New ml-core/cuda_autograd/reductions.rs:
- fused_stats_reduce: min/max/sum/sum_sq/count in single pass with
warp-level __shfl_down_sync + atomicCAS (20 bytes DtoH)
- argmax_flat: single u32 result (4 bytes DtoH)
- argmax_rows: per-row argmax for 2D data
- sum_reduce: standard tree reduction
- col_sum_reduce: per-column sum along rows
DQN trainer integration:
- collect_qvalue_statistics: 4 DtoH → 1 (single stats() call)
- compute_q_diagnostics_fused: replaces Candle sort/narrow pipeline
with argmax_rows + stats + col_sums (3 kernels, 3 readbacks)
- ReductionKernels lazy-initialized in training loop
All kernels compiled via compile_ptx_for_device (native cubin + disk cache).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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