a6acc25ec8b5ae44cc9ad7366a1d85473ae2fd83
Replaces multiplication-gating `advantages[b] = done * (ret - vt)` with
branch-gating `is_done ? (ret - vt) : 0.0f`. The multiplication form
fails on IEEE-754 `0 * Inf = NaN`: when any batch's encoder produces a
non-finite `v_tp1` early in training (random-init outliers across 128
parallel backtests), the prior expression propagated that non-finiteness
to ALL non-done batches' advantages via `0 * (Inf - vt) = NaN`, which
then broke `compute_advantage_rms` (sum of A² → NaN), PPO surrogate
(A/RMS → NaN → ratio×A → NaN → l_pi=NaN), and the aux head through
shared encoder gradient. Validated step-4 NaN bisect 2026-05-29.
The branch-gate is the canonical fix per IEEE-754 done-gating discipline:
- `is_done ? r : (r + γ × vtp1)` — non-finite vtp1 never enters a done
batch's ret, and non-done batches' ret can still be non-finite (which
is fine because the V regression envelope clamp salvages it back to
bounds via fmaxf/fminf NaN-passthrough semantics)
- `is_done ? (ret - vt) : 0.0f` — non-done batches get 0 unconditionally,
regardless of ret's finiteness
Smoke at HEAD (b4aadff75 = atomicAdd-fixed + V envelope ±10) with the
prior multiplication-gate: deterministic NaN at step 4 (l_pi/l_aux NaN,
l_v finite at 6.329).
Smoke at HEAD + this fix: clean trajectory through 110 steps:
- step 100: l_q=1.80, l_pi=0.49, l_v=0.37, dones=10, pnl=-$8.9k, wr=0.36
- step 109: l_q=1.81, l_pi=0.75, l_v=0.33, dones=13, pnl=-$9.9k, wr=0.37
l_v dropped from 6.33 to 0.33 because the envelope's ±10 bound is now
actually constraining V regression targets (previously the masking
behavior of ±200 envelope made high l_v "look healthy" while hiding the
underlying NaN propagation).
This finally unblocks the Phase 2.1 smoke gate and the Phase 2.2/2.3
implementations downstream.
Co-Authored-By: Claude Opus 4.7 <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%