Files
foxhunt/ml
jgrusewski d777d714b2 feat(liquid): wire Liquid CfC into trading service and gRPC trainer
Closes the integration gap between Liquid CfC and DQN/PPO by adding:
- LiquidTrainer with gRPC progress callbacks, early stopping, and
  checkpoint management (ml/src/trainers/liquid.rs)
- LiquidModel wrapper in enhanced_ml.rs for hot-loading from safetensors
- Ensemble weight rebalance: DQN 0.25, PPO 0.25, TFT 0.20, Mamba2 0.15,
  Liquid-CfC 0.15

Verified: 81 liquid unit tests + 3 integration tests + 211 trading_service
tests pass, 0 compile errors across workspace.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-23 01:14:33 +01:00
..

ml

Machine learning models for Foxhunt.

Models

  • DQN (Rainbow) -- Deep Q-Network with prioritized experience replay, dueling heads, noisy nets, double Q-learning
  • PPO -- Proximal Policy Optimization with GAE, LSTM policies, clip-higher option
  • TFT -- Temporal Fusion Transformer for multi-horizon time series forecasting
  • Mamba2 -- State space model for efficient sequence prediction
  • Liquid Networks -- Biologically inspired neural networks for non-stationary data
  • TLOB -- Transformer-based Limit Order Book analysis
  • Flash Attention -- Optimized attention implementation

Training

Two paths per model:

  1. Standalone trainer -- direct training loop (e.g., DQN::train, PpoTrainer)
  2. UnifiedTrainable adapter -- wraps models for the hyperopt pipeline (e.g., DQNTrainableAdapter, UnifiedTrainablePPO)

Inference

InferenceAdapterBridge connects models to the ensemble coordinator in adaptive-strategy. Each model exposes an InferenceAdapter trait for prediction.

Backend

  • Candle v0.9.1 -- VarMap, AdamW, loss.backward(), GradStore, opt.step(&grads)
  • CUDA required for training -- tested on RTX 3050 Ti 4GB, max batch size 230
  • CPU inference supported

Hyperopt

ArgminOptimizer (Particle Swarm Optimization) with per-model adapters: DQN, PPO, ContinuousPPO, TFT, Mamba2. Uses ParameterSpace trait for continuous parameter mapping.

ModelType Enum

15 variants: CompactDQN, DistilledMicroNet, DQN, RainbowDQN, MAMBA, TFT, TGGN, LNN, TLOB, PPO, Transformer, Mamba, LiquidNet, TGNN, Ensemble.

Key Modules

dqn, ppo, tft, mamba, liquid, tlob, flash_attention, ensemble, evaluation, inference, trainers, hyperopt, checkpoint, preprocessing, data_loaders, features, model_factory, training_pipeline, regime_detection, stress_testing, validation, bridge, common, metrics.

Testing

SQLX_OFFLINE=true cargo test -p ml --lib  # ~2009 tests