b25ce1dcbf
The GPU PER replay buffer had a hardcoded 4 GB MAX_BYTES limit that rejected the auto-sizer's 10M-entry proposal on H100 (80 GB VRAM). Now per_max_buffer_bytes() computes 20% of total VRAM (min 1 GB) and flows through OptimalReplayConfig → DQNConfig → GpuReplayBufferConfig so both subsystems agree on the budget. Also fixes misleading regime detection log (indices 211/219 → 40/41) and renames dqn_config_2025 → dqn_default_config. Co-Authored-By: Claude Opus 4.6 <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;