ADRs tagged ai¶
Auto-generated by scripts/docs/generate-adr-by-tag.sh. Edit ADR Tags: lines to update.
156 ADR(s) carry this tag.
| ID | Title |
|---|---|
| ADR-0020 | Tiny-AI scope covers all four capabilities |
| ADR-0021 | Training stack is PyTorch + Lightning with ONNX export |
| ADR-0022 | Inference runtime is ONNX Runtime via execution providers |
| ADR-0023 | Tiny-AI user surfaces span CLI, C API, ffmpeg, and training |
| ADR-0036 | Tiny-AI Wave 1 scope expanded beyond D20–D23 |
| ADR-0039 | Pull forward runtime op-allowlist walk and model registry |
| ADR-0040 | Extend DNN session API to multi-input/multi-output with named bindings |
| ADR-0041 | Ship LPIPS-SqueezeNet FR extractor with inverse-ImageNet in graph |
| ADR-0042 | Tiny-AI PRs must ship human-readable docs in the same PR |
| ADR-0102 | DNN execution-provider selection is ordered + graceful, fp16_io does a host-side cast |
| ADR-0107 | Tiny-AI Wave 1 scope expanded beyond ADR-0020 through ADR-0023 |
| ADR-0109 | Nightly bisect-model-quality runs against a synthetic placeholder cache |
| ADR-0118 | FFmpeg patches ship as ordered series.txt, not a single carry |
| ADR-0120 | DNN-enabled matrix legs across compilers + macOS |
| ADR-0129 | Tiny-AI post-training int8 quantisation — static + dynamic + QAT per model |
| ADR-0203 | Tiny-AI training prep — implementation decisions |
| ADR-0207 | Tiny-AI Quantization-Aware Training (QAT) — design |
| ADR-0211 | Tiny-model registry schema + Sigstore --tiny-model-verify |
| ADR-0215 | FastDVDnet temporal pre-filter — 5-frame window, placeholder weights |
| ADR-0218 | MobileSal saliency feature extractor (T6-2a) |
| ADR-0222 | vmaf-perShot per-shot CRF predictor sidecar |
| ADR-0223 | 0223-transnet-v2-shot-detector.md |
| ADR-0234 | GPU-generation-aware ULP calibration head |
| ADR-0235 | Codec-aware FR regressor (fr_regressor_v2) |
| ADR-0236 | 0236-dists-extractor.md |
| ADR-0237 | Quality-aware encode automation surface (vmaf-tune) |
| ADR-0242 | Tiny-AI training on the original Netflix VMAF training corpus |
| ADR-0244 | vmaf_tiny_v2 — canonical-6 + StandardScaler tiny VMAF MLP |
| ADR-0247 | vmaf-roi sidecar binary for per-CTU QP offsets |
| ADR-0250 | Tiny-AI extractor template — shared scaffolding header |
| ADR-0255 | FastDVDnet temporal pre-filter — real upstream weights via luma adapter (T6-7b) |
| ADR-0257 | MobileSal real-weights swap deferred (T6-2a-followup blocker) |
| ADR-0261 | TransNet V2 shot-boundary detector — real upstream weights via NTCHW adapter (T6-3a-followup) |
| ADR-0262 | bisect-model-quality cache check uses logical comparison for parquet |
| ADR-0265 | U-2-Net u2netp saliency replacement blocked on weights distribution + op allowlist |
| ADR-0272 | fr_regressor_v2 codec-aware scaffold (Phase B prereq) |
| ADR-0276 | vmaf-tune fast — proxy-based recommend (Phase A.5) |
| ADR-0283 | vmaf-tune Apple VideoToolbox codec adapters |
| ADR-0285 | vmaf-tune libvvenc adapter — VVC / H.266 with optional NN-VC tools |
| ADR-0286 | Fork-trained saliency student saliency_student_v1 on DUTS-TR |
| ADR-0287 | vmaf_tiny_v5 — corpus expansion (4-corpus + YouTube UGC vp9 subset) |
| ADR-0293 | vmaf-tune saliency-aware ROI tuning (Bucket #2) |
| ADR-0296 | Region-of-interest VMAF scoring (vmaf-roi-score) — saliency-weighted scaffold |
| ADR-0299 | GPU scoring backend for vmaf-tune (--score-backend) |
| ADR-0303 | fr_regressor_v2 ensemble — production flip trainer + CI gate |
| ADR-0304 | vmaf-tune fast — production wiring (Optuna TPE + v2 proxy + GPU verify) |
| ADR-0305 | Encoder knob-space Pareto-frontier analysis stratified per (source, codec, rc_mode) |
| ADR-0308 | Encoder knob-sweep recipe-regression revision policy |
| ADR-0309 | fr_regressor_v2 ensemble — real-corpus retrain harness + flip workflow |
| ADR-0310 | BVI-DVC corpus ingestion for fr_regressor_v2 |
| ADR-0318 | fr_regressor_v2 ensemble retrain harness — wrapper-trainer interface fix + Phase A pre-step doc |
| ADR-0319 | fr_regressor_v2 ensemble LOSO trainer — real loader + per-fold training |
| ADR-0320 | fr_regressor_v2 ensemble seeds — production flip (smoke → false) |
| ADR-0321 | fr_regressor_v2_ensemble_v1 — full production flip (real ONNX + sidecars) |
| ADR-0323 | fr_regressor_v3 — train + register on ENCODER_VOCAB v3 (16-slot) |
| ADR-0324 | Ensemble training kit — portable Phase-A + LOSO retrain bundle |
| ADR-0325 | KonViD-150k corpus ingestion |
| ADR-0335 | Hardware-capability priors for the FR-regressor corpus |
| ADR-0336 | KonViD MOS head v1 (ADR-0325 Phase 3) |
| ADR-0339 | av1_videotoolbox placeholder adapter + upstream watcher |
| ADR-0340 | Multi-corpus aggregation for the FR-regressor / predictor v2 trainer |
| ADR-0346 | FR-features-from-NR-corpus adapter pattern |
| ADR-0349 | fr_regressor_v3 namespace — reserve _v3plus_features for the next feature-set bump |
| ADR-0364 | saliency_student_v2 — Resize-decoder ablation on the v1 recipe |
| ADR-0365 | Wire the CoreML execution provider into tiny-AI ORT dispatch |
| ADR-0366 | vmaf-tune corpus schema v3 — canonical-6 per-feature aggregates |
| ADR-0367 | LSVQ corpus ingestion for nr_metric_v1 |
| ADR-0368 | External-competitor benchmark harness — wrapper-only architecture |
| ADR-0369 | Waterloo IVC 4K-VQA corpus ingestion for nr_metric_v1 |
| ADR-0383 | K150K corpus scoring driver — parallel CPU worker redesign |
| ADR-0388 | Ingest BVI-CC as the second tiny-AI training corpus |
| ADR-0389 | vmaf_tiny_v3 — wider/deeper mlp_medium tiny VMAF MLP |
| ADR-0390 | vmaf_tiny_v4 — mlp_large arch (opt-in only; arch ladder stops here) |
| ADR-0392 | vmaf-tune Phase D — per-shot CRF tuning |
| ADR-0393 | fr_regressor_v2 probabilistic head — deep-ensemble + conformal scaffold |
| ADR-0394 | Local sidecar training — on-host bias-correction model |
| ADR-0395 | predictor stub-models policy |
| ADR-0396 | Video-temporal saliency extension to saliency_student_v1 |
| ADR-0401 | libvmaf WebAssembly target — phased EXPERIMENT then GO |
| ADR-0405 | Wire OpenVINO NPU execution provider into the tiny-AI dispatch layer |
| ADR-0412 | Fork-local release-artefact mirror scaffold for u2netp.pth (Apache-2.0) |
| ADR-0413 | YouTube UGC corpus ingestion for nr_metric_v1 |
| ADR-0417 | Tiny-AI Netflix corpus training scaffold — draft PR registration |
| ADR-0425 | vmaf-roi-score saliency materialiser |
| ADR-0426 | CHUG HDR corpus ingestion |
| ADR-0427 | Materialise CHUG HDR Features With Reference-Aligned Pairs |
| ADR-0431 | Split CUDA and CPU Feature Passes for FR-from-NR Extraction |
| ADR-0433 | CHUG Content Splits And HDR Audit |
| ADR-0434 | CHUG Parquet Metadata Enrichment |
| ADR-0444 | Promote saliency_student_v2 to production default |
| ADR-0446 | K150K/CHUG extractor passes HDR and HFR per-feature options |
| ADR-0447 | Motion features under-report on HFR / 50p content |
| ADR-0455 | KonViD-150k k150ka/k150kb split promotion into the MOS-head trainer |
| ADR-0457 | model/tiny/*.onnx blobs ≥1MB live in GitHub Releases, not git |
| ADR-0459 | vmaf-tune panel/display-aware recommendation workstream |
| ADR-0481 | ADM p-norm Parameter Hardcoded at 3.0 — Deferral Decision |
| ADR-0482 | Expand vmaf_pre FFmpeg filter device strings to match full VmafDnnDevice enum |
| ADR-0495 | MCP server probe-driven bug-fix cluster (2026-05-17) |
| ADR-0510 | CHUG re-extract VMAF-alignment fix — FR-corpus guard on the FR-from-NR extractor |
| ADR-0511 | MCP backend probe, default allowlist, and vmaf-tune ladder --score-backend (2026-05-18) |
| ADR-0518 | Tiny-model loader accepts external-data and feature-vector ONNX |
| ADR-0520 | Wire vmaf --no-reference through to the scoring path |
| ADR-0522 | --tiny-codec / --tiny-preset / --tiny-crf populate codec one-hot block |
| ADR-0524 | Tiny-model loader accepts symbolic batch dim |
| ADR-0525 | Extract run_cmd subprocess helper into aiutils |
| ADR-0527 | Accept pre-extracted BVI-DVC YUVs via --bvi-dir |
| ADR-0546 | Audit bundle — Vulkan motion dispatch wiring, saliency hard-fail, model-card placeholder |
| ADR-0547 | VMAF_ |
| ADR-0550 | Auto-resize input plane to NR tiny-model dims + --tiny-resize flag |
| ADR-0556 | Python / MCP / AI silent-fallback audit fixes (2026-05-18) |
| ADR-0559 | Feature Coverage Audit — Add speed_chroma + speed_temporal to Extraction Scripts (HDR-model prep) |
| ADR-0565 | Continuous Feature-Mix Evaluation Pipeline (predictor-bench) |
| ADR-0612 | Tiny-AI training on the original Netflix VMAF training corpus |
| ADR-0613 | Dynamic Optimizer — Joint Shot-Boundary + CRF Co-Optimisation |
| ADR-0614 | Per-Shot ABR Rendition Selection |
| ADR-0615 | Fast NR Pre-Scoring for CRF Bisect Acceleration |
| ADR-0616 | VMAF NEG Integration into vmaf-tune |
| ADR-0617 | Cross-Shot Complexity Weighting and Title-Level Quality Constraints |
| ADR-0618 | Content-Aware Classifier for Encoder Routing |
| ADR-0621 | Scaffold Audit P3 — six cleanup items + state drift |
| ADR-0624 | Fast NR Pre-Scoring Implementation (ADR-0615 impl) |
| ADR-0639 | Scaffold-audit P1 — backend precheck, HIP picture, mobilesal bpc, DNN multi-output |
| ADR-0640 | Tiny-AI training on the original Netflix VMAF training corpus (2026-05-20 scaffold iteration) |
| ADR-0642 | AI refresh defaults use current fork full-feature extractors |
| ADR-0646 | Route Attached DNN Multi-Output Tensors |
| ADR-0647 | Refresh fr_regressor_v1 from the 2026-05-20 Netflix feature table |
| ADR-0648 | CHUG HDR MOS Trainer Entry Point |
| ADR-0649 | CHUG HDR Wide MOS Feature Schema |
| ADR-0650 | Add a Signal-Mix Audit CLI |
| ADR-0651 | Preserve CHUG HDR Metadata On Feature Rows |
| ADR-0652 | Add CHUG Visual-Signal Primitives |
| ADR-0653 | CHUG Display Profile Training |
| ADR-0654 | Predictor Preserves Saliency Signals |
| ADR-0655 | Saliency Feature Materializer |
| ADR-0656 | External-bench wrappers emit registry competitor keys |
| ADR-0657 | Second-Opinion Feature Materializer |
| ADR-0658 | Project modernization audit |
| ADR-0661 | AI run manifest provenance |
| ADR-0663 | MOS Label Materializer |
| ADR-0668 | AI Derived Table Provenance |
| ADR-0669 | AI Corpus JSONL Provenance |
| ADR-0670 | AI Legacy Corpus Extraction Manifests |
| ADR-0671 | U2NetP Mirror Exporter |
| ADR-0672 | Saliency Materializer Temporal Controls |
| ADR-0674 | Second-Opinion Materializer Batch Manifest |
| ADR-0675 | MOS Label Materializer Batch Manifest |
| ADR-0676 | MOS Corpus Adapter Manifests |
| ADR-0677 | AI Dataset Fetch Manifests |
| ADR-0678 | Shared AI Run Manifest Helper |
| ADR-0680 | Shared AI CLI Helper Pattern |
| ADR-0681 | AI Script Bootstrap Helper |
| ADR-0682 | Tiny-AI Netflix corpus training scaffold — 2026-05-22 prep scope |
| ADR-0685 | Tiny-AI Netflix corpus training scaffold — 2026-05-27 prep scope |
| ADR-0687 | CHUG HDR MOS head — held-out test partition validator |
| ADR-0690 | VMAFX Binary and AI Tool Aliases |
| ADR-0841 | Environment variable reference page and canonical naming |