79fce72afb
ROOT CAUSE of 3100ms adam_child: adam_update_kernel and grad_norm_finalize_kernel were shared between post_aux_child and adam_update/forward children. On Hopper, CUfunction sharing across child graphs corrupts kernel state. Fix: load utility cubin from separate CUmodule for post_aux child, giving it isolated adam_update_post_aux, grad_norm_finalize_post_aux, and scale_f32_post_aux handles. Zero cross-child CUfunction sharing for these kernels. Also: convert memset_zeros to raw cuMemsetD8Async in IQN (3 calls), IQL (1), Attention (1) — eliminates cudarc device_ptr_mut() overhead during graph capture. 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;