Files
foxhunt/crates/ml-alpha/tests
jgrusewski 6a3f45d872 refactor(ml-alpha): consolidate BCE — Kendall σ is THE BCE, wire MHA into trainer
Single source of truth for the multi-horizon BCE per the new
feedback_single_source_of_truth_no_duplicates pearl. Eliminates the
`bce_loss_multi_horizon_sigma.cu` / `loss_sigma.rs` duplication
introduced earlier today and folds the Kendall σ-weighting into the
canonical kernel.

Deletions:
  cuda/bce_loss_multi_horizon_sigma.cu              (folded into legacy)
  src/trainer/loss_sigma.rs                         (helper merged)
  tests/bce_sigma_numgrad.rs                        (subsumed)

Rewrites:
  cuda/bce_loss_multi_horizon.cu — replaced with σ-aware
    implementation; kernel function name kept as
    `bce_multi_horizon_forward_backward` so cubin symbol stays stable.
    NVIDIA-grade warp-shuffle reduce (4 warps, 1 cross-warp barrier);
    new args `log_sigma_h` (per-horizon Kendall σ logarithm) and
    `d_log_sigma_h` (its gradient).
  src/trainer/loss.rs — standalone helper updated to new 11-arg
    kernel signature. Exposes optional `log_sigma_h` in `BceInput`
    (None → zeros / passthrough Kendall init) and returns
    `mean_bce_per_h` + `d_log_sigma_h` in `BceOutput`.
  tests/bce_grad_finite_diff.rs — adds `log_sigma_h: None` to the
    test inputs; all 4 numgrad tests PASS unchanged.
  build.rs — drops `bce_loss_multi_horizon_sigma` entry from
    KERNELS. The single canonical `bce_loss_multi_horizon` cubin
    now contains the σ-aware kernel.

Wiring:
  PerceptionTrainer gains a single `pub mha: MultiHorizonAttention`
    field. Owns `log_sigma_h_d` + `grad_log_sigma_h_d` (and the rest
    of the multi-horizon attention path, anchored on Stage 2 to fully
    replace the legacy `attention_pool` path).
  step_batched + evaluate_batched BCE callsites now thread
    `mha.log_sigma_h_d` and `mha.grad_log_sigma_h_d` through the
    11-arg kernel signature.

This commit keeps the legacy `attention_pool` callsite in place; the
Stage 2 commit will replace it with `mha.pool` + `mha.inv_pool` +
`mha.moe` and delete the `attn_*` fields entirely.

Verified locally: ml-alpha builds clean with the cuda feature,
bce_grad_finite_diff (4/4) PASS on RTX 3050.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-18 14:59:12 +02:00
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