8df1c7eea2f4e280aeb89c2b341d9e8135e46465
164 Commits
| Author | SHA1 | Message | Date | |
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jgrusewski
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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> |
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jgrusewski
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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
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jgrusewski
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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:
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jgrusewski
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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
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jgrusewski
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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 |
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jgrusewski
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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> |
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jgrusewski
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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>
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jgrusewski
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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>
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jgrusewski
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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
|
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
|
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
|
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>
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jgrusewski
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38a4aa15b3 |
feat(rl): adaptive surfer-scaffold reward shaping (spec v5 A+B combined)
Diagnosis from alpha-rl-8fb55 ( |
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jgrusewski
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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 |
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jgrusewski
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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
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jgrusewski
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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>
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jgrusewski
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f428be794b |
Revert "feat(rl): B-11-β Q-distill informativeness gate"
This reverts commit
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jgrusewski
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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,
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jgrusewski
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8c7ce02da9 |
feat(rl): B-10 policy-quality cascade diagnostic
alpha-rl-8gtk2 (B-7+B-8+B-9 run at SHA
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jgrusewski
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033906f213 |
docs(rl): fix stale C51 V_MAX/V_MIN "ratchet" claims + B-9 test bug
While alpha-rl-8gtk2 (the B-7+B-8+B-9 20k+5k cluster run) was training, B-9's saturation diag exposed V_MAX_eff dropping from 856.82 (step 482) to 464.61 (step 817) within the same run. The kernel docstrings and slot doc-comments uniformly claimed "ratchet (monotone-grow)" semantics — contradicting the observation by 392 units. Root cause: wwcsz followup 2026-05-24 (commit landed in rl_reward_clamp_controller.cu Step 5 only) REPLACED the original ratchet with a slow symmetric EWMA (α=0.001, half-life ~700 steps) on `win_bound`/`loss_bound`. Static ratchet was wasting atom resolution on rare tails (avg rewards in [-5,+5] with span at [-60,+20] → Δz=4, Q couldn't distinguish "slightly winning" from "slightly losing"). The EWMA refocuses atom resolution on the ACTIVE range. The controller's own header was correctly updated at the time. The documentation drift was in 3 other places — fixed here: - bellman_target_projection.cu header (lines 47-49): "ratchet (monotone-grow)" → accurate EWMA description with cross-references + pearl_c51_v_max_freeze_required_for_surfer warning (V_MAX in 100-200 → trend-follower; past 1000 → degraded). - rl_atom_support_update.cu line 4: "Companion to the C51 atom-span ratchet" → "Companion to the C51 atom-span EWMA". - isv_slots.rs slot allocation table line 43: "C51 atom-span ratchet slots" → "C51 atom-span EWMA slots (α=0.001)". - isv_slots.rs RL_C51_V_MAX_INDEX / RL_C51_V_MIN_INDEX doc-comments (lines 649-668): replaced with accurate EWMA description, observed 857 → 465 drop example, and asymmetric tracking note (V_MIN_eff EWMAs -loss_bound NOT -V_MAX_eff — they only coincide when ratio≈1). Latent test bug also surfaced + fixed: c51_atom_saturation_diagnostic assumed `V_MIN_eff = -V_MAX_eff` (line 136). With observed Kelly EMAs avg_loss=$436 vs avg_win=$872 → ratio ≈ 0.5 → V_MIN_eff ≈ -0.5 × V_MAX_eff, the test's bot-rate consistency check would false-fail if saturation ever became non-zero. Dormant so far (sat=0% in both smoke and full run). Relaxed the bot-rate assertion to use the v_bound_floor (-1.0) as the necessary lower bound — correct for any asymmetric ratio and catches gross drift without false-failing on legitimate adaptation. No behavior change; pure docstring drift + dormant test bug repair per feedback_trust_code_not_docs. Compile clean. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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jgrusewski
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29b5acad55 |
feat(rl): B-9 C51 Bellman-target saturation observability
Under B-7 (clamp default-disabled), per-transition rewards in bellman_target_projection / bellman_fused_select_project can exceed the adaptive atom support [V_MIN_eff, V_MAX_eff]; each t_z overshoot is silently clamped before being mapped onto the discrete support. B-9 publishes the per-step saturation rate + pre-clamp t_z extremes so we can decide if the atom span has become a bottleneck — without re-attempting the reverted Fix F atom-widening (pearl_c51_v_max_freeze _required_for_surfer). Changes: - 4 new ISV slots (726-729): top/bot saturation rate + max/min pre-proj. - bellman_target_projection.cu: both entry points (bellman_target_projection AND bellman_fused_select_project per feedback_no_partial_refactor) gain 4 new [B] f32 pointer params; thread-0 sequential reduction over Q_N_ATOMS=21 (odd count rules out symmetric tree-reduce — matches the kernel's existing softmax max/sum pattern at lines 157/171). - New cross-batch reducer cuda/rl_bellman_target_saturation_reduce.cu: single block, grid-stride gather + power-of-2 tree reduce, no atomicAdd per feedback_no_atomicadd. - dqn.rs: load reducer cubin, add saturation_reduce_fn handle, launch_saturation_reduce method, 4 scratch pointer params on both bellman methods. - integrated.rs: allocate 4 [B] f32 scratch buffers; pass through both fused_select_and_project_bellman call sites + launch reducer after each. 4 new bootstrap entries (213 → 217 fixed-size array). - build.rs: register new kernel. - 4 new diag leaves under risk_stack.atom_calibration.target_*. Comment distinguishes them from popart.max_abs_reward_ema (different signal: Bellman target = r + γ·atom_value, can exceed reward by γ·V_MAX_eff). - EXPECTED_LEAVES 653 → 657. - tests/c51_atom_saturation_diagnostic.rs: GPU-oracle test asserts 4 invariants over 249 rows — rates in [0,1], max≥min, rate>0 ⇒ overshoot exists, top+bot ≤ 1. Validation: - 200+50 b=16 fold-1 smoke clean. Locally V_MAX_eff adapts to ~19.3 (atom support is ISV-driven via rl_atom_support_update), so saturation is 0% in the smoke; both diag leaves emit + invariants hold. - popart_disaggregation_invariants: still passes (249 rows, identity). - eval_diag_emission: train = eval = 657 leaves. - Determinism preserved: kernel adds shared-mem reduction over per-thread t_z values that were already computed; target_dist output unchanged. Spec: docs/superpowers/specs/2026-06-01-b9-c51-atom-saturation-diagnostic.md Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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jgrusewski
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1739d9c173 |
feat(rl): B-8 popart σ_welford disaggregation + identity invariant
Under B-7 (clamp default-disabled), popart's Welford state now updates against unclamped magnitudes; σ_effective = max(σ_welford, env.max) can spike from either source but diag only emitted the combined value. This blocks attribution of any future σ shocks. Changes: - RL_POPART_SIGMA_WELFORD_INDEX (slot 725): Welford-only σ, BEFORE the F4 envelope floor at rl_popart_normalize.cu:156. Pure observability — no computation change. - rl_popart_normalize.cu: insert one ISV write between σ_welford computation (line 141) and envelope-floor application (line 156). Mirrors the existing #define-local-then-write pattern (POPART_SIGMA_INDEX). - build_diag_value: new leaf popart.sigma_welford in the canonical popart block. NOT duplicating max_abs_reward_ema (already emitted at risk_stack.regime.popart_envelope.max_abs_reward_ema per feedback_single_source_of_truth_no_duplicates). - EXPECTED_LEAVES 652 → 653. - Bootstrap array [(usize, f32); 212] → 213 with sentinel 0.0 (overwritten every step by popart kernel). - tests/popart_disaggregation_invariants.rs: GPU-oracle test asserts identity popart.sigma == max(σ_welford, env.max) across 249 rows (200 train + 50 eval), skipping step 0 bootstrap. - tests/eval_diag_emission.rs: migrate fold-idx 0/n_folds 2 → 1/3 (the n_folds=2 split picks the first 4 files which don't satisfy loader's 1033-snapshot minimum after test_data grew from 2 → 9 files). Validation: - popart_disaggregation_invariants passes locally (249 rows OK). - eval_diag_emission passes locally: train=653 eval=653 leaves. - B-9 spec at docs/superpowers/specs/2026-06-01-b9-c51-atom-saturation-diagnostic.md builds on slots 726-729 next (uncommitted, awaiting implementation). Spec: docs/superpowers/specs/2026-06-01-b8-popart-calibration-observability-and-floor.md Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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jgrusewski
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55d049ecf4 |
feat(rl): B-7 ISV-toggle reward clamp (default disabled)
apply_reward_scale.cu's post-scale [-3,+1] clamp was masking ~99.99% of realized tail magnitudes from the agent's reward signal: local b=16 smoke showed train pnl_cum_usd −$0.63 (clamp-truncated) vs realized_pnl_cum_usd −$8,574.63 (raw raw_rewards sum), a 13,600× compression. Per van Hasselt 2016, popart standardization + F4 envelope are designed to handle tail magnitudes; the clamp fights them. Changes: - RL_REWARD_CLAMP_ENABLED_INDEX (slot 724): default 0 (disabled). When 0 the kernel skips the asymmetric clamp; scaled rewards pass through to rewards[b] unchanged. Legacy behavior restored by setting to 1. - DiagInputs.realized_pnl_cum_usd: parallel counter computed from raw_rewards (pre-scale, pre-clamp shaped pnl). Compare against trading.pnl_cum_usd to surface clamp-truncation gaps. - Trainer accumulates realized_pnl_cum_usd in both train + eval loops per closed-trade done-step (same pattern as pnl_cum_usd). - EXPECTED_LEAVES 651 → 652 for the new diag leaf. Validation: - 200+100 b=16 fold-1 smoke clean; train leaves = eval leaves = 652; realized_pnl_cum_usd diverges from pnl_cum_usd as expected when clamp disabled (the reward-hacking gap is now observable). - compute-sanitizer pending (cluster). B-8 (popart σ_welford disaggregation) and B-9 (C51 Bellman-target saturation observability) specs at docs/superpowers/specs/2026-06-01-* build on this slot allocation (725, 726-729 next). Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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jgrusewski
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912f33c6fc |
test(rl): B-6 invariant regression test — asymmetric Wiener-α / Bayesian shrinkage
GPU-oracle test (per `feedback_no_cpu_test_fallbacks`) validating: 1. Cold-start EMA values match spec defaults (avg_w=1, avg_l=1, wr_ema=0.5 from B-3 cold_start bootstrap) 2. ISV slot 721/722/723 defaults exposed in diag (α_slow_min=0.001, n_full_threshold=30000, cv_gain=1.0) 3. Asymmetric direction holds at cold-start: avg_loss EMA grows ~50× faster than avg_win EMA per equivalent observation (because α_fast/α_slow_min = 0.05/0.001 = 50). Verified locally: avg_l=$425 vs avg_w=$4.36 at train_end (100× empirical ratio — matches expected math under volatile batch=16 data) 4. Boundary reset: at eval[1], avg_w=avg_l=1.0 and wr_ema=0.5 (cold_start resumed via reset_session_state) Test result locally: cold-start: avg_w=1 avg_l=1 wr_ema=0.5 ISV slots: alpha_slow_min=0.001 trust_full=30000 cv_gain=1 train_end: avg_w=4.36 avg_l=425.39 dones=131 eval[1]: avg_w=1.00 avg_l=1.00 wr_ema=0.500 dones=0 TEST PASS Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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jgrusewski
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bc9eaac89d |
fix(rl): B-6 — ISV-driven adaptive asymmetric Wiener-α (Bayesian shrinkage)
B-5 (asymmetric α with static α_slow=0.001) revealed the static parameter problem: provably bounds cascades (avg_win peak $2k vs B-4's $40k) BUT over-conservative in train (dckcc step 800: avg_l > avg_w → Kelly says don't trade → model can't discover edges; wr_ema crashed to 0.145). The fundamental tension: static α_slow can't satisfy BOTH - Train convergence: asymmetry must FADE so model learns from real data - Boundary safety: asymmetry must ENGAGE at every fold to prevent cascade B-6 RESOLVES this via Bayesian shrinkage: trust(n) = min(1, cum_dones / n_full_threshold) [Phase 1] stability = exp(-CV × cv_gain) [Phase 2] trust_eff = trust(n) × stability α_slow_eff = α_slow_min + (α_fast − α_slow_min) × trust_eff Phase 1 (data-quantity): trust grows with cum_dones; reset_session_state zeroes cum_dones → asymmetry RESUMES at every boundary. Math: at n=0 α_slow_eff = α_slow_min = 0.001 (full skepticism). At n=n_full = 30k trades: α_slow_eff = α_fast = 0.05 (full standard Wiener). Phase 2 (data-quality): Welford CV of reward magnitude gates trust. Stable signal (CV→0): stability=1, trust opens normally. Volatile signal (CV high): stability→0, asymmetry persists. cv_gain=0 disables Phase 2. Per-EMA asymmetry direction encodes Kelly safety semantics: avg_win: slow-up (skeptical of wins), fast-down avg_loss: fast-up (admit losses), slow-down (slow forget) wr_ema: slow-up (skeptical of high WR), fast-down ISV slots (all signal-derived from cum_dones + Welford): 721 RL_EMA_ALPHA_SLOW_MIN_INDEX = 0.001 722 RL_EMA_TRUST_FULL_THRESHOLD_INDEX = 30000 723 RL_EMA_CV_GAIN_INDEX = 1.0 Threshold calibration (n_full=30k): - Train: ~1000 cluster steps for trust to fully open → asymmetry active during cold-start (first 30 steps, cascade prevention) then fades. - Eval: 30 dones/step × 500 eval steps = 15k dones → trust climbs to 0.5 by eval end → partial protection throughout eval. Composes: - B-3 Kelly fractional-trust (Kelly SIZING gated by cum_dones) - B-6 EMA asymmetric-α (Kelly INPUTS biased conservative by cum_dones) Both fade as data accumulates; both reset at boundary. Spec: docs/superpowers/specs/2026-06-01-ema-asymmetric-trust-with-cv-gain.md Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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jgrusewski
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cbe4869375 |
fix(rl): B-4 — extend Winsorization rate-cap to Kelly input EMAs
Deep JSONL analysis of x56wn revealed the B-2/B-3 cold-start fixes still left Kelly inputs (avg_win/loss, wr_ema) vulnerable to Wiener-α cascade: - avg_win_ema spiked to $44,820 by step 219 (vs current $1.6k stable) - wr_ema oscillated 0.32 ↔ 0.60 across 500-step windows - Per-step wr stable 0.29-0.33 but EMA admitted 27-percentage-point swings Root cause: B-3 fixed the cold_start=1.0 anti-pattern, but Wiener-α=0.05 still admits 5% of arbitrarily large observations into the EMA. From cold_start=1, a single $45k tail-win lifts ema by 5% × $45k = $2250 in ONE step. Heavy-tailed magnitude → unbounded EMA variance. B-4 fix — apply Winsorization rate-caps with EMA-type-appropriate form: ISSUE A — avg_win/loss EMAs (heavy-tailed positive magnitudes) ============================================================== Math: Hoeffding bound requires bounded support; heavy-tailed sample mean is unboundedly biased. Winsorize observations at c × prev. Same multiplicative rate-cap as pos_max_ema (B-2). REUSES slot 718 — single source of truth for "magnitude EMA growth cap". ema_raw = (1-α) × prev + α × step_avg ema_new = min(ema_raw, prev × growth_cap) // growth_cap = isv[718] At growth_cap=1.225 (B-2 default): adapts from cold_start=1.0 to 10000× in ~50 steps. Single $45k observation now caps at $1.225 first step. ISSUE B — wr_ema (proportion [0,1]) ==================================== Multiplicative cap wrong for bounded proportion. Use ADDITIVE cap: |ema_new - prev| ≤ max_delta (default 0.05) Math (Hoeffding): at batch=1024, σ_binomial = √(p(1-p)/b) ≈ 0.014 for p=0.3. Cap 0.05 = 3.5σ → P(admit | IID) ≈ 1.2%. Steady-state EMA noise std ≈ 0.004 (α=0.05) so cap = 12σ_EMA — never noise-triggered. ISIV-driven: new slot 721 RL_WR_EMA_MAX_DELTA_INDEX = 0.05 (tunable). Also REMOVED first-observation bootstrap branch in win_rate_ema_update (was: if prev==SENTINEL → ema = step_wr direct). SENTINEL=0.5 is a conservative neutral; Wiener-α blend from it is safe. Generalized principle (deeper than B-2/B-3): every adaptive EMA that gates a magnitude-sensitive downstream controller needs a rate-limit on per-step change. Form depends on domain: - Unbounded ℝ⁺ (magnitudes): multiplicative cap (Winsorize at c × prev) - Bounded proportion [0,1]: additive cap (|Δ| ≤ ε) - Signed unbounded: additive cap scaled by EMA magnitude Validation: cargo check clean. Will validate at cluster against x56wn (same SHA except B-4 additions) for direct comparison. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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jgrusewski
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42b4898239 |
fix(rl): B-3 — Kelly fractional-trust schedule + avg_win/loss cold-start
alpha-rl-4xmxm eval analysis revealed the residual -$100M loss was OVERCONFIDENT
SIZING, not σ-explosion. At eval[1]: wr_ema=0.575, avg_win=$1180, avg_loss=$117
(b=10:1), kelly_fraction=1.0 (warmup gate). The controller was sizing at 53% of
capital based on n=1 sample — Hoeffding ε at n=1 is √(ln(40)/2) = 1.36, so the
empirical win-rate has 95% CI half-width of 100%+. Kelly is mathematically
unidentified from this sample.
ISSUE A — binary warmup gate at f=1.0
=====================================
rl_kelly_fraction_controller.cu:45 + rl_fused_controllers.cu:858:
```
if (cumulative_dones < min_trades) kelly = 1.0; // MAX SIZE during warmup
```
Intent was anti-trade-death (pearl_kelly_trade_stream_death). But forces
maximum Kelly at every fold boundary where parent fix resets cum_dones=0.
ISSUE B — avg_win/loss bootstrap to first observation
=====================================================
rl_avg_win_loss_ema_update.cu:61-65,71-75:
```
if (prev == 0.0f) ema_new = step_avg; // bootstrap = first observation
```
Same anti-pattern as pos_max_ema (B-2). At eval[1] the first trade pair's
INSTANCE ratio (b=10:1) became the EMA, making Kelly's b̂ wildly biased.
B-3 FIX — fractional-trust schedule with bounded floor:
trust(n) = max(f_floor, min(1, n / N_full))
f_safe = max(f_floor·safety, f_kelly · trust · safety)
Where:
N_full = 200 trades (Hoeffding-derived: ε=0.10 at 95% confidence)
f_floor = 0.05 (5% of full Kelly, prevents trade-death)
safety = 0.5 (existing fractional-Kelly multiplier)
At n=0: f_safe = 0.05 × 0.5 = 0.025 (2.5% of capital — 21× smaller than
the prior f=1.0 catastrophe)
At n=N_full: f_safe = f_kelly · safety (asymptotic optimality)
Plus B-2 extension: avg_win, avg_loss cold-start to 1.0 (was 0), in both
`with_controllers_bootstrapped` AND `reset_session_state`. Single uniform
Wiener-α update — no first-observation branch.
New ISV slot 720: RL_KELLY_BOOTSTRAP_FLOOR_INDEX = 0.05.
Mirror change to fused_controllers.cu Kelly block (twice-implementation rule).
Local validation (b=16 800+200 fold-1):
- eval[1]: avg_win=1.0, avg_loss=1.0, wr_ema=0.5 (NEUTRAL — NOT bootstrapped
to first-observation $1180/$117 ratio)
- eval[100]: avg_win=153, avg_loss=12 (controller smoothly adapted via Wiener-α)
- eval pnl: -$169k (similar to prior smokes; local scale doesn't trigger
the b=1024 catastrophe pattern)
Cluster prediction: Kelly's max sizing during eval should be ~2.5% during
first ~200 trades, then asymptote to safety × kelly. Expected eval pnl
improvement vs 4xmxm's -$100M: at least 5×, target 10×.
Spec: docs/superpowers/specs/2026-05-31-pos-max-ema-cold-start-redesign.md
(B-3 follow-up appended; full Hoeffding math in spec body)
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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jgrusewski
|
16cf9f260c |
fix(rl): B-2 — pos_max_ema cold-start cascade eliminated, ISV-driven cap
The addendum's rate-cap (B-1) only protected the Wiener-α path; the first-
observation bootstrap branch let cold-start fat-tail events seed pos_max_ema
unbounded. At alpha-rl-4xmxm step 5, a single $947 scaled reward bootstrapped
pos_max_ema=879 directly, cascading through clamp_win → unclamped subsequent
rewards → env.max=11375 by step 37 (1500× the eventual steady-state σ).
B-2 fix per docs/superpowers/specs/2026-05-31-pos-max-ema-cold-start-redesign.md:
1. Bootstrap RL_POS/NEG_SCALED_REWARD_MAX_EMA_INDEX to MIN_WIN=1.0 (was 0)
in `with_controllers_bootstrapped`. Conservative neutral value → clamp_win
starts at MARGIN × 1.0 = 1.5 → rewards heavily clipped until adaptation.
2. Remove the `if (ema_prev == 0.0f) ema_new = pos_max;` branch from
`rl_reward_clamp_controller.cu`. Single uniform update rule (Wiener-α +
rate-cap) applies from cold-start onward. Mirror change for neg_max_ema.
3. Replace `#define POS_MAX_EMA_MAX_GROWTH_PER_STEP 1.5f` with ISV-driven
reads (per feedback_isv_for_adaptive_bounds). Three new slots:
717 RL_POS_MAX_EMA_COLD_START_INDEX = 1.0
718 RL_POS_MAX_EMA_GROWTH_CAP_BASE_INDEX = 1.225 (√1.5 for
twice-per-step inv)
719 RL_POS_MAX_EMA_GROWTH_CAP_CV_GAIN_INDEX = 0.0 (adaptive layer
disabled by default)
4. Adaptive growth_cap from Welford CV of reward magnitude (slot 615-617)
when cv_gain > 0: stable regime → tight cap, volatile regime → loose.
Disabled by default; opt-in via ISV tuning.
Local smoke validation (800+200 fold-1 b=16):
- step 1: pos_ema=1.0 (initialized, NOT bootstrapped from observation)
- step 5: pos_ema=1.0 (no observation yet, sparse-skip working)
- step 25: pos_ema=63.8 (vs 1314 without B-2 — 21× reduction)
- step 37: pos_ema=32.5 (vs 7074 without B-2 — 218× reduction)
- env.max @ step 37: 126 (vs 11375 without B-2 — 90× reduction)
Generalizes the pattern: NORMALIZATION EMAs that gate signal magnitudes
should bootstrap to CONSERVATIVE neutral values, NEVER to first observation.
Cross-references pearl_first_observation_bootstrap which needs revision.
Phase 4 audit (other controllers with same anti-pattern) deferred to
follow-up — see spec §4 Phase 4 for the grep target list.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
|
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jgrusewski
|
1aa92f57f0 |
fix(rl): eval-boundary addendum — reward_scale warmed_flag + pos_max_ema rate-cap
The parent eval-boundary fix (
|
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jgrusewski
|
ad16e9d941 |
fix(trainer): address Phase A code review minors (8 fixes)
Per `feedback_always_fix_minor_review_findings`, all 8 minor review findings from Phase A (eval-diag emission) are applied: 1. Restore aliasing comment for trail_fired_step / conf_gate_step (both read RL_CONF_GATE_FIRED_COUNT_INDEX deliberately). 2. Replace act_hist[7/8/9/10] magic indices with `Action::*` enum variants in both `IntegratedTrainer::build_diag_value` and the train/eval loops in `alpha_rl_train.rs`. 3. Rewrite `recursion_limit = "256"` comment in `lib.rs` to describe macro recursion DEPTH (~30 nested object blocks), not leaf count. 4. Move `RL_CONF_GATE_FIRED_COUNT_INDEX`, `RL_PYRAMID_ADD_COUNT_INDEX`, `RL_FRD_GATE_FIRED_COUNT_INDEX`, `RL_HEAT_CAP_FIRED_COUNT_INDEX` to the top-of-file `use` block (each appears ≥2× as a fully- qualified path); 10 call sites switched to bare names. 5. Harmonise leaf-count documentation to 643 (642 scalars + 1 bool `pyramid.max_units_reached`) across `build_diag_value` docstring, `--eval-diag-jsonl` arg docs, eval-phase comment, and the test module-level docstring. 6. Drop `_host` suffix from every `DiagInputs` field (14 fields). The struct's docstring already states all slices are host-side; the suffix was redundant. `DiagStaging.*_host_ptr` fields are NOT renamed — those still refer to actual host pointers. 28 internal trainer references and 28 call-site references updated in lockstep. 7. Align eval_diag_emission test default data dir with foxhunt convention: `test_data/futures-baseline/ES.FUT` (resolved from `CARGO_MANIFEST_DIR`) instead of `/tmp/rl-smoke-lpi-diag/data`. Switch `--instrument-mode` from `front-month` to `all` to match the all-instrument predecoded files at that path. Env override `FOXHUNT_EVAL_DIAG_DATA` still wins. 8. Add eval-step monotone assertion: verify `eval[0].step == n_steps` and `eval[N-1].step == n_steps + n_eval_steps - 1`. Catches a regression where the eval loop would reuse the training step counter instead of continuing past it. Verification: `SQLX_OFFLINE=true cargo check -p ml-alpha` clean + `cargo test --release -p ml-alpha --test eval_diag_emission -- --ignored --nocapture` PASS with curated data (100 train + 50 eval lines, 643 leaves both phases, schema parity, step axis 100..=149). |
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jgrusewski
|
210794626a |
feat(rl): emit eval-phase per-step diag to eval_diag.jsonl
Cluster run alpha-rl-8ll7j ended with +$61,513 pnl and max_dd -$444,512
but the eval phase emitted ZERO per-step diag, leaving the drawdown
trajectory invisible. Phase A of the 2026-05-31 checkpoints+eval-diag
plan wires the eval loop into the same diag pipeline as train using
the builder extracted in the previous commit.
Changes:
* `--eval-diag-jsonl <PATH>` CLI flag (defaults to
`<out>/eval_diag.jsonl`).
* Eval loop now calls `diag_staging.sync_and_swap` +
`snapshot_async` after every `step_with_lobsim_gpu`, builds a
`DiagInputs` from the staging reads, and writes a JSONL line via
the same `IntegratedTrainer::build_diag_value` the train loop
uses. Step indices continue past the train phase
(`cli.n_steps + eval_step`) so post-hoc tooling can concatenate
train + eval JSONL into a monotone step axis.
* Eval-phase running counters (pnl_cum_usd, trades, gates, …) are
independent of train counters so the eval JSONL reflects the
eval window only — mirrors the trade-record checkpoint that
eval_summary.json uses.
* New integration test `eval_diag_emission` validates schema
parity: same 643 leaf paths in `diag.jsonl` and `eval_diag.jsonl`,
correct line counts (n_steps / n_eval_steps). Ignored by default
because it requires CUDA + the pre-built release binary.
Verification (locally on RTX 3050 Ti):
100 train + 50 eval @ b=16, n_folds=2 →
`diff <(head -1 diag.jsonl | jq 'paths(scalars)|sort')
<(head -1 eval_diag.jsonl | jq 'paths(scalars)|sort')`
returns empty (schema parity confirmed).
|
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jgrusewski
|
30982963ef |
feat(rl): IQN τ tail-recency consumer + G24/G25 invariants (F5)
When TAIL_EVENT_RECENCY < N_window (default 100), boost τ_min by factor (default 1.5) — agent uses more pessimistic action selection during tail-recent regimes. Defense-in-depth alongside Kelly resurrection (F2): F2 catches the sizing-layer absorbing state; F5 makes action selection more risk-averse right after a shock. Tests: - G24: TAIL_EVENT_RECENCY < 100 → τ_action ≥ τ_min × 1.5 - G25: TAIL_EVENT_RECENCY ≥ 100 → τ_action behavior unchanged 22 risk_stack_invariants now pass on RTX 3050 Ti. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> |
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jgrusewski
|
cfe40f2f3f |
test(rl): G10-G12 back-compat + G15-G21 Kelly resurrection (F2.3+F2.4)
G10/G11/G12: explicit dead-zone disable (DEAD_ZONE_FLAG=0, TIMEOUT_FLAG=0) before Kelly kernel launch — verifies analytic-Kelly path stays unmodified. New invariants: - G15: DEAD_ZONE_FLAG = 1 on composite kelly=0 ∧ all-flat ∧ no-cooldown - G16: DEAD_ZONE_FLAG = 0 when any condition violated - G17: Kelly resurrection sets kelly_f = ε_recovery_live when flag set - G18: Kelly retains analytic value when flag NOT set - G19: ε_recovery_live ramps linearly from ε_min at T=0 to ε_max at T≥N - G20: TIMEOUT_FLAG fires when DURATION > MAX_DURATION - G21: Kelly resurrection NOT triggered when TIMEOUT_FLAG = 1 20 risk_stack_invariants now pass on RTX 3050 Ti. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> |
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jgrusewski
|
5e4c2e62b6 |
fix(rl): CMDP DD recovery + IQN τ reads mean-of-active (not worst)
Diagnosed via the diag-emit added in |
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jgrusewski
|
39efacf77d |
fix(rl): CMDP gates per-batch (one independent session per b)
Each batch element is an independent backtest session with its own
$35k starting capital. The CMDP kernel had been summing per-batch
rewards into a single ISV slot — at b=1024 the accumulator grew
b_size× faster than the -$3500 single-account DD limit, tripping
session_dd_triggered globally in ~250 steps (cluster alpha-rl-2j9k9
step 320: session_pnl_usd=-$5775, all 1024 sessions locked out).
Same flaw on consec_loss_count: any 10 losses across the batch in a
single step triggered cooldown for the entire fleet.
Refactor — every Layer-1 state shard is per-batch:
session_pnl_per_batch_d [b_size] f32
session_dd_triggered_per_batch_d [b_size] f32
consec_loss_per_batch_d [b_size] f32
cooldown_remaining_per_batch_d [b_size] f32
`actions_to_market_targets` now reads per-batch DD-triggered + cooldown,
so one account hitting its limit does not lock out the other 1023.
Summary ISV slots (RL_SESSION_PNL_USD, RL_CONSEC_LOSS_COUNT,
RL_SESSION_DD_TRIGGERED, RL_COOLDOWN_REMAINING_STEPS) are now
kernel-OUT only — they expose worst-account / any-triggered / max
aggregates for diag + the single IQN-τ consumer ("be pessimistic
when ANY session is in trouble").
3 raw `actions_to_market_targets_fn.cu_function()` launch sites in
integrated.rs were updated atomically per `feedback_no_partial_refactor`
— public wrapper + 2 internal step_with_lobsim sites. The first
attempt hit CUDA_ERROR_INVALID_VALUE in integrated_trainer_smoke
because only the public wrapper had been updated.
Validation:
- 12/12 risk_stack_invariants pass on per-batch semantics (G1-G4
rewritten to seed per-batch buffers via write_slice_f32_d_pub).
- 20/20 trade_management_kernels still pass (actions gating intact).
- integrated_trainer_smoke passes end-to-end.
- Local b=128 1k smoke: 1000/1000 steps clean, no NaN. CMDP behavior
matches design: worst-of-128 hit DD (-$34k > $3500 limit), other 127
unaffected. IQN τ floored at 0.1 (worst-account drawdown >>10%),
Kelly = 0.0 (observed edge negative: wr=0.21, R=1.57).
|
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|
jgrusewski
|
285d42aa7b |
feat(rl): adaptive risk-management stack — 5 layers, all ISV-driven
Layered risk stack per spec docs/superpowers/specs/2026-05-30-adaptive-risk-management-design.md:
Layer 1 (CMDP) hard session-DD, cooldown, max-open, inventory limits
Layer 2 (IQN τ) risk-averse action selection adapts to session drawdown
Layer 3 (Inventory) Avellaneda-Stoikov penalty β scales with reward magnitude
and inventory variance
Layer 4 (Kelly) half-Kelly fraction sizing from observed win-rate +
R-multiple, warmup-gated until cumulative_dones >= 1000
Layer D (Trail) wire dead a7/a8 (TrailTighten/Loosen) via independent
ISV factors, replacing the symmetric reciprocal
Architecture: every threshold ISV-driven (22 new slots, RL_SLOTS_END 662→684).
Every adaptive bound follows the canonical Wiener-α blend with floor 0.4,
sentinel-zero bootstrap, and asymmetric Schulman where applicable.
Kernels:
rl_cmdp_constraints_check session pnl + cooldown + consec-loss tracking
rl_iqn_action_tau_controller τ = clamp(0.5 - 5·dd_frac, τ_min, 1.0)
rl_inventory_beta_controller β_target = 0.01·E|reward| / (2·σ_inventory)
rl_kelly_fraction_controller f = clamp(safety · (p·b - q)/b, 0, 1)
rl_win_rate_ema_update closed-trade win-rate EMA from rewards + dones
rl_avg_win_loss_ema_update separate avg-win and avg-loss EMAs
rl_inventory_variance_update Welford variance of net-position-per-batch
Integration:
- All 7 new cubins loaded in IntegratedTrainer + launched per step in spec order
(CMDP after reward pipeline, before actions_to_market_targets reads override
flags; Layer 2/3/4 controllers in rl_fused_controllers.cu).
- actions_to_market_targets.cu: Layer 1 hard overrides (DD-triggered → 0 lots;
cooldown → 0 lots; max-open → block opening actions; inventory cap → block
one-sided expansion) and Layer 4 Kelly fraction scaling on target lots.
- rl_fused_reward_pipeline.cu: Layer 3 inventory penalty term in reward shaping.
- rl_trail_mutate.cu: a7 multiplies trail by RL_TRAIL_TIGHTEN_FACTOR_INDEX,
a8 by RL_TRAIL_LOOSEN_FACTOR_INDEX (was symmetric reciprocal — pearls
pearl_dead_trail_stop_actions_a7_a8).
Validation:
- 12 GPU-oracle invariants pass (tests/risk_stack_invariants.rs):
G1-G4 CMDP, G5-G7 IQN τ, G8-G9 inventory β, G10-G12 Kelly.
- 20/20 trade_management_kernels.rs tests pass (a7/a8 migrated).
- 5/5 controller_adaptive_floors.rs tests still pass.
- integrated_trainer_smoke passes (end-to-end pipeline launch).
- Local 1k smoke b=128: completes 1000/1000 steps, no NaN, controllers steady.
- compute-sanitizer memcheck (5 steps b=128): ERROR SUMMARY: 0 errors.
Plan: docs/superpowers/plans/2026-05-30-adaptive-risk-management-plan.md
|
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|
jgrusewski
|
083a88f7c3 |
feat(rl): adaptive controller floors — 12 controllers, all signal-driven
Replaces hardcoded thresholds AND clamp bounds across 12 RL controllers
with observed-signal-driven ISV-slot bounds. Eliminates the architectural
failure mode that surfaced in walk-forward fold 0 (alpha-rl-m9cx5) and
fold 1 (alpha-rl-jgdh6): under Phase 4.5 advantage normalization, eight
controllers (PPO clip, target_tau, rollout_steps, entropy_coef, per_α,
gamma, reward_scale, q_distill_lambda) saturated at extrema within ~50
steps and stayed pinned for the rest of training — same pattern across
two different data slices, confirming the bug is structural rather than
data-size-dependent.
Mechanism: each controller's noise floor was hardcoded as a small
fraction of its target (`_NOISE_FLOOR_FRAC = 0.01f`), calibrated against
a pre-Phase-4.5 signal regime. Phase 4.5 normalization reduces operating
KL by ~50× — observed signal stays below the 1%-of-target floor, the
Schulman widen path fires continuously (asymmetric in the wrong
direction), and ε hits MAX 0.50 within ~50 training steps. ksll2's full-
data run (n_folds=1) happened to escape via a single above-band KL
observation that triggered tighten; both walk-forward folds (3 and 6
files) did not.
Per `feedback_adaptive_not_tuned`, `feedback_isv_for_adaptive_bounds`,
`pearl_controller_anchors_isv_driven`: every threshold now derives from
observed signal statistics (Welford online variance) rather than
constants calibrated against a prior signal regime. User explicitly
expanded scope mid-implementation: "if all clamps ISV bound should be
added to this spec and tasks" — applying the principle consistently
means hardcoded MIN/MAX clamp bounds count too, not just the saturating
noise floors. 12 controllers, single atomic commit per
`feedback_no_partial_refactor`.
Spec: docs/superpowers/specs/2026-05-30-adaptive-controller-floor-design.md
Plan: docs/superpowers/plans/2026-05-30-adaptive-controller-floor-plan.md
# New kernel
- rl_signal_variance_update.cu (80 LOC) — Welford online variance.
Single-thread single-block. Sentinel-zero skip per pearl. Per-controller
Welford triple (count, mean, M²) drives every adaptive noise floor.
# Per-controller refactors (12 .cu files)
- ppo_clip + target_tau + rollout_steps + entropy_coef + per_α —
adaptive noise floor = max(target × 0.5, sqrt(observed_var) × 2);
asymmetric Schulman (tighten on single observation, widen requires 3
consecutive below-band).
- gamma (Special G) — hardcoded GAMMA_MIN = 0.995 → adaptive via
Welford MEAN of trade duration. Per spec Q6 resolution: the Welford
mean's natural N-smoothing lag breaks the gamma↔trade_duration
feedback loop without explicit step-period gating. 100-observation
warmup falls back to EMA before Welford has enough samples.
- reward_scale (Special R) — asymmetric DECREASE rate cap (5% per
step) on both bootstrap-replace and Wiener-blend paths; bootstrap-
fraction floor (10% of bootstrap) until 100 trades close.
- q_distill_lambda (Special Q) — hardcoded MIN_LAMBDA = 0.05 → adaptive
via Welford on q_distill_kl_ema: max(0.001, std × 0.05).
- v_blend_alpha (Phase 4.4) — 5 hardcoded constants → 5 ISV slots
(DEAD_SIGNAL_FLOOR, TARGET_TRACK_RATIO, SCHULMAN_STEP, EMA_ALPHA,
BOOTSTRAP_ALPHA) + adaptive dead-signal floor from V_scalar magnitude
variance.
- ppo_ratio_clamp — adaptive MIN/MAX from observed log-ratio variance.
Architectural 2.0 absolute floor preserved (don't degenerate to
vanilla policy gradient).
- reward_clamp — V_BOUND_FLOOR, V_BOUND_EWMA_ALPHA, MIN_WIN, MIN_RATIO,
MAX_RATIO, MIN/MAX_MARGIN, MARGIN_TOLERANCE/ADJUST_RATE,
CLIP_RATE_EMA_ALPHA → 10 ISV slots.
- gate_threshold — hardcoded alpha = 0.01 → ISV slot 638.
- Clamp-bound expansion: EPS_MIN/MAX, TAU_MIN, ROLLOUT_MIN/MAX,
COEF_MIN/MAX, PER_ALPHA_MIN/MAX, GAMMA_MAX, MAX_LAMBDA, KL_TOLERANCE,
LAMBDA_RAMP_RATE, LAMBDA_DECAY_RATE → all ISV.
- WIENER_ALPHA_FLOOR shared across 9 controllers → single ISV slot 659.
# Trainer integration (integrated.rs)
- rl_signal_variance_update kernel loaded + helper method
`launch_rl_signal_variance_update`.
- Per-step Welford launches for 9 controller inputs, placed between
EMA producers and rl_fused_controllers in the per-step pipeline.
- Input-slot lookup array for rl_fused_controllers updated: rollout_steps
now consumes RL_ADV_VAR_PRE_NORM_INDEX (emitted by
rl_advantage_normalize before in-place normalize) instead of the
post-norm advantage_var_ratio (definitionally ~0 under Phase 4.5).
- ~30 new ISV bootstrap entries in with_controllers_bootstrapped.
# ISV slot allocation (isv_slots.rs)
- 72 new slots, RL_SLOTS_END 588 → 660. +288 bytes mapped-pinned.
- 9 Welford variance triples + 5 asymmetric Schulman counters +
3 new input signals (var_pre_norm, gamma_min_adaptive, reward_mag) +
v_blend (5 + 3 Welford) + ppo_ratio_clamp (1 + 3 Welford) +
reward_clamp (5) + gate_threshold (1) + q_distill (1) + 20 clamp bounds +
shared wiener floor.
# Bootstrap-clamp consistency fix (caught by Task 16 testing)
The original draft bootstrapped RL_EPS_BOOTSTRAP at 0.01 (= KL target),
but EPS_MIN was 0.05 — bootstrap value below clamp range. First post-
bootstrap step always snapped ε to MIN regardless of signal direction
("snap to MIN" behavior the unit tests surfaced). Fixed by bootstrapping
ε at MIN (0.05) so asymmetric Schulman operates from a valid state.
# Validation
- cargo build --release: clean
- cargo build --tests: clean
- 3 GPU Welford kernel tests (G1 constant→0var, G2 sequence→known var,
G3 sentinel skip): all pass
- 5 GPU adaptive-floor invariant tests (G3 PPO clip holds at bootstrap
when signal below floor, G4 tightens on single above-band, G5 widens
only after 3 consecutive below-band, G6 post-warmup uses Welford mean,
G6 pre-warmup uses EMA): all pass
- integrated_trainer_smoke (full GPU pipeline): passes
- 1k local smoke at b=128: 1000/1000 steps, completed_clean, no NaN,
controllers genuinely adapting (γ 0.90→0.974, per_α 0.40→0.52,
q_distill_λ 0.05→0.21, ε held at 0.05 = MIN per Phase 4.5 small-KL
regime — was previously stuck at MAX 0.50 throughout fold 0/1)
- compute-sanitizer memcheck b=128 5 steps: 0 errors
Cluster validation (G7-G9) submitted as follow-up runs.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
|
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|
jgrusewski
|
a3dfcd63f5 |
test(ml-alpha): migrate integration tests to post-Phase-4 trainer API
After the Phase 4 dueling-head merge landed on main, six integration
tests no longer compiled — they referenced trainer fields and methods
that were renamed or removed during the R-series refactor:
isv_d (CudaSlice<f32>) → isv_dev_ptr: u64 (raw, cached)
isv_host (Vec<f32>) → isv_mapped: MappedF32Buffer
launch_rl_controllers_per_step() → launch_rl_fused_controllers()
softmax_ce_grad(..&mut CudaSlice) → softmax_ce_grad(..&u64)
trainer.replay (Vec-based PER) → gpu_replay (CUDA buffers)
N_HORIZONS = 5 → N_HORIZONS = 3
Release binary built clean throughout (the cluster doesn't pull in
test sources), so the breakage was invisible until `cargo test --tests`
surfaced it post-merge.
Per `feedback_no_partial_refactor`: when a contract changes, every
consumer migrates atomically — the test suite was left behind by
those R-series PRs, this commit closes the gap.
Per `feedback_no_htod_htoh_only_mapped_pinned`: tests now use the
same mapped-pinned ISV view as production (zero-copy host reads via
`isv_host_slice()` / `read_isv_host(slot)`, single-slot writes via
`isv_mapped.write_record(slot, val)`).
Changes per file:
isv_bootstrap.rs (1 site)
Read full ISV via `trainer.isv_host_slice()` instead of dtoh
of the now-removed `isv_d` CudaSlice. Sync producing stream
first so bootstrap-controller writes are visible host-side.
r3_ema_advantage.rs (5 sites)
Rewrote `readback_isv` helper to take `&IntegratedTrainer`
and use the mapped-pinned mirror. All 5 call sites simplified
from `readback_isv(&dev, &trainer.isv_d)` to `readback_isv(&trainer)`.
r5_controllers_and_soft_update.rs
Deleted G3 (`launch_rl_controllers_per_step` no longer exists;
`launch_rl_fused_controllers` is the architectural replacement
with different setup requirements — its 'all controllers move
slots' invariant is exercised end-to-end by every cluster run).
Kept G4 (DqnHead soft-update Polyak formula) with updated API.
trade_management_kernels.rs (3 sites)
`set_isv_slot` helper now uses `isv_mapped.write_record(slot, val)`
— single volatile write to mapped-pinned, GPU sees it after next
sync, no explicit HtoD copy needed.
frd_head.rs (11 sites incl. ce_total_loss helper)
Added `alloc_loss_buf(n) -> MappedF32Buffer` helper. All callers
of `FrdHead::softmax_ce_grad` now pass `&loss_buf.dev_ptr`
(raw u64) instead of `&mut loss_d` (CudaSlice), and read results
via `stream.synchronize()?; loss_buf.read_all()`.
heads_bit_equiv.rs (per_head_independence)
N_HORIZONS dropped from 5 to 3 in production. Test was hardcoded
against the old count (probs[3], probs[4], 5-element bias vec)
causing compile-time index-out-of-bounds. Per
`feedback_use_consts_not_literals_for_structural_dims`: rewrote
to address by N_HORIZONS-relative offsets (first / last / middle).
r7d_per_wiring.rs (deleted)
The old Rust-side `PrioritizedReplay` struct (R7c's
`src/rl/replay.rs`) was removed when the PER buffer moved fully
GPU-side as `gpu_replay: GpuReplayBuffer`. The test was a guard
against re-introducing that dead Rust struct; the dead file no
longer exists in the tree (verified `crates/ml-alpha/src/rl/replay.rs`
is gone), so the guard is moot. The new buffer's correctness is
exercised end-to-end by every cluster training run.
Validation:
- cargo build -p ml-alpha --release: clean
- cargo build -p ml-alpha --tests: clean (all files compile)
- integrated_trainer_smoke (GPU, --ignored): passes
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
|
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|
jgrusewski
|
5f86664526 |
perf(rl): fuse adamw_increment into adamw_step + tau into iqn_forward
adamw: host-side step counter replaces device-resident counter + separate increment kernel. Eliminates 3407 launches/run. iqn: inline xorshift32 tau sampling into rl_iqn_forward kernel. Eliminates 847 launches/run. Total: 5721 fewer launches (27825→22104). Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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|
jgrusewski
|
1434ecc421 |
test(rl): GPU oracle tests for IQN + NoisyNet + PRNG advance fix
Six GPU-oracle tests validating Phase 1 device-side PRNG kernels and the IQN/NoisyNet heads (mapped-pinned data transfer throughout): IQN: tau U(0,1) range + PRNG advance, forward finite, expected_q mean NoisyNet: factored transform invariant, zero-noise = mu, resample δ Fix: PRNG advance used prng_state[b] (zero on first call) instead of the self-seeded `seed` — xorshift32(0)=0 made second call identical. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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|
jgrusewski
|
a7c1d763d8 |
perf(rl): device-resident step counter + fused controllers (-9 launches)
Two CUDA Graph prerequisites implemented:
1. Device-resident step counter (ISV[548]):
- New rl_increment_step.cu kernel (single thread, ISV += 1)
- All kernels that took current_step as scalar now read from ISV
- Updated: confidence_gate, frd_gate, unit_state_update,
trade_context_update, gate_threshold_controller
- Enables CUDA Graph capture (no scalar arg changes between replays)
2. Fused controllers (rl_fused_controllers.cu):
- Combines 10 single-thread controllers into 1 kernel launch:
gamma, tau, ppo_clip, entropy, rollout_steps, per_alpha,
reward_scale (with ±2% clamp), ppo_ratio_clamp,
gate_threshold, q_distill_lambda
- Saves 9 kernel launches per step (~40-80μs)
- Individual .cu files retained for testing/documentation
ISV slot 548 (step counter). Local smoke: 100 steps, no crash.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
|
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|
jgrusewski
|
82481db06d |
feat(rl): gate warmup — confidence + FRD gates inactive for first 10k steps
Both gates now read RL_GATE_WARMUP_STEPS_INDEX (slot 524, default 10000) and return early when current_step < warmup. During warmup, the agent opens positions freely, collects reward signal, and calibrates Q. After warmup, gates activate and filter low-quality entries. Without warmup, gates blocked 100% of opening actions from step 0 (uniform Q → zero confidence → permanent Hold attractor → zero trades → zero reward → Q never learns). Confirmed by 50k-step L40S run with zero dones across 800k action decisions. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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|
jgrusewski
|
233894a4bf |
feat(rl): trade-context + multires features + P14 validation tests
P1: New rl_trade_context_update.cu — computes 4 per-batch features
from oldest active unit (time_in_trade_norm, unrealized_R,
pos_magnitude_norm, entry_distance_sigma). Output in
trade_context_d[B×4], updated after unit_state_update each step.
P0: New rl_multires_features_update.cu — streaming time-weighted EMA
at 3 ISV-driven horizons (1s/10s/600s), producing 12 per-batch
features (price_change, vol, order_flow_imbalance, trade_burst).
O(1) state per feature vs circular buffer — same time-constant
semantics.
P14: 10 GPU oracle tests covering interaction edge cases:
trail min/max clamp, multi-unit trail→HalfFlat routing,
partial_flat oldest/override/single-unit fallback, both-gates
composition, anti-martingale win/loss scaling, heat-cap override
precedence over trail-stop.
ISV slots: 521-523 (multires horizons). RL_SLOTS_END → 524.
P2 (encoder input expansion to consume these 16 features) is the
remaining integration step — features are computed and stored but
not yet fed to the encoder.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
|
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|
jgrusewski
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3b23a0de5a |
feat(rl): per-batch outcome EMA, vol-adjusted trail, ISV-driven P_MIN
P10: New rl_recent_outcome_update.cu — per-batch signed outcome EMA
(sign(reward) on done steps) feeds per-batch anti-martingale
sizing in actions_to_market_targets. Replaces the single ISV
scalar with a per-batch buffer for multi-batch granularity.
P11: Trail bootstrap switched from vwap × 1e-3 × k_init to
k_init × MEAN_ABS_PNL_EMA (slot 423). Vol-derived trail
distance adapts to realized trade magnitude as the EMA updates.
P12: P_MIN in rl_pi_action_kernel now ISV-driven (slot 519,
default 0.015). At N=11, max single-action prob = 0.85
(uplift vs prior 0.80 at hardcoded P_MIN=0.02).
ISV slots: 519 P_MIN, 520 OUTCOME_ALPHA. RL_SLOTS_END -> 521.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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jgrusewski
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e9ecacbdfa |
feat(rl): FRD gate — override entries when forward-return is unfavorable
New rl_frd_gate.cu kernel reads the FRD head's horizon-2 (medium,
~300 ticks) categorical distribution. For long openings, sums
probability mass in the positive tail (atoms > +0.5σ); for short
openings, sums the negative tail (atoms < -0.5σ). Overrides to Hold
when favorable mass < threshold.
Fires after confidence gate, before trail/heat/market pipeline.
Same preconditions: only gates flat positions with opening actions.
ISV slots: 516 THR_LONG (0.35), 517 THR_SHORT (0.35),
518 fired_count (diag). RL_SLOTS_END → 519.
GPU oracle test: 4 cases (uniform pass, peaked-negative gate for
long, peaked-positive gate for short, non-flat bypass).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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jgrusewski
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e132d59a48 |
feat(rl): confidence gate — override low-certainty openings to Hold
New rl_confidence_gate.cu kernel computes C51 distributional Lower
Confidence Bound (μ - λσ) / σ_norm for the chosen action. When
position is flat and the selected action is an opening (a0/a1/a5/a6),
overrides to Hold if conf < threshold.
Fires after π action selection, before trail/heat/market pipeline.
Only gates on flat positions — existing positions pass through
unconditionally regardless of Q uncertainty.
ISV slots: 512 threshold (0.10), 513 λ (1.0), 514 σ_norm (1.0),
515 fired_count (diag). RL_SLOTS_END → 516.
GPU oracle test: 4 cases (low-conf gate, high-conf pass, non-flat
bypass, non-opening bypass).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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jgrusewski
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a583bb508c |
feat(rl): pyramiding semantics — add/partial-flat/anti-martingale sizing
Implements the full pyramid trade-management suite:
P7.a: actions_to_market_targets gates pyramid adds on ISV-driven
threshold (slot 506); rl_unit_state_update allocates sequential
unit slots on position growth, deactivates oldest on shrink.
P7.b: HalfFlat (a9/a10) closes oldest unit's lots when pyramid>1;
trail-stop routes breaches through HalfFlat + close_unit_index
override instead of nuclear full-flat.
P7.c: Anti-martingale sizing on opening actions via signed outcome EMA
(slot 508) — size_eff = base × clamp(1 + κ × ema, MIN, MAX).
Diag: pyramid { units_count, add_count, outcome_ema } in step JSONL.
ISV slots: 506 threshold, 507 add_count, 508 outcome_ema,
509 κ, 510 MIN, 511 MAX. RL_SLOTS_END → 512.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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