The previous "auto-detect" logic forced CPU which was wrong — GPU is
faster for forward/backward even with parallel trials (DQN/PPO use
<350MB of 24GB VRAM across 7 threads).
Changes:
- Remove --device flag, always require CUDA GPU
- Add DQNTrainer::new_with_device() to share CUDA context across trials
- Propagate hyperopt device to internal DQN trainer (was ignoring it)
- PPO/DQN adapters error on missing GPU instead of silent CPU fallback
- Downgrade batch-size clamping from warn to debug
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
21a8e3410f