8c50e68fe7
After CUDA Graph replay with event tracking re-enabled, the total_loss and grad_norm CudaSlice buffers have stale write events from capture. cudarc's memcpy_dtoh calls device_ptr() which waits on these stale events, causing CUDA_ERROR_INVALID_VALUE on H100. Fix: use raw_device_ptr (ManuallyDrop guard) + cuMemcpyDtoH_v2 for the 2 scalar readbacks (8 bytes total — legitimate GPU exit for metrics). Stream is synchronized before readback, so event ordering is guaranteed. 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;