Docs Bedrock Validation (v0.79.0)

Bedrock Validation (v0.79.0)

Release: 0.78.0 "ASM CPU" → 0.79.0 "Bedrock Validation"
Checklist: 108 / 142 (76.1%) → 111 / 142 (78.2%)

This wave does not add a new compute backend. It hardens the Go CPU path, native persistence, transformer decode, and C-ABI so Lucy and Welvet bindings can trust train → save → reload → infer on real volumetric graphs.

What changed (summary)

Area Problem Fix
MHA layout Flat [B·S·D] was parsed as one long sequence (seq = len/D) mhaParseLayout trusts [B,S,D] when Shape[2] == d_model; legacy flat layouts still work
KV cache Training and autoregressive decode shared one policy; decode overwrote position 0 mhaPrepareKVForForward: reset on full-sequence train; keep cache for batch=1, seq=1, warm KV
Poly Talk KVOffset ignored in forward; += broken across steps seqBase = kvStart + b*seqLen; correct KVOffset advance; layout no longer stomps input.Shape[1]
MHA backward Q recomputed with RoPE but skipped Q/K RMS norm vs forward Backward matches forward norm order before RoPE
Dense Ternary save Checkpoint re-quantized from FP32 Master, not native path GetBitNetTernaryMatrix → packNativeTernaryToBitNetMatrix (same matmul as forward)
Signed low-bit I/O Int2/Int4/Ternary round-trip gaps on []uint8 persistence.go encode/decode aligned with CPU kernels
FP32 Master lifecycle Bindings could not mirror post-train native-only RAM LoomSyncInferenceWeights in welvet/cabi (461/461 C-ABI parity)
Regression harness False PASS (zeros/NaN); suite gaps Lucy [7] seven-layer CPU suite: 10 layer types × 21 dtypes × SC/MC × train × save/reload

Lucy seven-layer CPU suite

Run: cd lucy && go run . → [7] (or [0] for all layer types).
Log: lucy/lucy_testing_output/seven_layer.txt (reset each run).

Harness: lucy/examples/seven_layer/ — builds a volumetric JSON network per layer family, morphs all 21 dtypes, checks:

  • Forward SC ↔ MC parity (dtype tolerance)
  • Backward SC ↔ MC parity (10× fwd tol)
  • 50-epoch CPU training (loss decrease on MC path)
  • Save/reload before train and after train (forward match + native blob)
  • Grids 1³, 2³, 3³ (CNN1/2 skip 3³; CNN3 is 1³ only; Embedding at (0,0,0))

Layer types: Dense, SwiGLU, MHA, CNN1, CNN2, CNN3, RNN, LSTM, Embedding, Residual.

ASM: Dense forward only (UseAsmForward after JSON build); other types report asm N/A.

This suite is the long-term bedrock gate for CPU training and native checkpoints — broader than the older 18×21 permutation matrix because it includes multi-cell grids and end-to-end train + reload.

C-ABI (Welvet)

cd welvet/cabi/internal/check && go run .

Expect 461/461 (100.0%) functional overlap. The last gap closed in this release:

  • LoomSyncInferenceWeights — calls VolumetricNetwork.SyncInferenceWeights() when ReleaseFP32MasterWhenIdle is set (morph Master → native Versions, drop FP32 duplicate for inference RAM).

Python / TypeScript / WASM consumers that train outside LoomTrain should call this after morph or custom training if they mirror Go’s inference-only memory model.

What this release is (and is not)

You now have:

  • A deterministic CPU VM story that survives volumetric multi-cell layouts, not only single-stack benches.
  • Transformer decode aligned with training layout (KV + RoPE + Q/K norm).
  • Native dtype checkpoints that match forward for BitNet-style ternary and signed low-bit stores.
  • Full C-ABI name coverage for scanned poly/ surface (substring parity tool).

You do not yet claim:

  • Beating PyTorch/llama.cpp on model zoo size or raw tok/s.
  • ASM on MHA/SwiGLU/CNN (still Dense forward only).
  • Every seven-layer row green on every dtype at 1×1×1 (some unsigned / FP8 save bands remain harness-tuned; re-run [7] after pulls).

Next named target (unchanged): v0.8.0 "Edge-First" — thermal scheduling, UMA pinning, command-buffer graphing. ASM track: Dense backward, then SwiGLU / MHA / CNN (poly/README.md rollout queue).

Key source files

Topic Files
MHA layout / KV poly/mha_layout.go, poly/mha.go
BitNet CPU / ternary poly/bitnet_cpu.go
Persistence poly/persistence.go, poly/serialization.go
Master / inference RAM poly/weight_master.go
Seven-layer harness lucy/examples/seven_layer/*.go
C-ABI export welvet/cabi/acceleration_ext.go (LoomSyncInferenceWeights)

See also