test(aprender-train): H4 CPU forward bisect — CUDA path is the residual root cause (PMAT-CODE-PRETRAIN-INIT-LOAD-004)

[noahgift]

TL;DR

H4 LOCALIZED TO CUDA PATH. CPU aprender::Transformer::forward on populated Qwen 0.5B produces SENSIBLE logits (clean argmax=9370, peak-to-mean=5.68). The bug is in CUDA upload or GPU kernels — not in populate, CPU forward, or tied-embedding fall-through.

Empirical bisection result

CPU forward on populated Qwen 0.5B (fresh APR, BF16-correct):

populated: 290/290 tensors
logits: n=151936 nan=0 inf=0
        min=-15.03 max=11.72 mean=-3.33 std=2.65
        peak-to-mean = 5.68
        argmax = 9370 (specific, not flat)

CUDA eval_batch on same weights: val_loss > ln(vocab) (sub-random).

Same weights, same arch, different backend → CUDA path is the bug.

H4 component status

Component	Pre-this-PR	Post-this-PR
BF16 dtype tag	OPEN	FIXED #1 (PR #1601)
Populate (290/290)	OPEN	FALSIFIED — works ✓
CPU forward	OPEN	FALSIFIED — works ✓
Tied embedding fall-through	OPEN	FALSIFIED — works ✓
CUDA path	OPEN	CONFIRMED LIVE BUG

Three CUDA-side sub-hypotheses (next-cycle work)

• H4D.1: CudaTransformerTrainer::with_model upload distorts weights during H2D
• H4D.2: gpu_forward CUDA kernels (cuBLAS GEMM / RoPE / RMSNorm / fused attention) produce wrong outputs
• H4D.3: fused_cross_entropy_cuda reads wrong buffer location (off-by-stride in logits_buf)

Each is testable via CPU↔CUDA forward parity on populated Qwen.

Five-Whys

1. Why val_loss=18.55 > ln(vocab)=17.21? CUDA forward produces sub-random logits despite CPU forward producing sensible ones on same weights.
2. Why CUDA differs from CPU? Bug in upload, kernels, or xent buffer.
3. Why didn't falsifiers catch this? CUDA path was validated by convergence on synthetic data + from-scratch — both blind to forward-pass parity vs CPU.
4. Why ship CPU bisect, not CUDA fix? Pinpointing at the backend boundary is cheapest narrowing. Without this, next agent re-derives.
5. Why does this matter? Next falsifier cascade has a tight scope (3 sub-hypotheses, all CUDA-specific).

Test plan

• cargo test -p aprender-train --lib falsify_h4_cpu_forward: PASS
• rustfmt --check: clean
• cargo clippy -p aprender-train --lib -- -D warnings: clean
• LIVE on RTX 4090 with fresh Qwen APR: peak-to-mean=5.68, argmax=9370

SHIP-TWO impact

• MODEL-1 ship %: unchanged at 91%
• MODEL-2 ship %: unchanged at 57% — but H4 is now FULLY LOCALIZED to CUDA path. CPU is provably correct. Next-cycle bisection has a tight scope.

Out-of-scope follow-ups

PMAT-CODE-PRETRAIN-CUDA-FORWARD-001:

• CPU↔CUDA forward parity falsifier on populated Qwen
• Bisect H4D.1 (upload), H4D.2 (kernels), H4D.3 (xent buffer)
• Fix root cause; flip MODEL-2 ship % 57% → ≥58%

Files

• crates/aprender-train/src/train/pretrain_real.rs (+110, falsify_h4_cpu_forward_qwen_logits_sensible)

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