d98ec8d343
cuMemcpyDtoHAsync with non-pinned host pointers blocks the CPU on CUDA 13 / H100 driver 580+ until ALL pending GPU work completes. With graph_forward + aux_ops + adam queued, this caused multi-minute hangs between training steps. Fix: allocate 12 bytes of pinned (page-locked) host memory via cuMemHostAlloc(DEVICEMAP) for the 3 scalar readbacks (loss, mse_loss, grad_norm). Pinned memory enables true async DtoH — CPU returns immediately, GPU copies when it reaches that point in the stream. 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;