 823 temporarily set to 1.0 then reverted before
commit): hold_frac_flat = 0.0 at steps 0–3 (F5 mask + Option A patches
successfully forcing opens from flat — modal_action_id ∈ {0, 5, 4}, none
Hold). At step 4 onward hold_frac_flat → 1.0 due to `rl_session_risk_check`
tripping after cumulative losses (-$292k by step 49 at b=128 b_size) drop
the session PnL EMA below the bootstrap limit (-50.0 at slot 540). This is
the documented hard-safety override (out of scope per task brief) — the
first 3–4 steps confirm the Option A mechanism works at both gates before
the safety fires.
* No NaN; training stable.
Bootstrap of slot 823 reverted to 0.0 (OFF) before committing.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
|
||
|
jgrusewski
|
9ea7692abd |
feat(ml-alpha): Phase 7b F5 — state-conditional action availability mask
Adds the no-op-set / direction / trail-at-cap action availability mask
specified in §3.5 of docs/superpowers/specs/2026-06-04-bellman-target-foundation-reshape.md.
## What lands
* New kernel `cuda/rl_state_action_mask.cu` (~115 LOC) modelled on
`rl_band_mask.cu`'s lattice — Grid=(B), Block=(1,1,1), single thread
per block, ISV-gated, reads `pos_state[b*pos_bytes+0..4]` for
`position_lots` and the existing per-batch per-unit trail buffers
(`unit_trail_distance`, `unit_initial_r`, `unit_active`).
* New ISV slot `RL_F5_STATE_MASK_ENABLED_INDEX = 823` (binary master
gate; bootstrap 0.0 = OFF; preserves Phase 7a `43e7b6383`
bit-equality). `RL_SLOTS_END` bumped 823 → 824.
* Trainer integration: `launch_rl_state_action_mask` public wrapper +
inline call sites at the two policy-sampling paths
(`step_with_lobsim` and `step_with_lobsim_gpu_body`), inserted BEFORE
`rl_pi_action_kernel` so the sampler sees the masked logits. Both
sites sit inside the prefill graph capture (device-side master gate
preserves bit-equality across off↔on flips). `isv_constants` array
size bumped 274 → 275.
* `build.rs` registers the new cubin.
## Mask semantics (when slot 823 > 0.5)
* `position_lots == 0` (flat) → mask {Hold=2, FlatFromLong=3,
FlatFromShort=4, TrailTighten=7, TrailLoosen=8, HalfFlatLong=9,
HalfFlatShort=10}. Surviving support: {ShortLarge=0, ShortSmall=1,
LongSmall=5, LongLarge=6} — agent is FORCED to open.
* `position_lots > 0` (long) → mask all short-side actions
{ShortLarge=0, ShortSmall=1, FlatFromShort=4, HalfFlatShort=10}.
Same-side opens (5/6) remain available; pyramid resolution stays in
`actions_to_market_targets.cu`.
* `position_lots < 0` (short) → symmetric.
* Any active unit at trail-cap (`trail_distance ≥ unit_initial_r *
RL_TRAIL_MAX_INITIAL_R_RATIO * (1 − 1e-3)`) → additionally mask
TrailLoosen (mq2pc-specific gate per spec §3.5 trail-at-cap branch).
## Composition with F2 (Q-distill hinged advantage)
F2 computes `π_target` from unmasked E_Q; F5 sets `pi_logits[masked] =
−INFINITY` so `softmax(pi_logits)` has EXACTLY zero mass on masked
actions (F5-G1 design requirement). The distill gradient
`(π_θ − π_target)` evaluates to `(0 − π_target_masked)` at masked
actions, which naturally drives the target off those actions —
gradient consistency without re-masking inside `rl_q_pi_distill_grad`.
## Action enum (verified against actions_to_market_targets.cu and
crates/ml-alpha/src/rl/common.rs)
| id | name | masked from flat | masked from long | masked from short |
|----|----------------|------------------|------------------|-------------------|
| 0 | ShortLarge | | ✓ | |
| 1 | ShortSmall | | ✓ | |
| 2 | Hold | ✓ | | |
| 3 | FlatFromLong | ✓ | | ✓ |
| 4 | FlatFromShort | ✓ | ✓ | |
| 5 | LongSmall | | | ✓ |
| 6 | LongLarge | | | ✓ |
| 7 | TrailTighten | ✓ | | |
| 8 | TrailLoosen | ✓ | (cap-only) | (cap-only) |
| 9 | HalfFlatLong | ✓ | | ✓ |
| 10 | HalfFlatShort | ✓ | ✓ | |
(There are NO separate PyramidLong/PyramidShort actions in foxhunt;
pyramid logic resolves inside `actions_to_market_targets.cu` when
same-side opens fire from an existing position.)
## Surfer-principle trade-off (acknowledged per spec §3.5 + §4.1.4)
F5 destroys patience-while-waiting-for-setup by construction. F2
preserves the surfer principle mathematically (Open mass = 0 when
E_Q(Open) ≤ baseline); F5 sacrifices it for choice-set enforcement.
Bootstrap 0.0 keeps F5 OFF until F2 alone fails the Tier 1.5 / Tier 2
verdict AND the operator explicitly accepts the trend-follower
regression. Reversible at runtime via ISV re-seed.
## Verification
* `cargo build --release --example alpha_rl_train -p ml-alpha` clean.
* Determinism (band off, F5 off / band on, F5 off / F5 ON via
temporary bootstrap=1.0): all three PASS — `determinism-check.sh
--quick` reports byte-equal `eval_summary.json` and
`alpha_rl_train_summary.json` plus checksum-equal diag rows.
* Invariants (band_invariants 11/11, eval_diag_emission 1/1,
multi_head_policy_invariants 18/18, phase_5_invariants 3/3): 33/33
PASS.
## STOP-on-surprise — F5 mechanism vs downstream gate-stack interaction
50-step smoke with F5 ON (bootstrap=1.0, then reverted) surfaced an
EXPECTED interaction documented in spec §3.5 expected-failure-mode #5:
* F5 mask itself is mechanically correct — `pi_logits[masked] = −INF`,
softmax mass is zero, `rl_pi_action_kernel` samples only from
{0,1,5,6} from flat.
* BUT the downstream gates that run AFTER `rl_pi_action_kernel` —
`rl_confidence_gate` (lines 67-74 read `pos_state`, override opens
from flat to Hold when C51 confidence is low), `rl_frd_gate`,
`rl_session_risk_check`, `rl_min_hold_check` — re-introduce Hold
into the executed action histogram. F5-G1 (`hold_frac_flat == 0`)
is therefore NOT achieved by this commit alone.
The F5 kernel does what the spec asks; the gate-stack interaction is
the orthogonal wiring the spec called out as out-of-scope for F5
correctness. A follow-up plan should either suppress those gates'
Hold override when `isv[823] > 0.5 AND position_lots == 0`, OR
re-launch the F5 mask AFTER the gate stack (single extra device-side
kernel invocation). The mask kernel and ISV slot land here so the
follow-up is purely a wiring task. Per the STOP-on-unexpected-finding
discipline (feedback_investigation_first_falsification_methodology),
no further fix is applied in this dispatch.
## Files
* `crates/ml-alpha/cuda/rl_state_action_mask.cu` (new, ~115 LOC)
* `crates/ml-alpha/build.rs` (kernel registration)
* `crates/ml-alpha/src/rl/isv_slots.rs` (slot 823 + RL_SLOTS_END bump)
* `crates/ml-alpha/src/trainer/integrated.rs` (cubin include, struct
fields, ctor load + struct init, `launch_rl_state_action_mask`
wrapper, ISV bootstrap entry + array size bump 274→275, two inline
call sites at `step_with_lobsim` and `step_with_lobsim_gpu_body`)
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
|
||
|
jgrusewski
|
43e7b6383b |
feat(ml-alpha): Phase 7a F2 — Q-centered hinged-advantage distill target wired
rl_q_pi_distill_grad.cu Step 2 modified: when RL_F2_DISTILL_CENTERED_ENABLED_INDEX
(slot 817) > 0.5, π_target uses Q-centered hinged advantage:
π_target(a) ∝ softmax( max(0, E_Q(a) − baseline) / τ )
where baseline = max E_Q over no-op set selected by
RL_F2_DISTILL_NOOP_SET_MODE_INDEX (slot 818):
- mode 0 (default, slot 818 = 0.0): {Hold=2, TrailTighten=7, TrailLoosen=8}
- mode 1 (ablation, slot 818 = 1.0): {Hold=2} only
When slot 817 ≤ 0.5, the legacy softmax(E_Q/τ) path runs unchanged
(bit-equal with HEAD
|
||
|
jgrusewski
|
f788da862a |
feat(ml-alpha): Phase 7a Task 1.5 — comprehensive F2 diagnostic emissions (13 fields)
Adds instrumentation BEFORE the F2 hinge modification (Task 3) per
`feedback_investigation_first_falsification_methodology` "measure first,
change code second." Without these counters, the F2 cluster verdict
cannot distinguish "mechanism worked AND surfer preserved AND eval
improved" from "mechanism worked BUT surfer collapsed" — three
independent attribution signals collapse into one ambiguous outcome.
## ISV slots 819-822 (RL_SLOTS_END 819 → 823)
Four kernel-reduced F2 mechanism counters populated by
rl_q_pi_distill_grad.cu's end-of-kernel single-thread reduction block
(one block per batch, thread a==0 writes its own [batch] index — NO
atomicAdd, no race). Host reduces to mean/mode at diag emit.
- RL_F2_DIAG_BASELINE_MEAN_INDEX (819): mean of max E_Q over no-op set
- RL_F2_DIAG_ADV_MAX_MEAN_INDEX (820): mean of max hinged advantage
- RL_F2_DIAG_HINGE_ZERO_RATE_INDEX (821): fraction of (b,a) slots zeroed
- RL_F2_DIAG_TARGET_ARGMAX_INDEX (822): modal π_target action id
## 13 new diag fields under existing top-level keys
Surfer (3): trading.frac_batches_{flat,long,short} — host reduce on
position_lots; fleet-fraction denominators per
`pearl_fleet_fraction_not_aggregate`.
F2-G5 direct measurement (2): policy_diagnostic.hold_frac_flat,
open_action_mass_flat. F2-G5 (surfer-patience preservation gate, Hold%
when flat ∈ [30%, 85%]) is NOW LOCALLY MEASURABLE — closes the
measurement gap from plan v1.
Degenerate-attractor monitoring (4): policy_diagnostic.max_action_share
(detects single-action collapse), modal_action_id (which attractor),
noop_action_mass_{total,max} (no-op concentration).
F2 mechanism (4): policy_diagnostic.f2_baseline_mean,
f2_advantage_max_mean, f2_hinge_zero_rate, f2_target_argmax_action.
f2_target_argmax_action ≠ modal_action_id during surfer-adapt phase
indicates F2 is reshaping the gradient toward Open.
## Kernel changes
rl_q_pi_distill_grad.cu signature extended with 4 new scratch buffer
args. Reduction logic in the `a == 0` block computes per-batch values
and writes single-thread to [batch] index — no atomicAdd, no race.
Existing path (legacy distill target) unchanged when
RL_F2_DISTILL_CENTERED_ENABLED_INDEX (slot 817) is OFF.
## EXPECTED_LEAVES 712 → 746
13 new Phase 7a fields + 8 schema-drift leaves from upstream commits
(not re-synced in the prior B-11-β ledger between 671→672 and Phase 5
|
||
|
jgrusewski
|
66a6db89b3 |
feat(ml-alpha): Phase 7a F2 — allocate ISV slots 817-818 for Q-centered distill target
Two new slots:
- RL_F2_DISTILL_CENTERED_ENABLED_INDEX (817, bootstrap 1.0): master gate
for the F2 hinge in rl_q_pi_distill_grad.cu. Flip to 0.0 to fall back to
the legacy softmax(E_Q/τ) target (bit-equal with HEAD
|
||
|
jgrusewski
|
0463e44e0c |
feat(ml-alpha): Phase 5 — trail-max + MTM reward + entropy formula fix
Three coupled structural fixes for the TrailLoosen-pathology identified
by the Phase 4-A3 ultrathink investigation. Single-seed smoke
(FOXHUNT_BAND_ENABLED=1, seed 42, b=128): eval pnl improved from
-$794k (4-A3) to -$444k = +$350k loss reduction (44% less negative).
Win rate 37.1% (was 31.7%).
## Fix 1: Trail-max ceiling (new ISV slot 814)
RL_TRAIL_MAX_INITIAL_R_RATIO_INDEX bootstrap 4.0. In rl_trail_mutate.cu,
clamp unit_trail_distance ≤ initial_trail × 4.0. Without this the
TrailLoosen action (× 1.1 per fire) grew distances to 2959 ticks
(~$37k risk per position) per the Phase 4-A3 diagnostic.
Test: trail_max_clamped_by_initial_r_ratio — verified that after 30
TrailLoosen fires, trail clamped at 4.0× (uncapped would have been
17.4×, a 4.4× reduction).
Empirical effect: TrailLoosen at smoke final = 0/128 batches (was
49/128 = 38% in Phase 4-A3). The arbitrage is mechanically eliminated.
## Fix 2: Mark-to-market reward (new ISV slots 815/816)
RL_MTM_REWARD_ENABLED_INDEX (bootstrap 1.0) + RL_MTM_REWARD_WEIGHT_INDEX
(bootstrap 1.0). New Phase 1.6 in rl_fused_reward_pipeline.cu:
r += w_mtm × (unrealized_now − unrealized_prev)
Per-step reward proportional to total wealth delta (realized +
unrealized). Penalizes holding losers in real-time. Total reward over
a complete trade is identical to legacy (unrealized → 0 at close);
only the temporal distribution changes — with γ < 1, held losers are
visibly painful in the discounted return, closing actions get learned
properly.
Test: mtm_reward_disabled_matches_legacy — verified A/B gate cleanly
disables to legacy realized-only path. unrealized_pnl read from
pos.vwap_entry + current mid via standard accounting.
Empirical effect: FlatFromLong action appears in policy (was 0 in
4-A3), win rate up 5.4pp.
## Fix 3: Entropy gradient formula (correctness)
rl_q_pi_distill_grad.cu:131 had spurious +1.0f:
BEFORE: grad_entropy = -alpha × pi_a × (log_pi_a + 1.0f + s_entropy)
AFTER: grad_entropy = -alpha × pi_a × (log_pi_a + s_entropy)
True ∂(-H)/∂logit_a = π(a)·(log π(a) + H) per textbook softmax-entropy
gradient. Sign was correct; magnitude was 3× too aggressive on dominant
actions and 2-3× too weak on low-prob actions.
Test: entropy_gradient_matches_analytical — verified across all 11
actions with H=1.4931, kernel matches analytical formula within 1e-5.
## Verification
* 3/3 phase_5_invariants tests PASS
* 11/11 band_invariants regression tests PASS
* FOXHUNT_USE_MULTI_HEAD_POLICY=0 ./scripts/determinism-check.sh
--quick: exit 0 (200 rows bit-equal)
* FOXHUNT_BAND_ENABLED=1 ./scripts/determinism-check.sh --quick:
exit 0 (200 rows bit-equal)
* Pre-commit hook: 0 atomicAdd, 0 raw memcpy_htod/dtoh
## Smoke trajectory (FOXHUNT_BAND_ENABLED=1, seed 42, b=128, 2000+500)
step entropy top_3_action_hist
0 0.000 [128, 0, 0] (init)
100 0.785 [Hold=117, Long-=3, Short-=5, TrailLoosen=1]
500 0.489 [Hold=122, Long-=1, FlatLong=2, TrailLoosen=0]
1000 0.359 [Hold=123, FlatLong=5, TrailLoosen=0]
1500 0.268 [Hold=124, FlatLong=3, TrailLoosen=1]
1999 0.215 [Hold=125, FlatLong=3, TrailLoosen=0]
eval (5000 steps frozen policy):
total_pnl_usd: -$444,225 (best of session, was -$794k in 4-A3)
win_rate: 0.371 (best of session, was 0.317)
n_trades: 197
profit_factor: 0.534
max_drawdown_usd: $462,212
sharpe_ann: -7.20
## Falsification gates
* G_mechanism (no NaN, exit 0): PASS
* G_no_regression (pnl ≥ -$5M): PASS by wide margin (-$444k)
* G_trail_bounded: PASS (0 TrailLoosen fires at final, ceiling working)
* G_action_diversity (entropy ≥ 1.0): FAIL (0.22 — new pure-Hold
conservatism failure mode emerges; the policy learns "don't open
trades" as the safest path with all the constraints in place)
## Analysis of the new failure mode
The Phase 5 fixes worked exactly as designed: trail-max eliminated
the runaway risk mechanism, MTM made held losers painful, entropy
formula now matches theory. But with all three counter-pressures
applied, the policy's safest equilibrium is "Hold + occasionally
close." It's a strictly BETTER failure than 4-A3 (less negative pnl,
less risk-taking, cleaner action discipline), but still degenerate.
This is the conservation point: with TrailLoosen blocked, MTM
penalizing held losers, and quadratic cost on trades, the policy
discovers that doing NOTHING is approximately break-even. Genuinely
profitable opening is harder to learn than this no-trade baseline,
and Q-distill's distillation pressure plus SAC α saturation can't
push the policy off it.
Next investigation: WHY can't the policy discover profitable opens?
Either (a) the encoder isn't seeing actionable alpha signals, or (b)
the gradient flow to open-actions is too weak relative to the
counter-pressure stack. This is a separate spec.
## Linked
* Phase 4-A3:
|
||
|
jgrusewski
|
f593b1e617 |
feat(infra): plumb FOXHUNT_BAND_ENABLED through alpha-rl template
Mirror of the FOXHUNT_USE_MULTI_HEAD_POLICY pattern ( |
||
|
jgrusewski
|
65c328d3f1 |
fix(ml-alpha): Phase 4-A3 — band position-zero exception (opens-from-flat allowed)
Davis-Norman (1990) is a theorem about MANAGING existing hedge
positions; it tells the agent NOT to micro-adjust within the band. It
says nothing about whether to open from flat.
The `±|tanh|` activation in rl_band_head_forward.cu guarantees
`b_l ≤ 0 ≤ b_u` (the Davis-Norman invariant). Combined with the foxhunt
invariant that agents start FLAT (position=0), every flat-batch was
being masked to Hold — agents never opened, positions never moved, the
sigmoid surrogate on (b_l, b_u) sat deep-in-band where its derivative
≈ 0, and the band loss had no gradient signal.
Verified empirically at
|
||
|
jgrusewski
|
1c23ff368a |
feat(ml-alpha): Phase 4-A2 — band exploration bypass (slot 813)
Adds RL_BAND_MAX_MASK_FRAC_INDEX (bootstrap 0.85) and modifies rl_band_mask.cu to never mask the first (1 - max_mask) · B batches per step. Resolves the dead-signal trap from Phase 4-B at |
||
|
jgrusewski
|
552d91bf45 |
feat(ml-alpha): Tier 3 Phase 4-B — Band turnover controller + backward chain wiring
Closes Phase 4-A's open loop by making the no-transaction band LEARN its width. Two coupled mechanisms wired in: 1. Adaptive turnover-target controller — single-thread CUDA kernel (rl_band_turnover_controller.cu) reads per-step `frac_not_masked` and adjusts the turnover target via asymmetric Schulman-bounded adapter: tighten (×0.97/step) above 0.60 threshold, loosen (×1.05/step) below 0.20. Asymmetric LOOSEN rate is faster per `pearl_dead_signal_resurrection_discipline`. First-observation bootstrap on slot 809 with dedicated boot-done sentinel slot 810. 2. Backward chain wiring — rl_band_head_backward.cu propagates `grad_band_per_b [B × 2]` through the asymmetric ±|tanh|·N_max activation and linear projection into per-batch weight/bias scratch plus `grad_h_t [B × HIDDEN_DIM]` (OVERWRITE). Trainer reduces via `reduce_axis0` and folds into the encoder grad combiner alongside π/V/FRD/outcome heads using the existing `grad_h_accumulate_scaled` pattern. Band-weight Adam steps share LR with π (RL_LR_PI_INDEX) — same plateau dynamics as policy. Plus a GPU reducer rl_band_frac_aggregate.cu (single-block tree-reduce over batch → writes to slot 812) and a host-side launch sequence in step_with_lobsim_gpu_body that runs frac_aggregate → controller → turnover_loss → backward outside graph capture, gated by RL_BAND_ENABLED_INDEX > 0.5 so Phase 3D bit-equality is preserved when the master gate is OFF. ISV slots added (809-812): turnover_ema, controller_boot_done, turnover_target_adaptive, frac_not_masked_observed. The turnover loss kernel now reads slot 811 (controller output) instead of the static slot 803. Bootstrap target 0.05 matches the Phase 4-A static default so first-step behavior is identical. Tests: 4 new band_invariants tests cover the controller bootstrap, the escalate-on-over-trading path, the loosen-on-saturation path, and the backward chain producing non-zero `grad_h_t` from a turnover/target mismatch. All 9 band tests + 18 multi_head_policy regression tests pass. Determinism: `determinism-check.sh --quick` exits 0 for the three relevant configurations (band off, band on, band + multi-head on). The Schulman controllers are deterministic by construction (no PRNG); backward kernels are sole-writer per (batch, slot) so reduce_axis0 delivers bit-equal weight grads across replays. Spec: docs/superpowers/specs/2026-06-03-no-transaction-band-architecture.md §3.1 Option (c), §3.3 (backward chain), §3.4 (loss weight controller), §5 (diag emission), §9.1 Mitigation 3 (resurrection discipline). Pearls applied: * pearl_bootstrap_must_respect_clamp_range — bootstrap 0.05 ∈ [0.01, 0.20] * pearl_dead_signal_resurrection_discipline — asymmetric tighten/loosen rates * pearl_welford_trade_count_is_step_not_trade — bootstrap-done sentinel slot * pearl_determinism_achieved — single-thread controller, deterministic reducers Single-seed local smoke (b=128, 2000+500 steps, FOXHUNT_BAND_ENABLED=1) runs end-to-end without NaN. The band saturates to `frac_masked = 1.0` because position state stays at 0 throughout — the sigmoid surrogate gradient is zero deep inside the band, so the band's upper boundary cannot be pulled toward 0 even though the controller drives the adaptive target to its MAX (0.20). Spec §9.1 Mitigation 2 (`RL_BAND_MAX_MASK_FRAC_INDEX` exploration-slot bypass in rl_band_mask.cu) was declared but not shipped in Phase 4-A; it is the structural fix for this chicken-and-egg trap. Phase 4-B mechanism itself is verified correct via the four new tests; the saturation is an architectural-grafting gap surfaced for Phase 4-A2 follow-up rather than a Phase 4-B implementation defect. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
||
|
jgrusewski
|
e41a732081 |
feat(ml-alpha): Phase 4-A — No-transaction-band foundation (ISV slot 799 gate)
Foundation of the no-transaction-band architectural turnover regulator
described in
docs/superpowers/specs/2026-06-03-no-transaction-band-architecture.md.
Davis-Norman (1990) / Imaki-Imajo-Ito (2021, arXiv:2103.01775) — when the
current position lies inside a learned band [b_l, b_u], the architectural
default is "do nothing", complementing Phase 3D's reward-side fixes which
the literature (Goodhart-Skalse 2024) bounds the effectiveness of.
Scope: ISV slots 799-808 + BandHead forward + ±|tanh|·N_max_eff
activation + rl_band_mask action override + rl_band_turnover_loss
(Option b, fixed-target) + 5 GPU-oracle invariants + diag emission.
Master gate `RL_BAND_ENABLED_INDEX` (slot 799) bootstraps to 0.0 (OFF)
so the foundation preserves bit-equality with Phase 3D `bd811a774` until
operator opt-in via `FOXHUNT_BAND_ENABLED=1`.
Adaptive controller, encoder backward chain, and cluster verification
are Phase 4-B / 4-C, not in scope here.
ISV slots (799-808, bumps RL_SLOTS_END to 809):
799 RL_BAND_ENABLED_INDEX (master gate, bootstrap 0.0)
800 RL_BAND_LOWER_INIT_INDEX (b_l init, -0.5 in tanh space)
801 RL_BAND_UPPER_INIT_INDEX (b_u init, +0.5 in tanh space)
802 RL_BAND_LOSS_WEIGHT_INDEX (λ_turnover, 0.01)
803 RL_BAND_TURNOVER_TARGET_INDEX (target frac unmasked, 0.05)
804 RL_BAND_GRAD_SHARPNESS_INDEX (sigmoid surrogate, 4.0)
805 RL_BAND_FLAT_RECENTER_RATE_INDEX (reserved for 4-B controller)
806 RL_BAND_WIDTH_MIN_INDEX (collapse detection, 0.1)
807 RL_BAND_WIDTH_MAX_INDEX (saturation detection, 1.8)
808 RL_BAND_DIAG_LAUNCH_EVERY_INDEX (diag cadence, 1.0)
CUDA kernels (3 new):
rl_band_head_forward.cu — 2-stage forward: linear projection
(tree-reduce over HIDDEN_DIM, matches
ppo_policy_logits_fwd shape) + asymmetric
±|tanh|·N_max_eff activation enforcing
b_l ≤ 0 ≤ b_u (Davis-Norman invariant).
rl_band_mask.cu — overrides actions[b]→Hold when
position_lots[b] ∈ [b_l, b_u]. Master-
gated at slot 799; no atomicAdd; runs
OUTSIDE graph capture per spec §9.5.
rl_band_turnover_loss.cu — Option (b) turnover regularizer with
sigmoid surrogate. Per-batch loss +
per-batch grad on (b_l, b_u). Phase 4-A
wires kernel + test; full encoder grad
fold is Phase 4-B.
Rust glue:
crates/ml-alpha/src/rl/band_head.rs — BandHead struct, forward,
launch_mask, launch_turnover_loss.
Xavier-0.01 init under
scoped_init_seed(seed+0xBA_5EED).
trainer/integrated.rs — BandHead field + construction
(bias init = atanh(0.5)) +
ISV bootstrap row + FOXHUNT_BAND_
ENABLED override + forward call
at both step_with_lobsim and
step_with_lobsim_gpu_body sites
+ mask launch BEFORE confidence
gate + per-step band aggregate
diag (lower/upper/width means,
frac_in_band, frac_masked,
collapse_warning).
Tests (5 GPU-oracle invariants, all PASS):
band_activation_clamps_correctly — b_l ≤ 0 ≤ b_u, |·| ≤ N_max_eff
band_mask_forces_hold_when_in_band — pos 0 ∈ [-4,+4] → action becomes Hold
band_mask_passes_through_when_out_of_band — pos 5 ∉ [-1,+1] → action unchanged
band_turnover_loss_correct — loss + grad match analytical form
band_disabled_means_no_mask — slot 799 = 0.0 → mask no-op
Verification:
cargo build --release --example alpha_rl_train: exit 0
cargo test band_invariants --release -- --ignored: 5/5 PASS
cargo test multi_head_policy_invariants -- --ignored: 18/18 PASS (regression)
determinism-check.sh --quick (band OFF): exit 0
FOXHUNT_BAND_ENABLED=1 determinism-check.sh --quick: exit 0
FOXHUNT_USE_MULTI_HEAD_POLICY=1 determinism-check.sh --quick: exit 0
FOXHUNT_USE_MULTI_HEAD_POLICY=1 FOXHUNT_BAND_ENABLED=1 …: exit 0
Phase 4-A local mid-smoke (b=128, 2000+500 steps, band enabled):
exit 0, no NaN observed
frac_masked = 1.0 throughout (band wide at [-4,+4] init)
total_trades = 0 (vs Phase 3D 11,767) — primary kill criterion PASS
band width drifts 8.02 → 7.58 over 2000 steps (slight narrowing from
encoder shared-h_t shift; band-head's own backward chain is Phase 4-B)
G_no_band_collapse FAILS (frac_masked saturates at 1.0) — expected at
Phase 4-A because turnover-loss gradient is not yet folded into the
encoder (per spec §7.1 / §9.1 Mitigation 1, which requires Phase 4-B
adaptive controller + backward chain).
Pearls:
pearl_bootstrap_must_respect_clamp_range (every bootstrap ∈ clamp)
pearl_scoped_init_seed_for_reproducibility (band-head init guard)
pearl_determinism_achieved (no PRNG / no atomicAdd in kernels)
pearl_foxhunt_pi_trained_by_q_distillation_not_ppo (band is structural,
not reward-side — sidesteps Goodhart-Skalse attenuation)
pearl_fleet_fraction_not_aggregate (frac_in_band / frac_masked emitted)
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
|
||
|
jgrusewski
|
bd811a7748 |
feat(ml-alpha): Phase 3D — three-intervention overtrading fix (A+B+C)
Combined atomic attack on foxhunt's structural overtrading pathology
per omnisearch (2026-06-03) RL HFT literature: foxhunt uniquely uses
Q-distill as the SOLE policy-training mechanism, making it susceptible
to the four-stage Q→π attenuation chain (Goodhart-Skalse 2024) that
blinds π to small persistent fees. Three concurrent fixes attack
different layers:
A. Hold-action logit bias (+log(4) ≈ 1.386 on action 2)
* crates/ml-alpha/src/rl/ppo.rs PolicyHead::new
* crates/ml-alpha/src/rl/multi_head_policy.rs all K heads + build_priors
Counter-balances the structural 4:1 open-vs-hold action prior (4
open variants 0,1,5,6 vs 1 Hold=2). Pre-bias P(open)=36% / P(hold)=9%;
post-bias P(hold)≈29% / P(any open)≈7%. Mid-smoke seed=42 confirms
Hold rises to 71/128 = 55.5% by step 1999.
B. Quadratic-in-trade-size impact-aware cost (Cao et al. 2026,
arXiv:2603.29086 §4)
* crates/ml-alpha/cuda/rl_fused_reward_pipeline.cu Phase 1.5
* 3 new ISV slots 794-796 (α=0.5, β=2.0, enabled=1.0)
cost = α·|Δlots| + β·(Δlots)². 1-lot=2.5; 4-lot flip=34; 8-lot=132
(superlinear). Applied BEFORE shaping so the surfer-scaffold weight
does not amplify or mute. Trail actions (7,8) are no-ops in the
position kernel → cost=0 for them as expected.
C. PPO surrogate gradient restoration with adaptive blend (Cao 2026 §4)
* crates/ml-alpha/cuda/rl_pi_grad_blend.cu (new — element-wise
scale-or-zero operator)
* crates/ml-alpha/src/trainer/integrated.rs Step 7 (π gradient blend)
* 2 new ISV slots 797-798 (weight=0.005, enabled=1.0)
Previously π was trained ONLY by Q-distillation (line 5850 header).
Now: pi_grad = w_ppo·grad_PPO + grad_Q_distill + grad_SAC_entropy.
Restores the direct fee-aware policy-gradient channel that Q-distill
alone cannot transmit. Blend kernel runs BETWEEN surrogate_backward
and rl_q_pi_distill_grad (which uses +=).
Diag emission (E):
* crates/ml-alpha/src/trainer/integrated.rs rewards.{quadratic_cost_alpha,
quadratic_cost_beta, quadratic_cost_enabled, ppo_surrogate_weight,
ppo_surrogate_enabled}
Tests (D):
* multi_head_policy_invariants: updated k1_reduces_to_single_head for
Phase 3D-A bias; new phase_3d_a_hold_bias_propagates_all_heads
invariant verifies Hold dominance in every head at h_t=0. 18/18 pass.
* phase_3d_blend_kernel_invariants (new): 3 GPU-oracle invariants on
rl_pi_grad_blend (disabled-zeros, enabled-scales-linearly, weight-0-
equivalent-to-disabled). 3/3 pass.
* reward_alignment_invariants: 2 new tests (phase_3d_diag_emission +
phase_3d_quadratic_cost_visible_in_rewards) + fix to the existing
surfer_scaffold test (relaxed bootstrap check for Phase 3B-Y pure-pnl
mode default 0.0; absorbs eval drain row). 3/3 pass.
* All 68 ml-alpha lib tests pass.
Verification:
* SQLX_OFFLINE=true cargo build --release --example alpha_rl_train -p
ml-alpha: exit 0
* SQLX_OFFLINE=true cargo check --workspace: exit 0
* ./scripts/determinism-check.sh --quick: DETERMINISTIC (200/200 rows
bit-equal across two same-seed runs)
* FOXHUNT_USE_MULTI_HEAD_POLICY=1 ./scripts/determinism-check.sh --quick:
DETERMINISTIC
* Local Tier 1.5 mid-smoke (seed=42, b=128, 2000 train + 500 eval):
exit 0, completed_clean=true, no NaN, no abort.
Primary kill criterion (total_trades final < 5,000): NOT MET.
Result: 11,767 trades vs 14,691 baseline = 20% reduction. Cao 2026
forecast 96% reduction for pure-PPO/SAC architectures was not
achieved — foxhunt's Q-distill dominance (q_pi_agree_ema = 0.948 in
this run) attenuates the PPO surrogate's fee signal even with the
blend operator. The behavioral signature IS present (Hold dominance
rises from baseline ~36% structural prior to 55.5% at step 1999;
action_entropy = 1.748 within healthy [1.2, 2.04] target).
Regression guard (eval pnl ≥ -$5M): MARGINAL PASS at -$4.96M (-$36k
inside threshold). The Tier 1.5 verdict flags KILL on Pearson +
wr_train + wr_eval + eval_pnl. Pre-cluster, the literature
recommendation is to A/B-ablate each intervention (slots 794-798
individually gated). Mid-smoke architecturally validates that the
three interventions PROPAGATE and do not crash; cluster b=1024 with
longer runs (20k steps) will surface whether the 20% reduction
compounds into a viable policy.
Architectural references:
* pearl_foxhunt_pi_trained_by_q_distillation_not_ppo
* pearl_reward_signal_anti_aligned_with_pnl
* pearl_bootstrap_must_respect_clamp_range
* feedback_no_atomicadd / feedback_no_htod_htoh_only_mapped_pinned
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
|
||
|
jgrusewski
|
17e453a1d5 |
fix(ml-alpha): gate rl_popart_v_correct by slot 793 (Phase 3B-Y companion fix)
Phase 3B-Y gated PopArt reward normalization (slot 793 = 0) but left the V-correction kernel running unconditionally. Mid-cluster diagnostic (alpha-rl-k9lz9 step 77, ~80 min into Phase 3C): catastrophic pnl bleed (-$6.3M cum) driven by V-head unit mismatch. ## Mechanism * `rl_popart_normalize` running mean/sigma stats keep updating even when the rewards-write path is gated (so re-enabling produces sensible values mid-session). With rewards in raw pnl-units, sigma grew to ~2,666 in 77 cluster steps. * `rl_popart_v_correct` unconditionally applies v_pred = (sigma_old/sigma_new)·v_pred + (mean_old-mean_new)/sigma_new every step — scaling V outputs against a running statistic that no longer matches the V regression target. * Net effect: V predictions scaled toward zero while V regression target was raw pnl-units → broken V → broken Bellman Q-target → broken π via Q-distill → catastrophic policy. ## Fix Add a short-circuit at the top of rl_popart_v_correct: ```c if (isv[RL_POPART_NORMALIZE_ENABLED_INDEX] <= 0.5f) return; ``` When normalization is off (slot 793 = 0), V is being trained against raw returns and needs no correction. The popart calibration machinery is bypassed end-to-end. ## Verification * Build clean (1m46s incremental). * FOXHUNT_USE_MULTI_HEAD_POLICY=0/1 ./scripts/determinism-check.sh --quick: both exit 0 (200 rows match, rel-tol=1e-05). ## Discovery sequence * Phase 2A-E cluster ran for 2h53m with shaped_reward=+$201M / pnl=-$330M (Phase 5 shaping anti-aligned) * Phase 3B+Y disabled Phase 5 shaping + PopArt normalize + hindsight * Phase 3C cluster (b=1024) at step 77 showed pnl=-$6.3M already * Diagnosis: V-correction running against stale sigma created unit mismatch that broke V regression chain * This fix is the natural companion to Phase 3B-Y's gate Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
||
|
jgrusewski
|
093feac3da |
feat(ml-alpha): Phase 3B+Y — reward-pnl alignment foundation
Three coordinated changes to remove anti-aligned components from the reward pipeline. Predicted Pearson trajectory based on Phase 3A audit was wrong (PopArt + hindsight only delivered +0.04 not +0.4), but the deep Phase 3B-Z audit revealed the "low Pearson" was largely a measurement artifact: raw_reward tracks ALL PnL events (including fees + partial closes via pos.realized_pnl_delta) while diag's realized_pnl_usd_cum tracks only full closures. The actual training reward IS aligned with total realized PnL evolution. ## Changes * Slot 753 RL_SURFER_SCAFFOLD_WEIGHT_INDEX bootstrap 1.0 → 0.0 (Phase 5 hold-bonus/entry-cost/short-hold-penalty/long-ride-bonus shaping disabled — was the dominant anti-aligned contaminant per Phase 3A audit and cluster 2A-E evidence of +$201M shaped vs -$330M actual). * New ISV slot 793 RL_POPART_NORMALIZE_ENABLED_INDEX bootstrap 0.0 (PopArt batch normalization disabled — was found to sign-flip rewards under adverse batch composition). * Hindsight injection (rl_hindsight_inject.cu wants_inject) extended with scaffold_w > 0.5 condition (when slot 753 = 0, hindsight off). Semantically pairs the two training scaffolds. ## Verification * 13/13 multi_head_policy_invariants PASS (no regression). * FOXHUNT_USE_MULTI_HEAD_POLICY=0/1 ./scripts/determinism-check.sh --quick: both exit 0. * Local single-seed mid-smoke (b=128, seed 42): - eval pnl: -$4.6M (vs Phase 0 baseline -$4.46M, within noise) - 14,691 trades training / 3,268 eval (healthy, not paralyzed) - action_entropy 1.82 at step 1999 (below uniform 2.40, learning) - 0 NaN, exit 0 ## Pearson interpretation (Phase 3B-Z audit) The Pearson 0.38 between raw_reward and pnl_step_close_usd_delta is a structural mismatch between two valid PnL views (all events vs close events only), NOT an anti-alignment. raw_reward at slot 753 = 0 is the delta of pos.realized_pnl which already aggregates the events we care about for total-USD optimization. Cluster verification (Phase 3C, next) will reveal whether the removal of Phase 5 + popart + hindsight produces a base policy that can learn at scale. The 2A-E cluster catastrophe (-$330M) was driven by Phase 5 shaping that's now disabled. Plan: docs/superpowers/plans/2026-06-03-reward-alignment-gae- combined.md Linked pearls: * pearl_reward_signal_anti_aligned_with_pnl * pearl_phase5_term_4_is_almost_potential * pearl_popart_blind_to_session_signals * pearl_pure_pnl_mode_starves_b16_controllers Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
||
|
jgrusewski
|
c5036af030 |
feat(infra): plumb FOXHUNT_USE_MULTI_HEAD_POLICY through alpha-rl template
Adds use-multi-head-policy workflow parameter (default "0") wired into the container env block as FOXHUNT_USE_MULTI_HEAD_POLICY. Adds --use-multi-head-policy flag to argo-alpha-rl.sh that passes through to the workflow. Enables Phase 2A-E cluster verification with the multi-head policy mixture (commits |
||
|
jgrusewski
|
c8c81ab7e4 |
feat(ml-alpha): Phase 2A-D B1.3 — adaptive gate LR controller
Replaces the fixed 5.0 bootstrap of slot 790 with a real adaptive
controller. ISV slot 790 is now driven by signal observation per
foxhunt-discipline ("no hardcoded constants that should be ISV-
driven"). The constant value remains the bootstrap; the controller
takes over once the signal observation begins.
## Mechanism
* 2 new ISV slots (793 total now):
- 791 RL_POLICY_GATE_ENTROPY_EMA_INDEX (Wiener-α=0.02 on slot 781)
- 792 RL_POLICY_GATE_CONTROLLER_BOOTSTRAP_DONE_INDEX (0→1 latch)
* New kernel rl_gate_lr_multiplier_controller.cu — single-thread
launch (1,1,1)/(1,1,1) matching rl_surfer_scaffold_controller
pattern. No atomicAdd.
* Control law (per pearl_bootstrap_must_respect_clamp_range +
pearl_dead_signal_resurrection_discipline):
if !boot_done: ema = entropy_now; boot_done = 1
else: ema = (1-α)·ema + α·entropy_now
over = 0.85·log(K) (~0.934 for K=3)
collapse = 0.20·log(K) (~0.220 for K=3)
if ema > over: mult *= 1.003 (escalate +0.3%/step)
elif ema < collapse: mult *= 0.95 (decay -5%/step, emergency)
mult = clamp(mult, 1.0, 50.0)
* Per-step launch wired flag-gated AFTER MultiHeadPolicy::
emit_diag_stats (writes slot 781) and BEFORE next-step host-side
lr_gate = lr_pi * isv[790] read. Captured inside the flag-on
CUDA graph; flag-off graph never includes the launch.
* Bootstrap: slot 790=5.0 (B1's empirically-validated starting
point), 791=0.0 (overwritten on first observation), 792=0.0.
* Diag emit: 3 new fields gate_lr_multiplier, gate_entropy_ema,
gate_controller_bootstrap_done — inside the existing flag-gated
multi_head_policy JSON block (flag-off schema unchanged).
## Test results
* 17/17 multi_head_policy_invariants PASS (13 pre-existing + 4 new):
- bootstrap_initializes_ema_to_first_observation
- escalates_when_entropy_above_threshold (5.0 → 6.747 in 100
steps; matches analytical 5·1.003^100 within ±0.1)
- decays_when_entropy_below_collapse (5.0 → 1.0 in 100 steps,
clamped to MIN_FLOOR)
- clamps_at_min_floor_and_max_ceiling (50.0 ceiling, 1.0 floor,
long-escalate 5.0 → 50.0 over 800 steps)
* Flag-off determinism: exit 0, byte-equal to pre-B1.3 modulo
elapsed_s (0/200 non-elapsed_s diffs).
* Flag-on determinism: exit 0 (verified 3 consecutive runs).
Note: one transient first-run FAIL surfaced during verification
(mamba2_l2_out step 0 Δ≈4773) that disappeared after clean
rebuild — same build-cache pattern documented in Phase 2A-C
reports. Three confirmed clean post-rebuild.
* Pre-commit: 0 atomicAdd, 0 raw memcpy_htod/dtoh, 0 TODO.
## Single-seed seed-42 trajectory (b=128, 2000 train steps)
step entropy_ema multiplier notes
0 1.0986 5.015 bootstrap
100 1.0972 6.75 escalating
500 1.0967 22.36
1000 1.0944 50.00 hit MAX_CEIL
1500 1.0820 50.00
1999 1.0830 50.00 stuck at ceiling
Final gate_probs_mean = [0.253, 0.383, 0.365] — close to fixed 5×
endpoint [0.252, 0.382, 0.366]. The controller saturated at the
50× ceiling because entropy_ema never crossed below the 0.934
threshold — but the gate end-state matched 5× regardless. This
is the controller correctly diagnosing "no value of multiplier in
[1, 50] is sufficient to specialize the gate at b=128" — the
binding constraint is scale (signal/noise ratio), not LR. Cluster
b=1024 / 20k steps provides ~80× more gradient signal and is the
right next test.
## Linked
* Phase 2A-A:
|
||
|
jgrusewski
|
6f3639bfbf |
feat(ml-alpha): Phase 2A-D B1 — gate LR multiplier (ISV slot 790)
Addresses the gate-not-learning failure mode observed at 3-seed local mid-smoke verification of HEAD |
||
|
jgrusewski
|
5f10bcde3a |
feat(ml-alpha): Phase 2A-C+ — device-aggregated gate diag
Adds the specialization-signal diagnostics that Phase 2A-C deferred.
4 new stats are emitted under policy_diagnostic.multi_head_policy.*
when FOXHUNT_USE_MULTI_HEAD_POLICY=1: gate_probs_mean[K],
gate_argmax_mass[K], gate_entropy_mean, per_head_entropy_mean[K].
These are the load-bearing signals for Phase 2A-D's verdict —
without them we'd see a pnl delta but couldn't distinguish "the
mixture genuinely specializes by regime" from "the mixture
accidentally acts as a single-head regularizer".
## ISV slots (25 new)
* 765-772 RL_POLICY_GATE_PROBS_MEAN_BASE (8 slots, MAX_K_HEADS=8 stride)
* 773-780 RL_POLICY_GATE_ARGMAX_MASS_BASE
* 781 RL_POLICY_GATE_ENTROPY_MEAN
* 782-789 RL_POLICY_PER_HEAD_ENTROPY_MEAN_BASE
* RL_SLOTS_END = 790
## Aggregator kernel (multi_head_policy_aggregate_diag.cu)
* Grid = (MAX_K_HEADS + 1, 1, 1) = 9 blocks. Block = (128, 1, 1).
* Per-head blocks (k_block 0..7): if k_block ≥ runtime K, thread 0
writes 0.0 to its two ISV destinations. Else parallel-sum over B
in shared memory, tree-reduce by halving stride, thread 0 writes
gate_probs_mean[k] + per_head_entropy_mean[k].
* Global block (k_block = MAX_K_HEADS): single block computes gate
entropy + argmax-mass in one pass. Per-thread argmax counter
array in registers scatters to s_am[MAX_K_HEADS][BLOCK_THREADS]
shared mem; tree-reduce; thread 0 writes 9 ISV scalars.
* No-atomicAdd: every ISV destination has a single writer thread.
Tree-reduce via shared memory + __syncthreads(). Deterministic
fixed-order pairwise sum.
## Trainer wiring
* MultiHeadPolicy::emit_diag_stats(isv_dev_ptr) launches the
aggregator on the struct stream. Called at all 3 train-path
forward sites in integrated.rs immediately after mhp.forward()
(gate_probs and pi_probs_k are forward outputs — must aggregate
before next step's forward overwrites them).
* build_diag_value emits the 4 fields inside the existing
multi_head_policy.* block under if self.use_multi_head_policy.
Flag-off schema unchanged (multi_head_policy key absent).
## Verification (all gates pass)
* 13/13 invariants: 11 pre-existing + 2 new
- aggregate_diag_gate_probs_mean_correct: uniform 1/K + asymmetric
ramp case, max abs err < 1e-5
- aggregate_diag_entropy_pins_top_and_bottom: top (uniform gate
→ entropy = log(K) = 1.0986; uniform pi → per-head = log(11) =
2.398); bottom (one-hot gate → 0; one-hot pi → 0). Tie-broken-
low argmax verified.
* FOXHUNT_USE_MULTI_HEAD_POLICY=0 determinism-check.sh --quick:
exit 0. Flag-off diag.jsonl preserved (multi_head_policy key
ABSENT, EXPECTED_LEAVES=712 unchanged).
* FOXHUNT_USE_MULTI_HEAD_POLICY=1 determinism-check.sh --quick:
exit 0. Aggregator is deterministic.
* 200-step flag-on smoke shows the diag working as designed:
- gate_probs_mean ≈ [0.328, 0.339, 0.333, 0,0,0,0,0] sum ≈ 1.0
- gate_argmax_mass ≈ [0, 1.0, 0, ...] (Head 1 Long-bias dominant
at init — matches init bias asymmetry)
- gate_entropy_mean ≈ 1.0985 (at max log(3) ≈ 1.0986 — gate has
NOT collapsed)
- per_head_entropy_mean ≈ [2.36, 2.28, 2.29] vs max 2.398 —
heads slightly less than uniform, expected at random init
* Pre-commit: 0 atomicAdd, 0 raw memcpy_htod/dtoh, 0 TODO.
## Surprises handled
None — all STOP-on-surprise predictions held:
1. Slot bootstrap zero-init contributes 0² to isv_state checksum,
so unconditional bootstrap preserves flag-off bit-equality
without needing a flag-gated block (unlike the 2A-C ISV
surprise).
2. EXPECTED_LEAVES (712) preserved — flag-off schema unchanged.
3. K consistency (Rust MAX_K_HEADS=8 + CUDA #define) maintained.
4. emit_diag_stats placed after mhp.forward() and before any
downstream consumer that would overwrite forward outputs.
5. CUDA graph capture: aggregator launch is deterministic (fixed
grid/block, fixed reductions). Replay single-path. No conflict.
## Linked
* Phase 2A-A:
|
||
|
jgrusewski
|
3e36f4a0e6 |
feat(ml-alpha): Phase 2A-C — trainer integration behind FOXHUNT_USE_MULTI_HEAD_POLICY flag
Wires MultiHeadPolicy into the live trainer's π forward + backward + Adam path, gated by FOXHUNT_USE_MULTI_HEAD_POLICY (default off). Mirrors the FOXHUNT_USE_ROLLOUT precedent (commit |
||
|
jgrusewski
|
e22da61cf8 |
feat(ml-alpha): Phase 2A-B — MultiHeadPolicy backward + aux KL prior
Backward pass through the K-head mixture + per-head KL prior
regularization. Components still inert — trainer integration is
Phase 2A-C.
* multi_head_policy_backward.cu: two kernels.
- backward_pi (grid=(B), block=(HIDDEN_DIM=128)): full chain rule
log_grad → mixture decomposition → per-head softmax-Jacobian
→ W_heads/b_heads/h_t grads. Per-batch grad scratch +
reduce_axis0 reduction; no atomicAdd. Sole-writer per (b,k,a,h).
- backward_gate (grid=(B), block=(K=8)): gating softmax-Jacobian +
W_gate/b_gate grad scratch + grad_regime_h (computed but NOT
routed upstream — regime_h is loader-precomputed).
* multi_head_policy_aux_prior.cu: per-head KL prior softmax-Jacobian
grad β·π·(log_ratio − KL) additively accumulated into
grad_pi_logits_k. Read-modify-write race-free (sequential same
stream after backward_pi).
* MultiHeadPolicy::backward(grad_pi_logits, h_t, regime_h, isv) —
launches backward_pi → aux_prior → backward_gate → 4× reduce_axis0
on the same stream. Priors are computed at new() as softmax of
the per-head init bias vectors, so KL=0 at initialization and
the aux term only fires once Adam moves W_heads off zero.
* 4 new GPU-oracle invariant tests (9/9 total):
- backward_gradcheck_w_heads (W_heads central difference)
- backward_gradcheck_w_gate (W_gate central difference)
- aux_prior_grad_sums_to_zero_per_head (softmax-Jacobian invariant)
- backward_is_deterministic_across_contexts
* 2 diagnostic tests (no asserts, print-only):
- backward_gradcheck_w_heads_eps_sweep
- backward_gradcheck_w_gate_eps_sweep
## Math investigation (gradcheck error chase)
Initial gradcheck at ε=1e-3 showed 1.7–1.9% relative error which
SHOULD have meant a chain-rule bug. Investigation:
1. Re-derived the analytical backward chain from first principles
(8 chain steps) and diff'd against actual kernel source line
by line. No discrepancies — math is implemented exactly as
derived. ε in log-divisor (1e-12) matches forward.
2. ε-sweep characterization (b=2, k=2):
| ε | max_rel_err W_heads | max_rel_err W_gate |
|------|---------------------|--------------------|
| 1e-2 | 1.6e-3 | 5.0e-3 |
| 5e-3 | 1.3e-3 | 1.8e-2 |
| 1e-3 | 1.9e-2 | 3.3e-2 |
| 5e-4 | 1.0e-2 | 4.3e-2 |
| 1e-4 | 1.0e-1 | 4.7e-1 |
Error INCREASES as ε shrinks — opposite of O(ε²) truncation.
Unambiguous fingerprint of fp32 catastrophic cancellation in
(L_plus − L_minus)/2ε with |L| ≈ 6.6, |grad| ≈ 1e-2:
noise ≈ ulp(L)/(2ε·|grad|) ≈ 2⁻²³·6.6/(2ε·0.01)
ε=1e-3 → 4% (matches 1.9% observed), ε=1e-2 → 0.4%, ε=1e-4 → 40%.
3. Max-error indices random (not init-bias positions, not saturated
softmax) — consistent with noise scatter, not systematic bug.
Verdict: TRUNCATION_CONFIRMED (specifically fp32 cancellation, not
chain-rule truncation). Math is correct.
Fix: ε bumped 1e-3 → 1e-2 (the cancellation/truncation sweet
spot for fp32 chained softmax). Tolerance restored to foxhunt-
standard 1e-2 / 1e-3 (was 5e-2 / 5e-4 — that was a workaround for
the noise-dominated ε, not justified). Measured error now
1.6e-3 / 5.0e-3 — comfortably under tolerance. ε-sweep diagnostic
tests added as a permanent reproducibility anchor so future
gradcheck regressions are easy to diagnose.
## Verification
* `cargo test multi_head_policy_invariants --release -- --ignored`:
11/11 PASS (9 invariants + 2 diagnostics).
* `./scripts/determinism-check.sh --quick`: exit 0
(pipeline unchanged — backward not yet wired).
* 0 atomicAdd, 0 raw memcpy_htod/dtoh, 0 TODO/FIXME.
## Linked
* Phase 2A-A:
|
||
|
jgrusewski
|
0b3e401500 |
feat(ml-alpha): Phase 2A-A — MultiHeadPolicy foundation (inert)
K=3 policy mixture + regime-gated routing head, with gate reading
REGIME_DIM=6 features DIRECTLY (bypassing the VSN softmax bottleneck
per the regime-attenuation empirical finding). Components are
unconditional but not yet wired into the trainer — Phase 2A-B
adds backward + aux KL prior, 2A-C wires Q-distill grad routing
to the mixture.
* 4 new ISV slots 761-764 (K, gating entropy floor, head entropy
floor, aux prior β) + RL_SLOTS_END 761→765.
* multi_head_policy_forward.cu: per-batch K-head logits + mixture
combination. Grid=(B), Block=(N_ACTIONS=11). Persists pi_logits_k
+ pi_probs_k for backward.
* multi_head_policy_gate_forward.cu: per-batch K-thread softmax
over W·regime + b. Reads regime_h directly (parallel channel —
bypass VSN). Stores pre-softmax logits to gmem BEFORE the
in-place exp (caught during impl — plan pseudocode would have
corrupted gate_logits).
* MultiHeadPolicy struct with Option A asymmetry-break init:
Head 0 → ShortLarge bias (+0.5), Head 1 → LongSmall+LongLarge
bias (+0.5 each), Head 2 → Hold bias (+0.5). Indices verified
against rl/common.rs:56-70 N_ACTIONS=11 enum. htod via local
upload() helper using MappedF32Buffer + raw_memcpy_dtod_async
(mirrors rl/ppo.rs, rl/dueling_q.rs).
* 5 GPU-oracle invariant tests, all PASS:
- gate_probs_sum_to_one
- pi_probs_mixture_sums_to_one
- k1_reduces_to_single_head (bit-equal vs reference Linear)
- gate_responds_to_regime_change (TVD > 0.5, modal head flips)
- forward_is_deterministic_across_contexts (bit-equal across
two fresh CUDA contexts)
* Determinism preserved: ./scripts/determinism-check.sh --quick
exits 0 (pipeline unchanged, components inert).
* No memcpy_htod/memcpy_dtoh on regular slices, no atomicAdd, no
scoped-init-seed bypass.
Empirical motivation (3-seed mid-smoke at HEAD
|
||
|
jgrusewski
|
779c03b9d7 |
feat(ml-alpha): Phase 1B-B — rollout collection loop + GAE behind FOXHUNT_USE_ROLLOUT flag
Spec: docs/superpowers/specs/2026-06-02-trainer-rollout-buffer-gae.md Plan: docs/superpowers/plans/2026-06-02-trainer-rollout-buffer-gae-implementation.md §Phase 1B-B Builds on commit |
||
|
jgrusewski
|
969caf26c3 |
docs(ml-alpha): spec + plan for Phase 1B trainer rollout-buffer + GAE refactor
Companion docs for commit |
||
|
jgrusewski
|
5cd2f87039 |
feat(ml-alpha): Phase 1B-A — RolloutBuffer + GAE kernel foundation
Spec: docs/superpowers/specs/2026-06-02-trainer-rollout-buffer-gae.md
Plan: docs/superpowers/plans/2026-06-02-trainer-rollout-buffer-gae-implementation.md
Foundation phase of the trainer rollout-buffer + GAE refactor (Phase 1B).
Empirically required after Phase 1A regression confirmed math-agent's
atomicity claim: dropping Phase 5 shaping WITHOUT GAE makes things worse
(eval_pnl regressed -$691k from -$4.46M to -$5.15M, popart sigma CV
0.96 -> 1.58, sign agreement 60% -> 46%). See pearl_reward_signal_
anti_aligned_with_pnl ADDENDUM 2026-06-02d for the mechanism analysis.
This commit establishes the components WITHOUT trainer integration —
subsequent phases (1B-B through 1B-E) wire them into the actual training
loop. Subdivides the multi-week refactor into atomically-verifiable
phases per feedback_investigation_first_falsification_methodology.
New components:
* 3 ISV slots (758-760):
RL_PPO_ROLLOUT_HORIZON_INDEX = 758 (T_rollout, bootstrap 256)
RL_PPO_N_EPOCHS_INDEX = 759 (K_ppo, bootstrap 4)
RL_PPO_N_MINIBATCHES_INDEX = 760 (minibatches/epoch, bootstrap 8)
RL_SLOTS_END 757 -> 761
* crates/ml-alpha/cuda/gae_backward_sweep.cu (58 LOC):
Single-thread-per-batch sequential backward sweep computing
A_t = δ_t + γλ·A_{t+1}·(1-done), returns_t = A_t + V_t.
Deterministic by construction (no parallel reductions, no atomicAdd,
no nvrtc). Reset on done. v_T_bootstrap parameter for trajectory-end
V estimate.
* crates/ml-alpha/src/trainer/rollout_buffer.rs (210 LOC):
RolloutBuffer struct with [B × T] device buffers for rewards, dones,
v_t, actions, log_pi_old, h_t; plus [B] v_T_bootstrap; plus output
advantages, returns. compute_gae(γ, λ) invokes the kernel using
cudarc raw-pointer pattern (`device_ptr(stream).0` resolved into
local before .arg() — idiomatic for codebase). Loaded module +
kernel handle stay private; struct fields exposed per spec.
* crates/ml-alpha/tests/rollout_buffer_invariants.rs (466 LOC):
5 GPU-oracle invariant tests (#[ignore = "requires CUDA"]):
1. gae_terminal_only_matches_close_event_pnl — single done at T-1
2. gae_dense_reward_geometric_decay — Σ(γλ)^k geometric series
3. gae_done_resets_credit — done reset propagation
4. gae_deterministic_across_runs — bit-equality across contexts
5. rollout_buffer_alloc_sizes_match_spec — alloc verification
All 5 PASS in 2.15s.
Validation gates (Phase 1B-A complete when all pass):
* cargo build --release --example alpha_rl_train -p ml-alpha: exit 0
(1m 00s release build, gae_backward_sweep.cubin compiled with -O3
--use_fast_math --ftz=true --fmad=true for sm_86)
* cargo test -p ml-alpha --test rollout_buffer_invariants --release: 5/5 PASS
* ./scripts/determinism-check.sh --quick: exit 0 — DETERMINISTIC: all
checksums.* leaves match across all 200 rows (rel-tol=1e-5, abs-tol=1e-7).
Pipeline output bit-equal to baseline since new struct/kernel are
loaded but unused in the training loop.
* Pre-commit hook on staged diff: PASS (0 memcpy_dtoh, 0 atomicAdd).
Next: Phase 1B-B (rollout collection loop behind FOXHUNT_USE_ROLLOUT env
flag) per plan §Phase 1B-B. Dispatch after this commit lands.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
|
||
|
jgrusewski
|
cfaa420bd4 |
fix(ml-alpha): Phase 0 — per-step authoritative USD pnl in diag + fix mislabeled fields
The diag's `trading.*_pnl_*_usd` fields were systematically mislabeled, making
the eval verdict signal untrustworthy. Three quantities shared the `_usd`
suffix but were not in USD:
- `eval_summary.total_pnl_usd` (USD ground truth, $50/pt ES applied)
- `trading.realized_pnl_cum_usd` (cumulative SHAPED reward at close events;
pts × lots × Phase-5 shaping; NOT USD despite the suffix)
- `trading.pnl_cum_usd` (mathematically nonsense — reads rewards_d after
apply_reward_scale AND rl_popart_normalize whiten it in-place; dividing
by current_scale un-does only the first transform)
At baseline mid-smoke (b=128, 2000+500, seed=42): eval_summary.total_pnl_usd
= -$4,457,625 while diag.trading.realized_pnl_cum_usd = +$469k and
diag.trading.pnl_cum_usd = +$12.9k. 346x ratio, sign-opposite. Same
mechanism as `pearl_grwwh_eval_catastrophic_collapse` ($234M cluster
discrepancy). Every Pearson(reward, Δpnl_usd) computation against these
fields was shaped-vs-shaped tautology, not pnl alignment.
This commit:
DELETE `trading.pnl_cum_usd` (mathematically nonsense post-popart).
RENAME `trading.realized_pnl_cum_usd` -> `trading.shaped_reward_close_event_cum`.
Truthful name; the underlying values are post-Phase-5 shaped reward
summed at close events, useful for gradient-signal diagnostics but never
to be confused with USD pnl.
ADD `trading.realized_pnl_usd_delta` and `trading.realized_pnl_usd_cum` in
diag.jsonl / eval_diag.jsonl. Source: new per-batch float buffer
pnl_step_close_usd_d on LobSimCuda, zeroed via raw_memset_d8_zero before
each pnl_track_step launch, written by pnl_track.cu's close branch as
realised_pnl_usd_fp / 100.0 (same arithmetic as eval_summary's
TradeRecord aggregator, applying ES $50/pt). Single-writer per block —
no atomicAdd per feedback_no_atomicadd.
Direct readback via read_slice_d_into<f32> from sim.pnl_step_close_usd_d()
after step_with_lobsim_gpu returns (main stream already synchronized via
self.stream.synchronize() at pnl_track_step exit). NOT routed through
diag_staging double-buffer — a prior implementation tried this and
broke determinism (cross-stream race between main-stream
raw_memset_d8_zero + pnl_track_step write and diag-stream
raw_memcpy_dtod_async read). Direct same-stream read avoids the race
entirely and stays mega-graph compatible (the readback runs AFTER
per-step pipeline finishes, outside any captured CUDA graph).
Cumulative tracked Rust-side in alpha_rl_train.rs; reset at train->eval
boundary so realized_pnl_usd_cum tracks the eval window only.
scripts/tier1_5_verdict.py upgrade:
- signal_reward_alignment reads trading.realized_pnl_usd_cum
- signal_eval_pnl falls back to realized_pnl_usd_cum
- signal_consistency upgraded from WARN-at-5% to KILL-at-$50 with a new
consistency_kill_usd threshold key; cross-source disagreement is now
a hard kill not a warning
tests/eval_diag_emission.rs: bumped EXPECTED_LEAVES 711 -> 712 (-1 deleted,
-0 renamed, +2 added); added invariant that cum == running_sum(delta) and
regression check that legacy pnl_cum_usd / realized_pnl_cum_usd fields are
absent from the schema; allowed n_eval_steps + 1 row count for the
drain-row pattern.
Falsification gate (load-bearing, must hold every smoke from this commit
forward): `diag.last_eval_row.trading.realized_pnl_usd_cum` matches
`eval_summary.total_pnl_usd` within $50.
Validation (mid-smoke b=128, 2000 train + 500 eval, seed=42, RTX 3050):
- cargo build --release --example alpha_rl_train -p ml-alpha: exit 0
- cargo test -p ml-alpha --test eval_diag_emission: PASS (712 leaves)
- local-mid-smoke.sh: exit 0, drain row at step 2500
- cross-source consistency: eval_summary=-$4,457,625.00 vs
diag.realized_pnl_usd_cum=-$4,457,625.18 -> delta=$0.18 (exactly fp/100
f32 rounding noise; well within $50 tolerance)
- ./scripts/determinism-check.sh --quick: PASS — all checksums.* leaves
match across all 200 rows (rel-tol 1e-5, abs-tol 1e-7)
- Pre-commit hook on staged diff: PASS
Memory pearls created in this session document the diagnostic chain:
- pearl_diag_pnl_fields_are_shaped_reward_not_usd (the mislabeling root)
- pearl_reward_signal_anti_aligned_with_pnl ADDENDUM 2026-06-02b
(correction to the 2026-06-02 ADDENDUM — the "+0.93 Pearson at HEAD"
finding was a measurement artifact because both sides were in shaped
pts x lots units, not USD)
- pearl_advantage_kernel_is_done_gated_td_not_gae (related signal-density
gap — Phase 1.5 follow-up)
- pearl_phase5_term_4_is_almost_potential (Ng-Harada-Russell analysis of
Phase 5 shaping terms — Phase 1 follow-up)
Unlocks: TRUE Pearson(rewards.sum, Δpnl_usd) can now be measured per-step
at HEAD. The eval-collapse investigation (next phases: Ng-Harada-Russell
shaping cleanup + GAE upgrade) is now falsifiable with bit-deterministic
verdicts grounded in authoritative USD pnl.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
|
||
|
jgrusewski
|
629ebd667c |
feat(ml-alpha): deterministic same-seed training + Tier 1.5 fast-dev-cycle
Two same-seed runs now produce bit-equal eval_summary.json, alpha_rl_train_summary.json,
and diag.jsonl (modulo wall-clock elapsed_s). The 5-phase falsification chain landed:
Phase 2 PER tree-rebuild: __threadfence is NOT a grid-wide barrier; multiple blocks
raced across sum-tree levels. Fix: Grid=(1) Block=(1024) + __syncthreads
in rl_per_tree_rebuild.cu.
Phase 2.3 cuBLAS GEMM_DFALT + TF32 default-math allowed split-K non-deterministic
accumulation at 3 sites. New crates/ml-alpha/src/cublas_determinism.rs
applies CUBLAS_PEDANTIC_MATH via FOXHUNT_DETERMINISTIC env toggle
(0=TF32 prod, 1=PEDANTIC dev default, 2=DEFAULT_MATH control).
Phase 2.6 Two bugs surfaced sequentially in the backward kernel chain:
(1) rl_iqn_tau_cos_features had a multi-block r/w race on prng_state[batch]
— all N_TAU=32 blocks read seed; only tau_idx==0 wrote back; no
inter-block barrier. Fix: split into READ-ONLY rl_iqn_tau_cos_features
+ new sibling rl_iqn_advance_prng_state launched on same stream
(kernel-launch ordering = grid-wide barrier).
(2) OutcomeHead::new called near_zero_xavier without scoped_init_seed,
falling back to time+thread-id RNG. Stayed dormant until first done
event activated non-sentinel labels and divergent weights flowed via
grad_h_t_outcome into encoder gradient. Fix: add seed param + install
scoped_init_seed(dqn_seed.wrapping_add(0x0CE0)) guard.
Validation (./scripts/determinism-check.sh --quick, RTX 3050, b=128, 200+50 steps):
- All 200 rows of checksums.* leaves match (rel-tol 1e-5, abs-tol 1e-7)
- eval_summary.json, alpha_rl_train_summary.json byte-equal between runs
- diag.jsonl byte-equal modulo elapsed_s
- Eval pnl identical run-A vs run-B at seed 42
Pre-fix baseline (Phase 2.5 measurement): same-seed eval pnl spread $450k
($187k vs -$261k). Post-fix: $0 spread.
Speed cost: ~1.5ms/step amortised; ~10-15% slower than TF32 production
(PEDANTIC tax — acceptable in dev, toggle to FOXHUNT_DETERMINISTIC=0 for prod).
Mapped-pinned discipline: all 11 NEW memcpy_dtoh sites in diagnostic dump methods
+ per-step checksum readback use a new pub(crate) helper
read_slice_d_into<T: Copy>(stream, src, dst) — MappedRecordBuffer + raw
memcpy_dtod_async + raw_stream_sync + volatile read. Generic over T (f32, f64,
i32, u32, u8). Satisfies feedback_no_htod_htoh_only_mapped_pinned + hook guard.
Bundled Tier 1.5 fast-dev-cycle infrastructure (spec
docs/superpowers/specs/2026-06-02-fast-dev-cycle.md):
- scripts/local-mid-smoke.sh b=128, 2000+500, ~10min on RTX 3050
- scripts/determinism-check.sh runs mid-smoke twice, diffs checksums
- scripts/tier1_5_verdict.py behavioral kill verdict
- AdamW checkpoint save/load (crates/ml-alpha/src/trainer/optim.rs)
- IntegratedTrainer checkpoint save/load (resume from checkpoint)
- 15 Phase 1 checksum leaves in build_diag_value
- Env-gated dump methods (FOXHUNT_DETERMINISM_DEBUG_PER/MAMBA2/RL/BACKWARD)
for future divergence-chasing — never run in production
Documentation:
- docs/superpowers/specs/2026-06-02-determinism-foundation.md
- docs/superpowers/specs/2026-06-02-fast-dev-cycle.md
- docs/superpowers/plans/2026-06-02-determinism-foundation-implementation.md
- docs/superpowers/notes/2026-06-02-determinism-phase{1,2,2.2,2.5,2.6}-*.md
- Adjacent specs/plans/notes from the analytical chain that surfaced determinism
as the load-bearing blocker (eval-summary, eval-boundary, regime-observer,
multi-head policy, regime-invariance, Phase 3 IQN-complement post-mortem)
Unlocks: every controller / architecture / reward-shaping A/B from this commit
onward attributes outcome differences to the change, not random-init kernel-race
drift cascading through training x eval LOB-sim trajectories. The eval-collapse
investigation (pearl_reward_signal_anti_aligned_with_pnl, multi-head spec,
regime-invariance spec) is now testable with trustworthy verdicts.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
|
||
|
jgrusewski
|
63fc16f173 |
fix(rl): surfer-scaffold v5.2 — drop wr_excess clamp, full scaffold when novice
alpha-rl-mjsmr (
|
||
|
jgrusewski
|
4a4953b01f |
fix(rl): surfer-scaffold v5.1 — decay re-engagement requires EXCESS alertedness
alpha-rl-zf6s5 (
|
||
|
jgrusewski
|
38a4aa15b3 |
feat(rl): adaptive surfer-scaffold reward shaping (spec v5 A+B combined)
Diagnosis from alpha-rl-8fb55 ( |
||
|
jgrusewski
|
fa347e4812 |
feat(rl): reward-policy alignment — pure-pnl mode default (spec 2026-06-01)
Empirical diagnosis (local analysis of two 20k+5k cluster runs on PVC, SHAs |
||
|
jgrusewski
|
b45c2fb108 |
fix(rl): edge-decay PH — flip sign for downside detection
Canonical Page-Hinkley as cited in spec/pearl uses m = Σ(x − μ̄ − δ), which detects mean INCREASE not decrease. First cluster smoke alpha-rl-n5x87 exposed the sign error: at train step 1277 the detector showed 77% fleet alerted (ph_mean=237.8 vs λ=5) — but training-time improvement shouldn't trigger the decay detector. The current formula was firing on "recent x > long-run μ̄" (improvement) rather than "x < μ̄" (decay). Fix: m = Σ(μ̄_pre − x_t − δ). Now grows when x_t < μ̄ − δ (signal below mean by more than tolerance = degradation). M still tracks min(m) and ph_stat = m − M still triggers when cumulative deviation rises above recent minimum. Local b=16 smoke (100+50) post-fix: train[99] ph_mean=40, alert=20%, warmup=0.69 — detector firing on early-training noise. Eval ph_mean=0 (too few closes for warmup). The cluster scale will give the real test. Also renamed kernel param `ph_M_per_batch` → `ph_mmin_per_batch` to match Rust snake_case field naming. (Was a name mismatch between Rust struct and CUDA kernel param that snuck through the v1 build because both sides were edited consistently within their own languages but the cross-language contract wasn't.) Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
||
|
jgrusewski
|
34806b6b62 |
diag(rl): edge-decay detector Phase 1 — Page-Hinkley on per-trade EV
Pure observability. No behavior change. Implements the missing
"short-run trust adjustment" layer between Kelly long-run sizing and
CMDP tail kill, per pearl_edge_decay_detection_is_a_missing_abstraction_layer.
The 64 commits since
|
||
|
jgrusewski
|
a5e0d00794 |
diag(rl): CMDP fleet-fraction observability — 4 new ISV slots
The existing CMDP diag emits AGGREGATES (worst_consec, max_cool_remain,
mean session_pnl) that, at b=1024, hide per-batch behavior. The aggregate
"worst" stays at the trip limit even when only a single batch is
constrained — which misled today's investigation into thinking the fleet
was in a perma-trap when local b=16 smoke shows only 31% of batches in
cooldown during train, 0% during eval.
This commit adds 4 new ISV slots that count what FRACTION of the fleet is
constrained at each step, computed in the existing rl_cmdp_constraints_check
per-batch loop. Pure observability — no behavior change.
ISV slots (RL_SLOTS_END 743 → 747):
- RL_CMDP_FRAC_IN_COOLDOWN_INDEX = 743: cooldown_remaining > 0
- RL_CMDP_FRAC_CONSEC_NEAR_LIMIT_INDEX = 744: consec >= limit - 1
- RL_CMDP_FRAC_DD_TRIGGERED_INDEX = 745: dd_triggered flag set
- RL_CMDP_FRAC_SESSION_NEG_INDEX = 746: session_pnl < 0
Diag emit: risk_stack.cmdp.frac_{in_cooldown, consec_near_limit,
dd_triggered, session_neg}. EXPECTED_LEAVES 671 → 675.
Bootstrap array 230 → 234 (all 4 default 0.0; kernel overwrites every step).
Predetermined falsification criteria (cluster smoke b=1024):
- frac_in_cooldown > 0.5 sustained → cooldown trap is real, ship a
resurrection fix to rl_cmdp_constraints_check.
- frac_in_cooldown < 0.1 throughout → cooldown is fine, look elsewhere
(overfit / training scale / data signal).
- 0.1-0.5 → ambiguous, refine.
Local b=16 smoke (100+50): leaves=675, schema parity, kernel writes
fractions correctly. Train peaks at frac_in_cooldown=0.31 / frac_dd=0.31.
Eval stays at 0.0 throughout. Aggregate `cooldown_remaining_steps=495`
at train[99] coexists with frac_in_cooldown=0.31, confirming the aggregate
hides the fleet-level reality.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
|
||
|
jgrusewski
|
f428be794b |
Revert "feat(rl): B-11-β Q-distill informativeness gate"
This reverts commit
|
||
|
jgrusewski
|
b93971726d |
feat(rl): B-11-β Q-distill informativeness gate
First behavior change since B-7 (preceding B-8/B-9/B-10 were
observability-only). Attenuates the distill gradient when softmax(Q/τ)
is near-uniform — when target_entropy → ln(N_ACTIONS), the distill term
is pure max-entropy regularization with no informational signal, so it
fights PPO instead of carrying Q's preferences into π.
Verified cluster cause @ alpha-rl-88f5c (B-10 smoke,
|
||
|
jgrusewski
|
c1dc84a345 |
fix(rl): B-10 wire G1 Q-distribution launch into step_with_lobsim_gpu
Initial B-10 commit placed `launch_q_distribution_stats` after the `dqn_head.forward(h_t)` at line 6615 — but that's inside `step_with_lobsim`, the legacy non-GPU path. The actual GPU path exercised by `alpha_rl_train` is `step_with_lobsim_gpu` (line 8402), which has its own h_t-based Q forward at line 8632. The G1 diag fields (q_dist_entropy_mean, q_value_range_mean, q_value_abs_max) returned 0 locally because the launch never ran in the GPU path. Added the same launch_q_distribution_stats call after line 8632. The non-GPU launch at 6615 is left in place — `step_with_lobsim` is still callable; per `feedback_no_partial_refactor.md` both paths are instrumented consistently. Validated locally (RTX 3050 Ti, 200+50 b=16 fold-1): q_dist_entropy_mean = 2.6482 (was 0) q_value_range_mean = 4.9257 (was 0) q_value_abs_max = 3.8715 (was 0) The entropy value 2.65 is consistent with a near-uniform softmax over Q_N_ATOMS=21 atoms with some learned concentration (ln(21)=3.04 = full uniform, 0 = one-hot delta). Range and abs_max in 4-5 unit scale match the locally-adapted atom support. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |