4c1ed1d953
Diagnostic Smoke 2 (lob-backtest-sweep-kw7f6 at d2d34b6d4) confirmed
empirically:
- Per-horizon logit distributions near-uniform (mean spread 0.05, std
spread 0.02), explaining mean_run_len ratio = 1.04x (vs target >=10x)
- heads_w1 inspection: 100% dense at off-bucket positions (32,768/32,768
nonzero), magnitude ratio off/in ~= 1.0
- GRN kernel grep confirmed heads_w1 is the SOLE remaining HIDDEN_DIM-
reading path bypassing bucket-routing (heads_w_skip already restricted;
heads_w2/gate/main operate within HEAD_MID_DIM only)
Extends the existing heads_w_skip block-diagonal 3-layer defense to
heads_w1 with mask shape [N_HORIZONS x HEAD_MID_DIM x HIDDEN_DIM]:
- heads_w1_mask_init_kernel at transition: zero off-bucket params +
build mask
- heads_w1_zero_off_bucket_kernel on Adam (m, v) moments at transition
(prevents momentum from re-introducing off-bucket weights)
- heads_w1_grad_mask_apply_kernel per-step: zero off-bucket gradient
before Adam
- heads_w1_zero_off_bucket_kernel per-step post-Adam: belt+suspenders
for eps drift
GPU oracle tests verify mask init, grad mask apply, and post-Adam
invariance under simulated training (3 new tests for the 3-D heads_w1
shape; mirrors the existing heads_w_skip oracle tests).
ml-alpha lib: 33 passed.
GPU oracle tests on RTX 3050 sm_86: 19 passed (16 prior + 3 new).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Foxhunt
Production HFT trading system in Rust.
Architecture
The workspace contains 32 crates organized as follows:
Core Libraries (16)
| Crate | Purpose |
|---|---|
trading_engine |
Order processing, FIX 4.4, IB TWS, SIMD, RDTSC timing |
risk |
VaR, Kelly, circuit breakers, kill switches, compliance |
risk-data |
Risk data types and shared structures |
trading-data |
Trading data types |
ml |
DQN Rainbow, PPO, TFT, Mamba2, ensemble inference |
ml-data |
ML data types and feature definitions |
data |
Market data ingestion and storage |
backtesting |
Replay engine, strategy tester |
adaptive-strategy |
Ensemble execution, microstructure analysis |
common |
Shared types, resilience, error handling |
storage |
S3 and local model storage |
model_loader |
Model serialization and loading |
market-data |
Market data feed handlers |
database |
PostgreSQL access layer (SQLx) |
config |
Configuration management |
tli |
CLI commands and tooling |
Services (8)
| Service | Purpose |
|---|---|
backtesting_service |
gRPC backtesting service |
broker_gateway_service |
FIX routing, broker connectivity |
trading_service |
Core trading operations |
ml_training_service |
Model training orchestration |
data_acquisition_service |
Market data acquisition |
trading_agent_service |
Autonomous trading agents |
api_gateway |
gRPC API gateway with auth |
web-gateway |
Axum REST + WebSocket gateway |
Frontend
web-dashboard/ -- React 19 + TypeScript + Vite + TradingView charts.
Building
# Check compilation (no PostgreSQL required)
SQLX_OFFLINE=true cargo check --workspace
# Run tests for a specific crate
SQLX_OFFLINE=true cargo test -p <crate> --lib
# Clippy
SQLX_OFFLINE=true cargo clippy --workspace
ML Models
Four production model architectures on Candle v0.9.1 with CUDA:
- DQN Rainbow -- Deep Q-Network with prioritized replay, dueling heads, noisy nets
- PPO -- Proximal Policy Optimization with GAE and LSTM policies
- TFT -- Temporal Fusion Transformer for multi-horizon forecasting
- Mamba2 -- State space model for sequence prediction
Each model has a standalone trainer and a UnifiedTrainable adapter for the hyperopt pipeline.
Infrastructure
- Git: Gitea at
git.fxhnt.ai(Tailscale-only), Scaleway DEV1-S - Observability: OpenTelemetry OTLP (env
OTEL_EXPORTER_OTLP_ENDPOINT) - Database: PostgreSQL with SQLx offline mode for CI
License
Proprietary. All rights reserved.