Per-component gradient clipping: - 2 new CUDA kernels (dqn_clipped_saxpy, dqn_clip_grad) - CQL gradient isolated into separate scratch buffer - Budget allocation: C51=70%, CQL=15%, IQN=10%, Ens=5% - Dynamic budget — inactive components' share goes to C51 Spectral norm extended to all 10 weight matrices: - Was trunk-only (W_s1, W_s2), now covers all heads - 16 u/v power iteration buffers, batched GOFF sync-back - Uniform sigma_max, end-to-end Lipschitz bounded Bug fixes from 9-agent audit: - Backtest episode reset: all 8 fields (was 5), max_equity updated before floor check - gradient_clip_norm unified: 10.0 everywhere (was 10.0 vs 1.0) - entropy_coefficient: Option<f64> → f64, single default 0.001 - Close price: unwrap_or(1.0) → direct indexing (no silent wrong rewards) - step_count: only increments during training (was incrementing on inference) - Quantile loss: single CUDA context (was 3×), silent fallbacks removed - MaybeNoisyLinear: single-variant enum removed → direct NoisyLinear - Budget fractions: exported as pub(crate) constants, referenced not hardcoded Monitoring: - Per-component gradient Prometheus gauges (C51 raw, combined) - Diagnostic logging every 1000 steps Tests: 7 new gradient budget tests, 1 gradient bounds smoke test All 488 tests pass (359 ml-dqn + 129 ml) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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