Integration of 7 hive agents: - gpu_replay_buffer: 103 Candle refs → 0 (14 new CUDA kernels) - gpu_action_selector: 27 refs → CudaSlice API - signal_adapter: 26 refs → 3 new CUDA kernels - gpu_experience_collector: 5 refs → CudaSlice output - gpu_weights+iql+guard: 13 refs eliminated - DQN forward: new forward_only_kernel for inference - VarMap: F32 contiguous enforcement, fast-path extraction New modules: - ml-core/cuda_autograd: GpuTensor, GpuVarStore, GpuLinear, GpuAdamW - ml-ppo/cuda_nn: CudaLinear, CudaLSTM, CudaAdam, networks - ml-supervised/gpu_tensor: GpuTensor + cuBLAS for KAN, Diffusion cudarc 0.17.3 → 0.19.3 (via candle 0.9.1 → 0.9.2) safetensors 0.4 → 0.7 Zero errors, zero warnings workspace-wide. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
foxhunt-e2e
End-to-end testing framework covering service orchestration, gRPC clients, database integration, ML pipeline, and complete trading workflows.
Key Types
E2ETestFramework-- core orchestratorServiceManager-- automated service startup/shutdownDatabaseTestHarness-- transaction-isolated DB testingMLPipelineTestHarness-- mock ML model inference
Test Categories
- Service startup, shutdown, recovery
- gRPC client connections, streaming, error handling
- ML inference, training, ensemble predictions
- Trading workflows, order lifecycle, risk, emergency stop
Usage
SQLX_OFFLINE=true cargo test -p foxhunt-e2e --lib