- DQN: adapter creation, deterministic inference, varied inputs - PPO: adapter creation, deterministic inference, short input padding - TFT: sequence buffering, valid prediction after warmup - Mamba2: sequence buffering, valid prediction, deterministic SSM - Ensemble: all 4 models -> EnsembleCoordinator -> trading decision - Smoke: full pipeline with 10 sequential predictions, stability check This establishes the production baseline proving the ML pipeline works end-to-end with all 4 models contributing to ensemble decisions. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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5.4 KiB