c90de98594
Phase C.5a — additive infrastructure for the aux trunk wire-up. Allocates saved-fwd buffers (h_s2_aux, h_aux1, h_aux2), gradient buffers (6× aux_trunk_*_grad), accumulator (dh_s2_aux_accum), and dedicated Adam launcher (launch_aux_trunk_adam_update) reading β1/β2/ε/LR/grad-clip from ISV[444..449). No contract change. No call sites for the new launcher yet. C.5b atomically wires these in. Phase C.5 was split (authorized 2026-05-08) after the original implementer flagged ~600-800 LOC scope across 4 files with correctness windows. C.5a is purely additive; C.5b is the genuine ~300 LOC atomic migration. 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;