bf4d0c899f3da92f15a45d52128836a56da614b9
URGENT correctness fix surfaced by Task 13 implementer. Bug: training-time Phase 2 dispatch sites (cfc_step_per_branch_fwd at ~3139, h_mag_per_bucket for Controller D at ~3211-3212) read self.trunk.bucket_*_d which are zero-initialized at trunk construction and only populated via load_checkpoint. The Phase 1→2 transition populates a SEPARATE BucketRoutingMetadata owned by the trainer (self.bucket_routing_metadata) but never syncs it into the trunk fields. With zero-init bucket_dim_k, the per-branch kernel's uniform predicate `tid >= bucket_dim_k[branch]` early-returns ALL threads -> Phase 2 silently no-ops during training, Smoke 1 fails before producing signal. Fix: at transition, DtoD-copy metadata buffers into trunk fields BEFORE the `Some(metadata)` move (so `metadata.*` borrows remain valid): - metadata.bucket_channel_offset_d -> trunk.bucket_channel_offset_d - metadata.bucket_dim_k_d -> trunk.bucket_dim_k_d - metadata.bucket_id_per_channel_d -> trunk.bucket_id_per_channel_d - metadata.heads_w_skip_offset_d -> trunk.heads_w_skip_offset_d Trunk fields remain the single source of truth for both training-time dispatch AND checkpoint serialization. Total sync cost: 4 DtoD memcpys, ~256 bytes total at the one-shot transition (off the hot path). Verification: - `cargo check -p ml-alpha --all-targets`: clean - `cargo test -p ml-alpha --lib`: 33 passed, 0 failed - 3 read sites (perception.rs:3139, 3211-3212, 4725-4726) verified unchanged; all 4 new memcpy_dtod_async calls bracketed in the transition block (perception.rs:2224, 2234, 2244, 2254). - Block-diagonal heads grad-mask init (step 7) continues to read `metadata.bucket_id_per_channel_d` via `as_ref()` after the move; ordering preserved per pearl_canary_input_freshness_launch_order. 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.
Description
Languages
Rust
88.2%
Cuda
7.7%
Python
1.3%
Shell
1.1%
PLpgSQL
0.8%
Other
0.8%