d980fdedf7
Task 7 — Counterfactual Experience Augmentation: Every timestep writes BOTH original AND mirror experience to output. Mirror action: exposure_idx → (b0_size-1) - exposure_idx (L100↔S100). Mirror reward: -reward. Output buffers are 2x for counterfactual. Always active — no enable_ flag. Doubles effective data diversity. Task 20 — Lottery Ticket Pruning: lottery_ticket_mask kernel: zeros pruned weights in f32 + bf16 after Adam. lottery_ticket_compute_mask kernel: magnitude threshold → binary mask. At pruning epoch (50): read all weights, sort by |w|, bottom 70% → mask=0. After that: mask applied every training step (one kernel launch). Invalidates CUDA graphs on mask creation (new step structure). Enable_ flag removal: ALL enable_ conditionals removed from hot paths. One production path. - enable_domain_randomization → removed (always randomize) - enable_mirror_universe → removed (always mirror odd epochs) - enable_vol_normalization → removed (always normalize) - enable_anti_lr → removed (always anti-intuitive LR) - enable_gradient_vaccine → removed (always project gradients) - enable_causal_intervention → removed (always run interventions) - enable_adversarial_self_play → removed (always saboteur active) - enable_counterfactual → never added (always counterfactual) Domain randomization GPU kernels: removed enable_jitter and enable_dr parameters from CUDA kernel signatures. Kernels always randomize. Co-Authored-By: Claude Opus 4.6 (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.