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Phase E.4.A Task 6: tiny CUDA kernel that pushes a state[state_dim] vector into slot `head_idx` of a circular window buffer [K, state_dim]. Host tracks head_idx and zeros buffer on episode reset. This is the GPU-side append primitive that the smoke binary's per-step inference will call (T7) before Mamba2 over the buffer (T8). GPU smoke (alpha_window_push_circular_writes_to_indexed_slot): writes state_a at slot 0, state_b at slot 2, verifies non-targeted slots stay zero. PASS. docs/isv-slots.md: documents kernel as slot-agnostic per kernel-audit-doc hook requirement. Co-Authored-By: Claude Opus 4.7 <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;