Replace per-bar GPU forward passes with chunked batch inference (1024 bars
per chunk). This reduces ~90K individual CUDA kernel launches to ~88 batched
forward passes — ~1000× fewer GPU round-trips.
Changes:
- Add DQN::batch_greedy_actions(&self) for immutable batched forward+argmax
- Add RegimeConditionalDQN::batch_greedy_actions with per-regime-head batching
- Add DQNTrainer::convert_to_state_vec (CPU-only, skips GPU tensor allocation)
- Add PortfolioTracker::set_position_direct for backtest state sync
- Rewrite hyperopt backtest loop: chunked batching with portfolio state
updates between chunks (1024-bar granularity ≈ 17h of 1-min data)
Portfolio features (last 3 of 54 dims) are refreshed between chunks via
set_portfolio_for_backtest(), keeping position/PnL/exposure accurate at
chunk boundaries while batching inference within each chunk.
2640 tests pass, 0 clippy warnings.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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