ca7dfa9f08
SECOND race condition from block_dim (1,1,1)→(32,1,1) change: c51_loss_reduce had 32 threads all computing sum and writing to total_loss[0] simultaneously. On sm_90 (H100) → corrupted loss → NaN in C51 gradient → graph_mega replay hangs. This kernel runs INSIDE graph_mega (submit_forward_ops_main), called twice (MSE reduce + C51 reduce). Both corrupted. Also fixed stochastic_depth_rng in previous commit (same issue, runs in pre-replay). Co-Authored-By: Claude Opus 4.6 (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;