5309d4bee5
LAYOUT FINGERPRINT BREAK: pre-SP15 checkpoints WILL NOT LOAD after this commit. Greenfield OK per spec Q1. Per spec §6.5: dd_pct (slot 406, written by Task 1.3 dd_state_kernel) gets concatenated to the trunk forward input as the last dim. Eval-time policy SEES drawdown context on every forward pass; Phase 3 teachings can condition on dd_pct directly via state, not just reward modulation. New kernel `dd_pct_concat_kernel.cu` produces a [B, state_dim_padded + 1] buffer whose leading state_dim_padded columns equal the input states_buf and whose +1 last column equals isv[DD_PCT_INDEX=406] broadcast across batch. Pure scatter-copy (no atomicAdd per feedback_no_atomicadd). layout_fingerprint_seed extended with 'TRUNK_INPUT_DD_PCT=sp15_phase_1_5' marker — FNV1a hash changes; old checkpoints fail to load with the existing layout-mismatch error path (same fail-fast that fired on the SP4 / SP14 layout breaks). Phase 1.5 lands kernel + launcher + layout fingerprint marker + GPU oracle test only. Trunk consumer migration (re-pointing forward_online to consume the concat buffer + bumping s1_input_dim from 48 → 49 + propagating through GRN encoder, VSN gate input, bottleneck path, and backward dx scratch) is deferred to a follow-up atomic commit per feedback_no_partial_refactor — matches the established Phase 1.1-1.4 precedent (kernels + launchers verify in isolation first; consumer migration is a load-bearing change touching the GRN encoder, VSN partition boundaries, fxcache schema, and backward gradient flow). GPU oracle test `dd_pct_concat_kernel_writes_last_column` validates B=4, raw state_dim=48, state_dim_padded=128: leading 128 columns of each output row match the input states (including pad zeros), and the 129th column equals isv[DD_PCT_INDEX]=0.42 broadcast across all 4 rows. Test passes on local RTX 3050 Ti (sm_86) in 1.62s. cargo test -p ml --lib --features cuda: 945 passed / 14 failed — same 14 failures pre-existing on the parent commit `c6fd4b4b2` (Task 1.4 partial baseline); zero introduced by this commit. Per spec §6.5 step 7 (trunk-grounding behavioral test): Phase 4 L40S smoke verifies dd_pct propagation at production scale via the existing layout-fingerprint-mismatch fail-fast on cold-start of any pre-SP15 checkpoint. The follow-up Phase 1.5.b commit that lands the consumer migration adds the explicit trunk-grounding KL test alongside the forward_online wiring. Touched: - crates/ml/src/cuda_pipeline/dd_pct_concat_kernel.cu (new) - crates/ml/build.rs (+1 cubin manifest entry) - crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs (+SP15_DD_PCT_CONCAT_CUBIN + launch_sp15_dd_pct_concat + TRUNK_INPUT_DD_PCT layout fingerprint marker) - crates/ml/tests/sp15_phase1_oracle_tests.rs (+1 GPU oracle test) - docs/dqn-wire-up-audit.md (+1 Phase 1.5 entry) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
ml
10-model ML ensemble for the Foxhunt HFT system, built on Candle v0.9.1.
Models
- DQN (Rainbow) — deep Q-network with prioritized replay, dueling heads, noisy nets
- PPO — proximal policy optimization with GAE, LSTM policies, clip-higher
- TFT — temporal fusion transformer for multi-horizon forecasting
- Mamba2 — state space model for sequence prediction
- Liquid Networks — biologically inspired networks for non-stationary data
- TLOB — transformer-based limit order book analysis
- KAN — Kolmogorov-Arnold networks
- xLSTM — extended LSTM architecture
- TGGN — temporal graph neural network
- Diffusion — diffusion-based generative model
Key Modules
ensemble— model ensemble coordination and confidence aggregationhyperopt— PSO-based hyperparameter optimization with per-model adapterstrainers— unified training loops (DQN, PPO, supervised)inference—InferenceAdaptertrait for predictioncheckpoint— model checkpointing and restorationevaluation— walk-forward evaluation pipeline
Usage
use ml::dqn::DQN;
use ml::ppo::PpoTrainer;