47e67011c9
Closes the Phase 4 deferral. The 4 DqnBranches sub-launches now write
per-block engagement counts to 4 distinct ranges in
clamp_engage_per_block_buf; pearl_c_post_adam_engagement_check
aggregates all 4 ranges into one per-group rate-deficit EMA —
semantically equivalent to the pre-Phase-4 single-launch tracking.
Design: Option (b) sub-block offsetting, mirroring the existing
Curiosity pattern exactly. SP4_ENGAGE_EXTRA_BRANCHES_SUBLAUNCHES = 3
reserves 3 extra slots beyond Curiosity's tail; sub-launch 0 (Dir)
reuses the canonical DqnBranches slot 2; sub-launches 1/2/3 (Mag,
Order, Urgency) get extra slots 11/12/13. This keeps ParamGroup at
8 entries (no taxonomy growth, no 28 new ISV slot allocations).
SP4_ENGAGE_BUF_LEN: 11 → 14 × MAX_BLOCKS_PER_ADAM (45056 → 57344
i32 slots, +12 KiB on a non-hot-path mapped-pinned buffer).
Branch-to-offset mapping:
| Sub-launch | Offset constant | Slot | Buffer offset |
|------------|------------------------------------|------|---------------|
| Dir (b0) | SP4_ENGAGE_OFFSET_BRANCH_DIR | 2 | 8 192 |
| Mag (b1) | SP4_ENGAGE_OFFSET_BRANCH_MAG | 11 | 45 056 |
| Order (b2) | SP4_ENGAGE_OFFSET_BRANCH_ORDER | 12 | 49 152 |
| Urgency(b3)| SP4_ENGAGE_OFFSET_BRANCH_URGENCY | 13 | 53 248 |
pearl_c_post_adam_engagement_check generalized: a `multi_range` flag
covers both Curiosity (4 sub-launches W1/b1/W2/b2) and DqnBranches
(4 sub-launches Dir/Mag/Order/Urgency). Read AND zero-out paths use
the same flag — no duplication of branching logic.
Files changed:
- crates/ml/src/cuda_pipeline/sp4_isv_slots.rs: SP4_ENGAGE_EXTRA_
BRANCHES_SUBLAUNCHES const; SP4_ENGAGE_BUF_LEN formula extended;
SP4_ENGAGE_OFFSET_BRANCH_{DIR,MAG,ORDER,URGENCY}; layout test
updated to 14× MAX_BLOCKS_PER_ADAM
- crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs: launch_adam_update
branch sub-launches use new offsets; pearl_c_post_adam_engagement_
check aggregates DqnBranches multi-range
- docs/dqn-wire-up-audit.md: 2026-05-11 audit entry
Verification (passing):
- cargo check -p ml --tests --features cuda: 0 errors
- cargo test -p ml --lib sp4_isv_slots: 2/2 (engage buf layout asserts
14× + branch offsets correct)
- cargo test -p ml --lib sp21_isv_slots: 3/3
- sp20_aggregate_inputs_test: 12/12
- sp20_phase1_4_wireup_test: 2/2
- sp20_emas_compute_test: 4/4
- sp20_controllers_compute_test: 7/7
- sp21_per_trade_predicted_q_test: 3/3
Total: 33 tests, 0 failures. Behavioral gate: HEALTH_DIAG emits
per-branch engagement-rate-deficit EMAs in upcoming smoke run.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
ml
10-model ML ensemble for the Foxhunt HFT system, built on Candle v0.9.1.
Models
- DQN (Rainbow) — deep Q-network with prioritized replay, dueling heads, noisy nets
- PPO — proximal policy optimization with GAE, LSTM policies, clip-higher
- TFT — temporal fusion transformer for multi-horizon forecasting
- Mamba2 — state space model for sequence prediction
- Liquid Networks — biologically inspired networks for non-stationary data
- TLOB — transformer-based limit order book analysis
- KAN — Kolmogorov-Arnold networks
- xLSTM — extended LSTM architecture
- TGGN — temporal graph neural network
- Diffusion — diffusion-based generative model
Key Modules
ensemble— model ensemble coordination and confidence aggregationhyperopt— PSO-based hyperparameter optimization with per-model adapterstrainers— unified training loops (DQN, PPO, supervised)inference—InferenceAdaptertrait for predictioncheckpoint— model checkpointing and restorationevaluation— walk-forward evaluation pipeline
Usage
use ml::dqn::DQN;
use ml::ppo::PpoTrainer;