00ae84dd88
Strip all 413 #[allow(dead_code)] annotations from 139 files and remove the actual dead code they were suppressing: unused struct fields (and their constructor sites), unused methods/functions, and entire dead structs. Key removals: - trading_engine compliance: ~50 dead structs/fields across audit, reporting, SOX modules - trading_service: dead execution engine fields, broker routing, paper trading methods - ml_training_service: dead TLS validation (~340 lines), GPU state, monitoring fields - backtesting_service: dead model cache, TLS validation, TradeSignal fields - risk: dead VaR engine fields, safety coordinator fields, position tracker fields - adaptive-strategy: dead ensemble methods, regime detection, sizing functions 147 files changed, -4264 net lines. Workspace compiles with 0 errors. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
ml_training_service
Model training orchestration and lifecycle management for the Foxhunt HFT trading system. Manages training jobs for DQN, PPO, TFT, Mamba2, TLOB, and Liquid models with progress tracking, resource allocation, and model artifact storage.
Building
# Default (minimal features)
cargo build --release -p ml_training_service
# With GPU acceleration (requires CUDA)
cargo build --release -p ml_training_service --features gpu
# With mock training data (testing only, bypasses database)
cargo build --release -p ml_training_service --features mock-data
Features
| Feature | Default | Description |
|---|---|---|
minimal |
Yes | Minimal ML feature set for financial models |
gpu |
No | SIMD GPU acceleration (requires CUDA) |
debug |
No | Additional debug logging |
mock-data |
No | Use mock training data instead of PostgreSQL |
Configuration
The gRPC listen port is set via the GRPC_PORT environment variable. Prometheus metrics are exposed on port 9094.
PostgreSQL (via sqlx) is used for job metadata, training history, and state management. Set the connection string with DATABASE_URL.
Running
GRPC_PORT=50053 DATABASE_URL="postgresql://user:pass@localhost:5432/foxhunt_training" \
./target/release/ml_training_service serve
Testing
# Unit tests (offline, no database required)
SQLX_OFFLINE=true cargo test -p ml_training_service --lib
# Integration tests (requires running PostgreSQL)
cargo test -p ml_training_service