05a184168f
The guard cleanup agent incorrectly removed the backward dX overflow clamp from relu_mask_kernel. This clamp is a LEGITIMATE bf16 overflow prevention at the type boundary — identical to the forward-pass bias kernel clamping. The dX GemmEx writes bf16 output. When the f32 accumulated sum exceeds bf16 max (~65504), it writes Inf. The relu_mask ±500 clamp converts Inf to a finite value, preventing cascade through the backward chain. Also reverted the outside-graph params cast (the in-graph capture is correct). Remaining issue: grad_norm drops to 0 in epoch 2+ with f32 master weights. The model learns in epoch 1 (grad_norm=0.004) but stagnates in epoch 2+. Investigating CUDA graph replay of f32→bf16 params cast. 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;