c260dca8bd
Atomic step 5 of β migration. SP14 EGF producer chain now fires
ONLY from the experience collector (commit c691bd381).
Training-time launches removed; the collector-native chain is the
single production caller.
Trainer's pub(crate) launcher methods retained (no Rust dead-code
warnings on pub(crate) — atomic-rollback potential preserved).
Oracle tests in sp14_oracle_tests.rs exercise the SAME kernels
directly via load_cubin / load_function, not through these launchers
— deletion of the launchers would not affect oracle coverage. They
stay for the possibility that a future curriculum stage reverses
the rollout-only signal-quality assumption.
gradient_hack_detect (per-epoch circuit breaker) unchanged —
lockout-counter decrement is one-per-epoch by design.
Verification: cargo check clean; sp14_oracle_tests 2/2 non-GPU pass
(7 GPU tests ignored on RTX 3050 Ti host); L40S smoke validation
pending.
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;