Hacktoberfest 2026: những issue maintainer đã đánh dấu cho tháng Mười, đang mở và phù hợp người mới. Xem issue Hacktoberfest

[Phase 16] S8 — Run-scoped effective state and provenance

Đang mở
  • Có gì không ổn?
#894 0 bình luận 0 reaction 0 người được giao Xem trên GitHub

Chưa có ai nhận issue này.

Đánh giá

Độ khó
5/5
Thời gian dự kiến
Hơn một tuần
Mức phù hợp với người mới
12/100
Loại issue
Lỗi
Độ rõ ràng
Cần làm rõ
Mức độ hoạt động
Sôi nổi
Công nghệ
huggingface, python
Lĩnh vực
documentation, machine-learning

Hướng nghiên cứu

Start with the step plan in docs/roadmap/phase-16-trust-surface-hardening.md (lines 518-551) and the ForgeTrainer run state, then trace how the model card and compliance manifest producers read the config today. The fit-check YAML emitter and the --compliance-export path without a training run are the other entry points. Done means the six exit criteria pass, including the 4x2 lora.method and CUDA matrix and the A-to-B and B-to-A run isolation test. This is cross-cutting design work spanning several units, so it should be split before anyone starts.

Do mô hình lập chỉ mục viết ra từ nội dung của issue.

Mô tả

phase: 16 source: roadmap

Roadmap · Phase 16, step S8 · size XL · 4 unit(s) · planned in docs/roadmap/phase-16-trust-surface-hardening.md:518-551

Summary

Artifact producers and estimators re-interpret the original config instead of consuming this run's observed effective state, and the provenance that does exist is bound to a module singleton instead of the run. The model card misses DoRA, PiSSA and rsLoRA in all three of its surfaces, and the manifest's training_parameters.dora is False for method: dora, contradicting the same manifest's adapter_method — an internally inconsistent compliance artefact.

Units

Unit Tracked by (October 2026 review)
C31-RUN-OUTCOME (= CORE-06 + CORE-07 + CORE-12) #569 · #572 · #647 · #700 · #804
F-W20260729-CORE-09 #503 · #561
F-W20260729-TRUST-08 #569 · #647 · #686 · #689 · #709
F-W20260729-OPS-22 — no review issue; tracked by this issue

Decisions this step executes

  • C-6 — keep model_lineage.quantization meaning "requested" and add quantization_effective beside it.
  • C-7 — effective fields when no training run occurred: a "not_observed" sentinel.
  • C-9 — training.gradient_checkpointing does not become a real field; delete fit-check's invalid recommendation.

Plan

  • Record the run's effective state in ForgeTrainer and pass it to the card and manifest producers as a parameter — do not add CARD→MODEL or COMPLIANCE→MODEL import edges (architecture.md has none).
  • forgelm --compliance-export without a training run writes the "not_observed" sentinel.
  • No fixture mass-regeneration: each regenerated golden fixture needs a named reason.

Exit criteria

  • A 4×2 matrix (lora.method × CUDA available/absent, load_in_4bit) proves the card and the manifest name the method and quantization actually applied, with the requested value kept in its own field.
  • Runs A→B and B→A in one process produce manifests with no cross-contamination.
  • A failed merge_and_unload() is visible identically in the audit log, the card and the manifest.
  • Every YAML snippet fit-check emits validates against ForgeConfig.
  • A directory fingerprint changes on content change and not on traversal order.
  • A test enumerates all loader surfaces, so a new one cannot be added silently.

How to deliver

  • One root-cause family, committed on its own; then an Opus review round and a Sonnet review round, each with verified findings fixed and committed before the next step begins.
  • A reproducer that is red before the fix and green after; the full gauntlet from CLAUDE.md passes under ./.venv/bin/python.
  • Every English documentation edit ships with its Turkish mirror in the same commit; a new or renamed audit event gets its EN and TR catalog rows in the same PR.
  • A step that grows a deferred module carries its budget_history justification in the same diff; a widened guard rolls out non-strict first, then flips.
  • Commit bodies cite Absorbs F-W20260729-…; the CHANGELOG [Unreleased] section gets an entry only for a change a user or library consumer can observe (decision C-20).

Planned in docs/roadmap/phase-16-trust-surface-hardening.md (read at f94595f). Unit IDs (F-W20260729-…) come from the 2026-07-29/30 full-project review; the issue numbers next to them are the October 2026 review's records of the same defects.

Ngôn ngữ chính
Python
Star
9
Fork
1
Merge trung bình
8 giờ 10 phút
Pull request đã merge (30 ngày)
5

Chuẩn bị môi trường

Bắt đầu từ đâu

  1. Đọc hết issue, rồi đọc hướng dẫn đóng góp của dự án.
  2. Bình luận trên issue rằng bạn sẽ nhận — tránh hai người làm cùng một việc.
  3. Fork repository và làm thay đổi trên một nhánh.
  4. Mở pull request có tham chiếu số hiệu của issue.

Issue khác của HodeTech/ForgeLM

Tất cả issue của HodeTech/ForgeLM

Issue tương tự

Thêm issue về Python

Nhận issue mới trong hộp thư của bạn

Bản tóm tắt ngắn những issue GitHub phù hợp với người mới.