diff --git a/.github/dependabot.yml b/.github/dependabot.yml new file mode 100644 index 0000000..bd93da3 --- /dev/null +++ b/.github/dependabot.yml @@ -0,0 +1,26 @@ +# 依存パッケージの定期更新 PR（Dependabot version updates） +# 脆弱性検出（Dependabot alerts / security updates）はリポジトリ設定で有効化済み（本ファイルとは独立に動く） +version: 2 +updates: + - package-ecosystem: "uv" + directory: "/" + schedule: + interval: "weekly" + open-pull-requests-limit: 5 + commit-message: + prefix: "[update]" + groups: + minor-and-patch: + update-types: + - "minor" + - "patch" + - package-ecosystem: "github-actions" + directory: "/" + schedule: + interval: "weekly" + commit-message: + prefix: "[update]" + groups: + actions: + patterns: + - "*" diff --git a/.gitignore b/.gitignore index a1fa515..7ee90c9 100644 --- a/.gitignore +++ b/.gitignore @@ -22,9 +22,32 @@ # .claude/hooks/ の Python フックとそのテスト（tests/test_hooks.py）が生成するバイトコードキャッシュ __pycache__/ -# -- プロジェクト立ち上げ時に有効化する（.claude/rules/git-conventions.md 参照） -- -# .env -# .env.* -# node_modules/ -# build/ -# dist/ +# --- プロジェクト固有 --- + +# 臨床データ・合成データ（絶対にコミットしない） +data/ + +# 学習結果（指標・図・チェックポイント） +runs/ + +# モデルの重み +*.pt +*.pth +*.onnx + +# Python / uv +.venv/ +*.py[cod] +*.egg-info/ +build/ +dist/ +.ruff_cache/ +.pytest_cache/ + +# 環境変数 +.env +.env.* + +# OS +Thumbs.db +.DS_Store diff --git a/.python-version b/.python-version new file mode 100644 index 0000000..e4fba21 --- /dev/null +++ b/.python-version @@ -0,0 +1 @@ +3.12 diff --git a/CLAUDE.md b/CLAUDE.md index a05992e..7c83e46 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -5,7 +5,7 @@ ## 開発進捗 -最新: 立ち上げフェーズ 1（方針決定）完了．PLAN_01 要件定義書を作成 +最新: 立ち上げフェーズ 3（環境構築）完了．サーバ側の CUDA 疎通まで確認（手元の依存インストールは継続中） ※ 本欄は**最新ステップ 1 行のみ上書き更新**．詳細な進捗履歴（動機・設計判断・失敗パターン）は [docs/PROGRESS.md](docs/PROGRESS.md) に追記する．運用ルールは `.claude/rules/progress-log.md` を参照（該当ファイル編集時に自動ロードされる）． ## 必須ルール（コード実装時） @@ -70,14 +70,15 @@ ### 02_ENV（環境） - +- 技術スタック: docs/02_ENV/ENV_01_技術スタック.md +- 環境構築手順: docs/02_ENV/ENV_02_環境構築手順.md +- 管理者用環境構築手順: docs/02_ENV/ENV_03_管理者用環境構築手順.md +- 開発コマンド: docs/02_ENV/ENV_04_開発コマンド.md ### 03_PLAN（計画） - 要件定義書: docs/03_PLAN/PLAN_01_要件定義書.md - - ### 04_SPEC（仕様・設計） diff --git a/README.md b/README.md new file mode 100644 index 0000000..55016a7 --- /dev/null +++ b/README.md @@ -0,0 +1,7 @@ +# TIASJudgeModel + +舌領域をセグメンテーション済みの舌画像から舌色 5 分類（紫・暗赤・紅・淡紅・淡白）を推定する機械学習モデルの研究開発．学習は研究室の計算サーバで行い，臨床データは手元 PC に置かない． + +- 要件: [docs/03_PLAN/PLAN_01_要件定義書.md](docs/03_PLAN/PLAN_01_要件定義書.md) +- 技術スタック: [docs/02_ENV/ENV_01_技術スタック.md](docs/02_ENV/ENV_01_技術スタック.md) +- 環境構築: [docs/02_ENV/ENV_02_環境構築手順.md](docs/02_ENV/ENV_02_環境構築手順.md) diff --git "a/docs/02_ENV/ENV_01_\346\212\200\350\241\223\343\202\271\343\202\277\343\203\203\343\202\257.md" "b/docs/02_ENV/ENV_01_\346\212\200\350\241\223\343\202\271\343\202\277\343\203\203\343\202\257.md" new file mode 100644 index 0000000..5310992 --- /dev/null +++ "b/docs/02_ENV/ENV_01_\346\212\200\350\241\223\343\202\271\343\202\277\343\203\203\343\202\257.md" @@ -0,0 +1,90 @@ +# 技術スタック (Tech Stack) + +## 概要 (Overview) + +舌領域セグメンテーション済み画像から舌色 5 分類を推定するモデルを，手元の Windows で実装し，研究室の GPU サーバで学習する．臨床データは手元 PC に置かないため，**手元は合成データでの実装確認のみ**とし，実データを触るコードはすべてサーバ上で動かす． + +## 言語・実行環境 (Language & Runtime) + +| 項目 | 採用 | 備考 | +| --- | --- | --- | +| 言語 | Python | TIASjudge・SmTIAS-LightSim と揃える | +| Python バージョン | 3.12（`.python-version` で固定） | 既存 2 プロジェクトと同一．サーバにも導入済み | +| パッケージマネージャ | **uv**（Astral 製） | 既存プロジェクトと同じ．`uv.lock` をコミットして再現性を担保する | +| 手元 OS | Windows 11 | 実装・合成データでの動作確認のみ（GPU なし） | +| 学習環境 | 研究室 GPU サーバ（Ubuntu 22.04・RTX A6000） | uv・Python 3.12 導入済み | + +## 機械学習フレームワーク (ML Framework) + +| 項目 | 採用 | 備考 | +| --- | --- | --- | +| 学習フレームワーク | **PyTorch 2.x** | 研究用途の標準．事前学習モデルの入手性が高い | +| モデル | **timm**（PyTorch Image Models） | ConvNeXt・EfficientNet・ViT 等を設定 1 行で差し替えて比較できる | +| 学習ループ | 自前で記述（Lightning 等の高水準ラッパは使わない） | 患者単位分割・クラス不均衡対策を明示的に制御したいため．規模が小さく抽象化の利得が薄い | +| データ拡張 | `torchvision.transforms.v2` | 依存を増やさない．足りなければ albumentations を後から追加する | + +※ 具体的なモデル（ConvNeXt-Tiny 等）・入力解像度・学習設定は仕様設計フェーズ（`SPEC_01`）で決める．本ファイルでは土台のみ確定する． + +## データ処理・評価 (Data Processing & Evaluation) + +| 項目 | 採用 | 備考 | +| --- | --- | --- | +| 画像 IO | Pillow | 学習時の読み込み．軽量 | +| 数値計算 | NumPy | — | +| 評価指標 | scikit-learn | 混同行列・macro F1・クラス別 recall・患者単位の層化分割 | +| 図の出力 | matplotlib | 学習曲線・混同行列を PNG で出力する（サーバ上で描画し，画像ファイルだけ回収する） | +| ルールベース比較 | TIASjudge の `core/` ロジックを移植または参照 | ベースライン算出用．OpenCV が必要になった場合はサーバに GUI が無いため `opencv-python-headless` を使う | + +## 設定と実験記録 (Configuration & Experiment Tracking) + +| 項目 | 採用 | 備考 | +| --- | --- | --- | +| 設定ファイル | **YAML ＋ pydantic**（スキーマ検証） | SmTIAS-LightSim と同じ流儀．`configs/*.yaml` に実験条件を置く | +| 実験記録 | **軽量自作**（外部サービスを使わない） | `runs/<実験ID>/` に `config.yaml`・`metrics.json`・`history.csv`・`confusion_matrix.png`・チェックポイントを書き出す | +| 手元への回収 | 指標・図・ログのみ（画像・ラベルは回収しない） | 個人情報を含む可能性のあるものを持ち帰らないため | + +採用理由: 依存が増えず，**外部送信がゼロ**で，臨床データ由来の情報の流出経路を作らない．実験の比較はファイルを並べるだけで足りる規模である． + +## リモート実行 (Remote Execution) + +| 項目 | 採用 | 備考 | +| --- | --- | --- | +| リモート実行ツール | **自作 CLI**（SmTIAS-LightSim の `sm-remote` を移植） | コード送信・ジョブ実行・結果回収・GPU 空き確認 | +| 転送方式 | tar over ssh | Windows に rsync が無いため（LightSim と同じ判断） | +| 実行 | サーバ上の tmux 内で `uv run` | 接続が切れても学習が続く | +| SSH | Windows 標準 OpenSSH | 学外からは研究室 PC を ProxyJump の踏み台にする | +| データ | サーバ常設（コードのみ毎回転送） | 一度だけコピーし，以降は再転送しない | +| 認証情報 | サーバに GitHub の認証情報を置かない | コードは常に手元から送る | + +## 開発ツール (Development Tools) + +| 項目 | 採用 | 備考 | +| --- | --- | --- | +| テスト | pytest | 合成データで動くテストのみ（臨床データに依存するテストは書かない） | +| lint / format | ruff | Python の標準的な選択．規約は規約整備フェーズで定める | +| CI | **使わない** | ローカルで pytest・ruff を回す．必要になれば後から GitHub Actions を追加する | +| 依存更新 | Dependabot（`uv` エコシステム） | 週 1 回．CI が無いので更新 PR はローカル検証で確認する | + +## CPU / GPU の依存差 (CPU / GPU Dependencies) + +`torch` を PyPI からそのまま依存に入れると，**Linux では CUDA 付きの wheel，Windows では CPU 版の wheel** が選ばれるため，同一の `pyproject.toml` で「手元 = CPU，サーバ = GPU」が成立する見込みである． + +- サーバでの初回 `uv sync` 後に `torch.cuda.is_available()` が `True` になることを確認する（環境構築手順に含める） +- 想定どおりにならない場合は PyTorch 公式インデックスを `[tool.uv.sources]` で指定する方式に切り替える + +## 採用しなかった選択肢 (Rejected Alternatives) + +| 候補 | 却下理由 | +| --- | --- | +| Weights & Biases | 学習指標を外部サービスへ送信する．臨床データを扱う研究では審査・規約との整合確認が必要で，得られる利便性に対して手続きの負担が大きい | +| MLflow | サーバでサービスを立ててポート転送で見る運用コストが，本プロジェクトの実験数に対して過大 | +| torchvision のみ | 事前学習モデルの選択肢が狭く，「どの系統のモデルが向くか」の比較がしにくい | +| PyTorch Lightning・Keras 等の高水準ラッパ | 患者単位分割・クラス不均衡対策を明示的に制御したい．学習ループが小さいため抽象化の利得が薄い | +| GitHub Actions での CI | 現時点では 1 人開発でローカル実行で足りる．データを使うテストは CI で回せない | + +## 未確定事項 (Open Items) + +- モデルアーキテクチャ・入力解像度・学習設定（仕様設計フェーズで決定） +- サーバ上のデータ配置パスとディレクトリ構成（環境構築フェーズで決定） +- TIASjudge のルールベース診断を「移植」するか「別リポジトリを参照」するか（ベースライン実装時に決定） +- 学習済みモデルの配布形式（ONNX 等．モデルの見込みが立ってから決定） diff --git "a/docs/02_ENV/ENV_02_\347\222\260\345\242\203\346\247\213\347\257\211\346\211\213\351\240\206.md" "b/docs/02_ENV/ENV_02_\347\222\260\345\242\203\346\247\213\347\257\211\346\211\213\351\240\206.md" new file mode 100644 index 0000000..23bb7ce --- /dev/null +++ "b/docs/02_ENV/ENV_02_\347\222\260\345\242\203\346\247\213\347\257\211\346\211\213\351\240\206.md" @@ -0,0 +1,74 @@ +# 環境構築手順 (Environment Setup) + +## 前提ツール (Prerequisites) + +| ツール | 用途 | 備考 | +| --- | --- | --- | +| git | バージョン管理 | 運用は `.claude/rules/git-conventions.md` | +| gh | GitHub CLI | PR 作成・リポジトリ設定 | +| uv | Python・依存管理 | `winget install astral-sh.uv` | +| Python 3.7 以上 ＋ bash | `.claude/hooks/` の実行 | Windows は Git for Windows 付属の bash．※ Python が見つからないとアクセス制限フックが全ツールをブロックする | +| OpenSSH | サーバ接続 | Windows 11 標準（`C:\Windows\System32\OpenSSH\ssh.exe`） | + +## 手元 PC のセットアップ (Local Setup) + +```bash +git clone https://github.com/rintoHasegawa/TIASJudgeModel.git +cd TIASJudgeModel +uv sync +``` + +手元には **CPU 版の PyTorch** が入る（[ENV_01「CPU / GPU の依存差」](ENV_01_技術スタック.md)）．学習は回さず，実装と合成データでの動作確認に使う． + +## 臨床データの取り扱い (Clinical Data Handling) + +**手元 PC に臨床データを置かない．** これは手順ではなく守るべき制約である． + +- 実データは研究室 PC が原本，学習用のコピーは Newton の `~/data/TIASJudgeModel/`（[ENV_03](ENV_03_管理者用環境構築手順.md)） +- 手元へ回収するのは非個人情報の派生物のみ（指標・学習曲線・混同行列・ログ・モデル重み） +- 画像・ラベル・患者 ID を含むファイルは回収しない +- `data/`・`runs/` は `.gitignore` 済み + +## 合成データでの動作確認 (Synthetic Data) + +実データが無い手元で学習パイプラインを流すため，合成データ生成スクリプトを使う（実装フェーズで作成）． + +- 出力先: `data/synthetic/`（`.gitignore` 対象） +- 目的は「落ちずに 1 エポック回り，指標が書き出される」ことの確認であり，精度は意味を持たない + +## 研究室サーバの利用 (Lab Server) + +| Host 名 | アドレス | 用途 | +| --- | --- | --- | +| `Newton` | `Newton.local`（研究室 LAN 内） | 学習の実行．RTX A6000×3・Ubuntu 22.04・uv・Python 3.12 | +| `Newton-via-lab` | 研究室 PC を ProxyJump した経路 | 学外から接続する場合 | + +- SSH の鍵と `~/.ssh/config` は **SmTIAS-LightSim で構築済みのものを流用する**（設定手順は同プロジェクトの `docs/02_ENV/ENV_02_環境構築手順.md`「研究室サーバ編」を参照） +- **サーバ上では編集しない**．コードは常に手元から送る（次節） +- サーバに GitHub の認証情報を置かない + +## 日常の流れ (Daily Workflow) + +リモート実行ツール（ENV_01．`sm-remote` の移植）を使う．コマンド名・オプションは実装時に確定し，`ENV_04_開発コマンド.md` に記載する． + +1. 手元でコードを編集する +2. コードをサーバへ送る（tar over ssh） +3. GPU の空きを確認し，tmux 内で学習を実行する +4. 結果（指標・図・ログ）を回収する + +## 環境再現性のルール (Reproducibility Rules) + +- 依存の追加は `uv add`．`uv.lock` はコミットする +- 絶対パスをコードにハードコードしない（設定 YAML と環境変数で渡す） +- 乱数シードを設定ファイルで固定し，`runs/<実験ID>/config.yaml` に実際に使った設定を保存する + +## トラブルシューティング (Troubleshooting) + +| 症状 | 原因 | 対処 | +| --- | --- | --- | +| サーバで `torch.cuda.is_available()` が `False` | CPU 版 wheel が入った | ENV_01「CPU / GPU の依存差」に従い `[tool.uv.sources]` で PyTorch の CUDA インデックスを指定する | +| `ssh Newton 'cat ...'` が応答せず止まる | 標準入力が開いたまま（LightSim で実測） | `ssh -n` を付ける | +| 学外からの転送が遅い | Tailscale が DERP 中継経由になっている | `tailscale ping` で経路を確認し，転送は差分だけにする | +| ファイル操作系のツールが全てブロックされる | フック用の Python が見つからない | `python3` / `python` / `py` のいずれかが起動できるようにする | +| サーバで `uv: command not found` | 非対話 ssh の PATH に `~/.local/bin` が入らない | コマンドの前に `export PATH="$HOME/.local/bin:$PATH"` を付ける（リモート実行ツールもこれを行う） | +| 踏み台経由で `connect failed`（ホスト名不明） | 踏み台側の mDNS（`Newton.local`）の解決が一時的に失敗する | 時間をおいて再試行する．頻発する場合は踏み台の `~/.ssh/config` で Newton を IP 指定にする | diff --git "a/docs/02_ENV/ENV_03_\347\256\241\347\220\206\350\200\205\347\224\250\347\222\260\345\242\203\346\247\213\347\257\211\346\211\213\351\240\206.md" "b/docs/02_ENV/ENV_03_\347\256\241\347\220\206\350\200\205\347\224\250\347\222\260\345\242\203\346\247\213\347\257\211\346\211\213\351\240\206.md" new file mode 100644 index 0000000..83560b8 --- /dev/null +++ "b/docs/02_ENV/ENV_03_\347\256\241\347\220\206\350\200\205\347\224\250\347\222\260\345\242\203\346\247\213\347\257\211\346\211\213\351\240\206.md" @@ -0,0 +1,71 @@ +# 管理者用環境構築手順 (Administrator Setup) + +プロジェクト作成時に **一度だけ** 行う初期設定． + +## GitHub リポジトリの作成 (Repository Creation) + +private リポジトリとして作成する（臨床データは含めないが，研究途中のコードを公開しないため）． + +```bash +gh repo create rintoHasegawa/TIASJudgeModel --private --source=. --remote=origin \ + --description "舌画像から舌色 5 分類を推定する機械学習モデル（TIASjudge 用）" +``` + +## リポジトリのセキュリティ設定 (Repository Security Settings) + +Dependabot alerts（脆弱性検出）と Dependabot security updates は**リポジトリごとに既定で OFF** なので，作成直後に有効化する（冪等なので再実行してよい）． + +```bash +gh api -X PUT repos/rintoHasegawa/TIASJudgeModel/vulnerability-alerts +gh api -X PUT repos/rintoHasegawa/TIASJudgeModel/automated-security-fixes +``` + +検証: + +```bash +gh api repos/rintoHasegawa/TIASJudgeModel/vulnerability-alerts # 204 なら有効（404 なら無効） +gh api repos/rintoHasegawa/TIASJudgeModel/automated-security-fixes # {"enabled":true,...} なら有効 +``` + +※ 依存バージョンの定期更新は `.github/dependabot.yml` で設定する（別物．リポジトリ設定とは独立に動く）． + +## Newton 側の初期設定 (Server Setup) + +```bash +mkdir -p ~/work/TIASJudgeModel # コード置き場（push で上書きされる） +mkdir -p ~/data/TIASJudgeModel # データ置き場（push の対象外） +chmod 700 ~/data/TIASJudgeModel # 共用サーバなので自分だけに絞る +``` + +コードを初回送信したあと，サーバ上で以下を確認する． + +```bash +cd ~/work/TIASJudgeModel +uv sync +uv run python -c "import torch; print(torch.cuda.is_available(), torch.cuda.device_count())" +``` + +`uv sync` は CUDA 版 PyTorch が入るため時間がかかる．`True` と GPU 台数が出ることを確認する．`False` の場合は [ENV_01「CPU / GPU の依存差」](ENV_01_技術スタック.md)に従う． + +## 臨床データの初回コピー (Initial Data Copy) + +原本は研究室 PC に置き，**研究室 LAN 内で Newton へ一度だけコピーする**．手元 PC を経由させない． + +1. 研究室 PC で作業する（**`hostname` で研究室 PC であることを確認してから実行する**） +2. 研究室 PC から Newton へコピーする（例: `scp -r <データ> Newton:~/data/TIASJudgeModel/`） +3. コピー後に件数を突き合わせる（両側でファイル数を数える） +4. 原本は研究室 PC に残す（Newton 側は作業用コピー） + +以降は再転送しない．データセットの内容確認（枚数・クラス分布・破損チェック）はサーバ上のコマンドで行い，**集計結果のみ**を手元で見る． + +## 学外アクセス用の踏み台 (Off-campus Access) + +研究室 PC を ProxyJump の踏み台にする設定は SmTIAS-LightSim で構築済みのため，本プロジェクトでの追加作業は不要（未設定の場合は同プロジェクトの `docs/02_ENV/ENV_02_環境構築手順.md`「学外から接続する（研究室 PC 経由）」に従う）． + +## 人間が確認すべき事項 (Human Checklist) + +Claude は実施できない．着手前に確認する． + +- 臨床データの倫理審査・データ利用許諾の範囲（機械学習での二次利用が含まれるか） +- データを研究室の共用計算サーバに置くことが規程上許容されるか +- 研究室 PC で SSH サーバを動かすことが研究室のルールに照らして問題ないか diff --git "a/docs/02_ENV/ENV_04_\351\226\213\347\231\272\343\202\263\343\203\236\343\203\263\343\203\211.md" "b/docs/02_ENV/ENV_04_\351\226\213\347\231\272\343\202\263\343\203\236\343\203\263\343\203\211.md" new file mode 100644 index 0000000..a355e2e --- /dev/null +++ "b/docs/02_ENV/ENV_04_\351\226\213\347\231\272\343\202\263\343\203\236\343\203\263\343\203\211.md" @@ -0,0 +1,46 @@ +# 開発コマンド (Development Commands) + +日常の開発で使うコマンドの一覧．**コマンドを推測せず必ず本ファイルを参照する**（新しく確定・変更された時は本ファイルに反映する）． + +※ 学習・評価・リモート実行のコマンドは未実装のため本ファイルには未記載（実装時に追記する）． + +## 環境 (Environment) + +| 目的 | コマンド | 備考 | +| --- | --- | --- | +| 依存の同期 | `uv sync` | 初回・`pyproject.toml` 変更後．手元には CPU 版 PyTorch が入る | +| 依存の追加 | `uv add <パッケージ>` | `uv.lock` が更新されるのでコミットする | +| 開発用依存の追加 | `uv add --dev <パッケージ>` | pytest・ruff 等 | +| Python の実行 | `uv run python <スクリプト>` | 仮想環境を明示的に有効化しなくてよい | + +## テスト (Test) + +| 目的 | コマンド | +| --- | --- | +| 全テスト | `uv run pytest` | +| 特定ファイル | `uv run pytest tests/test_package.py` | +| 詳細表示 | `uv run pytest -v` | + +臨床データに依存するテストは書かない（合成データで動くテストのみ）． + +## Lint / Format + +| 目的 | コマンド | +| --- | --- | +| Lint | `uv run ruff check .` | +| Lint（自動修正） | `uv run ruff check --fix .` | +| Format | `uv run ruff format .` | + +## フック (Hooks) + +| 目的 | コマンド | 備考 | +| --- | --- | --- | +| フックのテスト | `bash .claude/hooks/tests/test_hooks.py` 相当を `uv run pytest .claude/hooks/tests` | テンプレート由来．`.claude/` の変更時に確認する | + +## 未実装のコマンド (Planned) + +実装した時点で本ファイルに追記する． + +- データセットの集計（サーバ上で実行．枚数・患者数・クラス分布・破損チェック） +- 学習・評価 +- リモート実行（コード送信・ジョブ実行・結果回収・GPU 空き確認） diff --git a/docs/PROGRESS.md b/docs/PROGRESS.md index c81abf3..af694dc 100644 --- a/docs/PROGRESS.md +++ b/docs/PROGRESS.md @@ -18,3 +18,12 @@ - スコープ外: セグメンテーションの学習・5 分類以外の所見・TIASjudge への組み込み実装・撮影条件の色補正 - 未確定: 画像枚数・患者数・クラス分布・ラベル形式・患者 ID の追跡可否は研究室 PC で実データを確認して確定する +## 立ち上げ（フェーズ 2〜3: 技術選定・環境構築） + +- [x] **技術スタックの確定**: PyTorch ＋ timm・uv・YAML ＋ pydantic・リモート実行は SmTIAS-LightSim の `sm-remote` 移植，実験記録は軽量自作，CI なしと決め [ENV_01](02_ENV/ENV_01_技術スタック.md) を作成した． + - 設計判断: 実験管理に W&B・MLflow を採らず自作にしたのは，臨床データ由来の指標を外部サービスへ送らない方針と，実験数に対する運用コストの釣り合いから +- [x] **環境構築**: GitHub private リポジトリを作成し Dependabot alerts / security updates を有効化（検証済み）．`.github/dependabot.yml`（`uv` ＋ `github-actions`）・`.gitignore` 更新（`data/`・`runs/`・重み）・`pyproject.toml`（Python 3.12）・パッケージ骨組み・README を作成し，[ENV_02](02_ENV/ENV_02_環境構築手順.md)〜[ENV_04](02_ENV/ENV_04_開発コマンド.md) を整備した．Newton に `~/work/TIASJudgeModel` と `~/data/TIASJudgeModel`（700）を作り，コードを tar over ssh で送って `uv sync` を通し **torch 2.14.0+cu130・CUDA 有効・GPU 3 台**を確認した． + - 確認できたこと: Linux では PyPI の wheel がそのまま CUDA 版で入る（ENV_01 の想定どおりで `[tool.uv.sources]` での対処は不要）．GPU は 3 台のうち 1 台が他ユーザー使用中で，共用前提の GPU 指定が必要 + - 失敗パターン: ① 手元の `uv sync` が PyPI からのダウンロードで connection reset（`safetensors`）→ 再試行中 / ② 非対話 ssh では `uv` が PATH に無く `command not found`（`export PATH="$HOME/.local/bin:$PATH"` が必要）/ ③ 踏み台経由で `Newton.local` の名前解決が一時的に失敗（再試行で復帰）．② ③ は ENV_02 のトラブルシューティングに記録した + - 未実施: push・PR，臨床データの初回コピー（研究室 PC → Newton），倫理審査・データ利用許諾の確認．仕様設計（フェーズ 4）はドラフトを提示済みで保存保留 + diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..93f4432 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,34 @@ +[project] +name = "tias-judge-model" +version = "0.1.0" +description = "舌画像から舌色 5 分類を推定する機械学習モデル（TIASjudge 用）" +readme = "README.md" +requires-python = ">=3.12,<3.13" +dependencies = [ + "torch>=2.5", + "torchvision>=0.20", + "timm>=1.0", + "numpy>=2.0", + "pillow>=11.0", + "scikit-learn>=1.5", + "matplotlib>=3.9", + "pydantic>=2.9", + "pyyaml>=6.0", +] + +[dependency-groups] +dev = [ + "pytest>=8.0", + "ruff>=0.8", +] + +[build-system] +requires = ["uv_build>=0.12.5,<0.13"] +build-backend = "uv_build" + +[tool.ruff] +line-length = 100 +target-version = "py312" + +[tool.pytest.ini_options] +testpaths = ["tests"] diff --git a/src/tias_judge_model/__init__.py b/src/tias_judge_model/__init__.py new file mode 100644 index 0000000..aade829 --- /dev/null +++ b/src/tias_judge_model/__init__.py @@ -0,0 +1,3 @@ +"""舌画像から舌色 5 分類を推定する機械学習モデル（TIASjudge 用）.""" + +__version__ = "0.1.0" diff --git a/tests/test_package.py b/tests/test_package.py new file mode 100644 index 0000000..a761504 --- /dev/null +++ b/tests/test_package.py @@ -0,0 +1,7 @@ +"""パッケージが import 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