diff --git a/.github/CONTRIBUTING.md b/.github/CONTRIBUTING.md index 76ceea105..7fe827bd1 100644 --- a/.github/CONTRIBUTING.md +++ b/.github/CONTRIBUTING.md @@ -1,29 +1,31 @@ -# Contributing during maintenance mode +# Contributing to CDT++ Thank you for helping improve CDT++. -CDT++ v1.0.0-rc3 is the release candidate for the final C++23 release, v1.0.0, after which this repository will be -archived. The project -is maintained as a scientific reference implementation and regression oracle for +CDT++ v1.0.0-rc3 is the current C++23 release candidate. The project remains maintained as a scientific reference +implementation and regression oracle for [causal-triangulations](https://github.com/acgetchell/causal-triangulations), its supported Rust successor. The -maintenance and archival scope is tracked by -[issue #90](https://github.com/acgetchell/CDT-plusplus/issues/90). +v1.0.0 release scope is tracked by [issue #90](https://github.com/acgetchell/CDT-plusplus/issues/90). Archiving the +GitHub repository or making it read-only is a separate future maintainer decision, not settled policy for immediately +after v1.0.0. ## Accepted work -Until archival, contributions should be limited to: +Contributions should be limited to: - correctness fixes, especially for causal invariants, bistellar moves, and scientific results; - deterministic tests, reproducibility improvements, and cross-implementation validation; - documentation, build, CI, portability, dependency, and release-readiness fixes; - work already approved in a project issue or release milestone, including [Qt restoration #98](https://github.com/acgetchell/CDT-plusplus/issues/98) and - [domain invariant work #101](https://github.com/acgetchell/CDT-plusplus/issues/101); and -- changes required to complete the v1.0.0 release and Zenodo archival handoff. + [domain invariant work #101](https://github.com/acgetchell/CDT-plusplus/issues/101) and + [Python experiment modernization #143](https://github.com/acgetchell/CDT-plusplus/issues/143); and +- changes required to complete the v1.0.0 release and Zenodo deposit. -New simulation features, 3+1D/4D development, and unrelated C++ expansion are out of scope. Propose ongoing feature -development in the Rust successor instead. If a change is not already tracked, open an issue before investing in a -substantial implementation so its maintenance value and scope can be agreed upon. +New simulation features, 3+1D/4D development, and unrelated C++ expansion remain out of scope unless a project issue +explicitly approves them. Potential future 4D research does not authorize implementation by itself. If a change is +not already tracked, open an issue before investing in a substantial implementation so its maintenance value and +scope can be agreed upon. ## Contribution workflow @@ -49,10 +51,10 @@ substantial implementation so its maintenance value and scope can be agreed upon ``` `just check` is the fast, non-mutating source and tooling gate, including the repository-owned Semgrep policy and - its fixtures. `just ci` adds the supported build and complete 24-entry CTest suite: all 103 doctest unit scenarios - and 23 CLI integration tests. `just build-parallel` builds the distinct CGAL/oneTBB configuration and runs the same - scientific suite plus the - replayable parallel stress launcher, for 25 entries. When changing C++ behavior, also run + its fixtures. `just ci` adds the supported build and complete 127-entry CTest suite: 104 doctest unit scenarios and + 23 CLI integration tests. `just build-parallel` builds the distinct CGAL/oneTBB configuration and runs its + 127-entry suite: 103 ordinary doctest scenarios, one replayable parallel stress launcher containing five scenarios, + and the same 23 CLI integration tests. When changing C++ behavior, also run `just clang-tidy` with the pinned LLVM 22 toolchain and review its advisory diagnostics. GitHub Actions runs `just ci` in its Ubuntu GCC, Ubuntu Clang, macOS AppleClang, and Windows MSVC jobs. The two Ubuntu jobs also run `just build-parallel` to exercise the opt-in CGAL/oneTBB contract. Sanitizer and coverage @@ -93,14 +95,13 @@ Project source files belong in `src`, public or shared headers in `include`, and CMake targets, presets, CTest registrations, Just recipes, and pinned vcpkg manifest rather than introducing parallel build paths. -## Release and archival +## Release and repository lifecycle -Release candidates, the final tag, and the archival handoff follow the -[`docs/RELEASING.md`](../docs/RELEASING.md) runbook. The final v1.0.0 release will be tagged from `main` and archived -through [Zenodo]. Release metadata and the archival handoff are tracked by -[issue #96](https://github.com/acgetchell/CDT-plusplus/issues/96). After archival, the repository will be read-only and -will no longer accept issues or pull requests. Further development should occur in -[causal-triangulations](https://github.com/acgetchell/causal-triangulations) or in an independent fork. +Release candidates, the final tag, and the Zenodo deposit follow the +[`docs/RELEASING.md`](../docs/RELEASING.md) runbook. The final v1.0.0 release will be tagged from `main`; release +metadata and the Zenodo handoff are tracked by [issue #96](https://github.com/acgetchell/CDT-plusplus/issues/96). +Making the GitHub repository read-only would require a separate explicit maintainer decision. Until then, issues and +pull requests remain governed by the scoped contribution policy above. Contributors retain credit through the repository history and resulting project citation metadata. diff --git a/.github/ISSUE_TEMPLATE/feature_request.md b/.github/ISSUE_TEMPLATE/feature_request.md index 57adfd541..0e89d0914 100644 --- a/.github/ISSUE_TEMPLATE/feature_request.md +++ b/.github/ISSUE_TEMPLATE/feature_request.md @@ -9,8 +9,10 @@ assignees: '' ## Problem -Describe the problem this request would solve. CDT++ is approaching its final archival release; new development may -belong in the supported [causal-triangulations](https://github.com/acgetchell/causal-triangulations) successor. +Describe the problem this request would solve. CDT++ remains a maintained C++ reference implementation, while broad +new development may belong in the supported +[causal-triangulations](https://github.com/acgetchell/causal-triangulations) successor. Explain why this repository is +the right ownership boundary. ## Proposed solution diff --git a/.github/dependabot.yml b/.github/dependabot.yml index 993b00f4d..ff756a901 100644 --- a/.github/dependabot.yml +++ b/.github/dependabot.yml @@ -13,6 +13,11 @@ updates: open-pull-requests-limit: 10 groups: github-actions: + applies-to: version-updates + patterns: + - "*" + github-actions-security: + applies-to: security-updates patterns: - "*" @@ -28,6 +33,11 @@ updates: open-pull-requests-limit: 10 groups: dependencies: + applies-to: version-updates + patterns: + - "*" + python-security: + applies-to: security-updates patterns: - "*" @@ -46,5 +56,6 @@ updates: open-pull-requests-limit: 10 groups: dependencies: + applies-to: version-updates patterns: - "*" diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 8460d1c45..18f0ac40f 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -93,9 +93,15 @@ jobs: echo "llvm=$(just --evaluate llvm_version)" echo "ninja=$(just --evaluate ninja_version)" echo "ninja-windows-wheel=$(just --evaluate ninja_windows_wheel_version)" + echo "typos=$(just --evaluate typos_version)" echo "uv=$(just --evaluate uv_version)" } >> "$GITHUB_OUTPUT" + - name: Set up typos + uses: taiki-e/install-action@6a1bd70eaac3c8bdf093356838d7ee09fda951cf # v2.85.5 + with: + tool: typos@${{ steps.tool-versions.outputs.typos }} + - name: Set up canonical CI environment with pkgx if: runner.os != 'Windows' uses: pkgxdev/setup@4d4ae97af87ccb39ab8be4e073dea697fef2c6f7 # v5.0.0 diff --git a/.github/workflows/python-experiments.yml b/.github/workflows/python-experiments.yml new file mode 100644 index 000000000..8678395ed --- /dev/null +++ b/.github/workflows/python-experiments.yml @@ -0,0 +1,84 @@ +--- +name: Python experiments + +"on": + push: + branches: + - main + paths: + - .github/actions/setup-just/action.yml + - .github/workflows/python-experiments.yml + - .python-version + - Justfile + - pyproject.toml + - scripts/experiment_tests/** + - scripts/mnist_experiment.py + - scripts/optimize_initialize.py + - ty.toml + - uv.lock + pull_request: + branches: + - main + paths: + - .github/actions/setup-just/action.yml + - .github/workflows/python-experiments.yml + - .python-version + - Justfile + - pyproject.toml + - scripts/experiment_tests/** + - scripts/mnist_experiment.py + - scripts/optimize_initialize.py + - ty.toml + - uv.lock + workflow_dispatch: + +permissions: + contents: read + +concurrency: + group: ${{ github.workflow }}-${{ github.ref }} + cancel-in-progress: true + +jobs: + offline: + name: ${{ matrix.name }} + runs-on: ${{ matrix.os }} + timeout-minutes: 30 + + strategy: + fail-fast: false + matrix: + include: + - name: Ubuntu x86-64 + os: ubuntu-latest + - name: macOS ARM64 + os: macos-15 + - name: Windows x86-64 + os: windows-latest + + steps: + - name: Check out repository + uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1 + with: + persist-credentials: false + + - name: Set up Just + uses: ./.github/actions/setup-just + + - name: Resolve uv version + id: tool-versions + shell: bash + run: echo "uv=$(just --evaluate uv_version)" >> "$GITHUB_OUTPUT" + + - name: Set up Python + uses: actions/setup-python@5fda3b95a4ea91299a34e894583c3862153e4b97 # v7.0.0 + with: + python-version-file: .python-version + + - name: Set up uv + uses: astral-sh/setup-uv@c771a70e6277c0a99b617c7a806ffedaca235ff9 # v9.0.0 + with: + version: ${{ steps.tool-versions.outputs.uv }} + + - name: Resolve wheels, type-check, and run offline experiment tests + run: just python-experiment-check diff --git a/.python-version b/.python-version index e4fba2183..6324d401a 100644 --- a/.python-version +++ b/.python-version @@ -1 +1 @@ -3.12 +3.14 diff --git a/Justfile b/Justfile index c1c4419e3..d6c880989 100644 --- a/Justfile +++ b/Justfile @@ -1,15 +1,17 @@ # Justfile for the CDT++ maintenance workflow. # Usage: just or just --list -set minimum-version := "1.57.0" +set minimum-version := "1.58.0" set shell := ["bash", "-euo", "pipefail", "-c"] -just_version := "1.57.0" +just_version := "1.58.0" uv_version := "0.12.1" +python_version := "3.14.6" git_cliff_version := "2.13.1" actionlint_version := "1.7.12" pinact_version := "4.1.1" pinact_module := "github.com/suzuki-shunsuke/pinact/v4/cmd/pinact@v" + pinact_version +typos_version := "1.49.0" llvm_version := "22" cmake_minimum_version := "4.4.0" cmake_version := "4.4.1" @@ -42,12 +44,12 @@ build-debug: # Run fast, non-mutating local validation. [group('workflows')] -check: _justfile-check _format-check _yaml-check _action-lint _zizmor _whitespace-check _cmake-check release-check python-check reference-check semgrep semgrep-test +check: _justfile-check _format-check _yaml-check _action-lint _zizmor _whitespace-check _cmake-check release-check python-check reference-check semgrep semgrep-test spell-check @echo "Checks complete." # Run the comprehensive pre-commit/pre-push validation gate. [group('workflows')] -ci: check _pinact-check reference-generated-check +ci: check _pinact-check reference-generated-check python-package-check @echo "CI validation complete." # Configure dependencies before CodeQL begins tracing the C++ build. @@ -161,7 +163,7 @@ clang-tidy: "+llvm.org@{{ llvm_version }}" \ "+cmake.org@{{ cmake_version }}" \ "+ninja-build.org@{{ ninja_version }}" \ - +python.org@3.11.15 \ + "+python.org@{{ python_version }}" \ +gnu.org/m4@1.4.21 \ +gnu.org/autoconf@2.73.0 \ +gnu.org/autoconf-archive@2024.10.16 \ @@ -230,6 +232,11 @@ semgrep-test: _sync-python-dev uv run --no-sync semgrep scan --test --strict --config "$config_path" "$fixture" done < <(find tests/semgrep -type f ! -name '*.fixed' -print0) +# Check repository text and identifiers for common spelling mistakes. +[group('workflows')] +spell-check: _ensure-typos + typos + # Build and exercise one supported Linux sanitizer configuration. [group('workflows')] sanitize kind: @@ -240,6 +247,7 @@ sanitize kind: "+llvm.org@{{ llvm_version }}" \ "+cmake.org@{{ cmake_version }}" \ "+ninja-build.org@{{ ninja_version }}" \ + "+python.org@{{ python_version }}" \ -- ./scripts/sanitizer.sh "{{ kind }}" fi exec ./scripts/sanitizer.sh "{{ kind }}" @@ -249,6 +257,50 @@ sanitize kind: python-check: python-format-check python-lint python-typecheck python-support-test python-entrypoint-test @echo "Python source checks complete." +# Install, type-check, and exercise the heavyweight PyTorch/Comet surface without networked services or datasets. +[group('workflows')] +python-experiment-check: _sync-python-experiments + uv run --no-sync ty check scripts/mnist_experiment.py scripts/optimize_initialize.py scripts/experiment_tests/*.py --error all + MPLCONFIGDIR="${TMPDIR:-/tmp}/cdt-matplotlib-cache" uv run --no-sync python -c "import comet_ml; import torch; import torchvision; print(comet_ml.__version__, torch.__version__, torchvision.__version__)" + MPLCONFIGDIR="${TMPDIR:-/tmp}/cdt-matplotlib-cache" uv run --no-sync python -m unittest scripts.experiment_tests.test_comet_pytorch + MPLCONFIGDIR="${TMPDIR:-/tmp}/cdt-matplotlib-cache" uv run --no-sync python -m unittest scripts.experiment_tests.test_mnist_training + +# Build both Python artifacts and exercise every installed entry point outside the checkout. +[group('workflows')] +python-package-check: _sync-python-dev + #!/usr/bin/env bash + set -euo pipefail + artifact_directory="$(mktemp -d "${TMPDIR:-/tmp}/cdt-python-artifacts.XXXXXX")" + consumer_directory="$(mktemp -d "${TMPDIR:-/tmp}/cdt-python-consumer.XXXXXX")" + cleanup() { + rm -rf "$artifact_directory" "$consumer_directory" + } + trap cleanup EXIT + + uv build --out-dir "$artifact_directory" + wheel="$(find "$artifact_directory" -maxdepth 1 -name '*.whl' -print -quit)" + [[ -n "$wheel" ]] || { echo "uv build did not produce a wheel." >&2; exit 1; } + uv venv --python {{ python_version }} "$consumer_directory/.venv" + uv pip install --python "$consumer_directory/.venv" --no-build "$wheel" + + if [[ -x "$consumer_directory/.venv/bin/python" ]]; then + python="$consumer_directory/.venv/bin/python" + scripts_directory="$consumer_directory/.venv/bin" + executable_suffix="" + else + python="$consumer_directory/.venv/Scripts/python.exe" + scripts_directory="$consumer_directory/.venv/Scripts" + executable_suffix=".exe" + fi + ( + cd "$consumer_directory" + "$python" -c "import scripts" + "$scripts_directory/cdt-bootstrap-vcpkg$executable_suffix" --help >/dev/null + "$scripts_directory/cdt-optimize-initialize$executable_suffix" --help >/dev/null + "$scripts_directory/cdt-mnist-experiment$executable_suffix" --help >/dev/null + "$scripts_directory/cdt-tag-release$executable_suffix" --help >/dev/null + ) + # Apply Ruff lint fixes and formatting to Python source. [group('workflows')] python-fix: _sync-python-dev @@ -418,6 +470,21 @@ _ensure-git-cliff: exit 1 fi +[private] +_ensure-typos: + #!/usr/bin/env bash + set -euo pipefail + command -v typos >/dev/null || { + echo "typos-cli {{ typos_version }} is required." >&2 + echo "Install it with: cargo install typos-cli --version {{ typos_version }} --locked" >&2 + exit 1 + } + actual_version="$(typos --version | awk '{print $2}')" + if [[ "$actual_version" != "{{ typos_version }}" ]]; then + echo "typos-cli {{ typos_version }} is required; found $actual_version." >&2 + exit 1 + fi + [private] _ensure-uv: #!/usr/bin/env bash diff --git a/README.md b/README.md index 90f30b6af..93f8c8d5b 100644 --- a/README.md +++ b/README.md @@ -13,12 +13,15 @@ ## Maintenance status -CDT++ v1.0.0-rc3 is the release candidate for the final C++23 release, v1.0.0, after which this repository will be -archived. It is -maintained as an independent scientific reference and regression oracle for +CDT++ v1.0.0-rc3 is the current C++23 release candidate. The repository remains maintained as an independent +scientific reference and regression oracle for [causal-triangulations](https://github.com/acgetchell/causal-triangulations), the supported Rust successor. New C++ work is limited to correctness, reproducibility, cross-implementation validation, the complete supported 2+1D move -set, and the final release contract tracked by [issue #90](https://github.com/acgetchell/CDT-plusplus/issues/90). +set, and work approved in project issues. The v1.0.0 release contract remains tracked by +[issue #90](https://github.com/acgetchell/CDT-plusplus/issues/90); making the GitHub repository read-only is a +separate future lifecycle decision rather than an automatic consequence of that release. Optional Python research +tooling is maintained by [issue #143](https://github.com/acgetchell/CDT-plusplus/issues/143) without making Python a +scientific oracle. ## Table of contents @@ -232,13 +235,12 @@ Windows development. ### Current reference-suite status With the pinned baseline, the reference configuration and build succeed on macOS with AppleClang. The cross-platform -`just build` command runs all 24 CTest entries through `scripts/build.sh` on Unix and `scripts/build.bat` on Windows: -one unit-test launcher containing 103 doctest scenarios and 23 CLI integration tests. The same `reference-smoke` preset -is the supported local and CI contract; there are no overlapping focused registrations that can pass while omitting -another doctest suite. The parallel-enabled AddressSanitizer and `parallel` -configurations add one launcher containing five scenarios, for 25 CTest -entries including the -replayable stress contract. +`just build` command runs all 127 CTest registrations through `scripts/build.sh` on Unix and `scripts/build.bat` on +Windows: 104 doctest scenarios from the unit-test executable and 23 CLI integration tests. The same `reference-smoke` +preset is the supported local and CI contract; there are no overlapping focused registrations that can pass while +omitting another doctest suite. The current `parallel` preset also registers 127 tests: 103 ordinary doctest scenarios, +one parallel launcher containing five scenarios, and the same 23 CLI integration tests. The parallel-enabled +AddressSanitizer configuration exercises the same replayable stress contract. ## Setup @@ -253,7 +255,7 @@ The smallest pkgx-assisted host setup is: - Xcode Command Line Tools on macOS, or a C++23 compiler and base build environment on Linux - pkgx - Just, used by the recipes and `scripts/pkgx-build.sh` to resolve the repository's tool-version pins -- Python 3.12 for native dependency bootstrap, and uv when checking or running the Python support scripts +- Python 3.14 for native dependency bootstrap, and uv when checking or running the Python support scripts - Doxygen 1.17.0 and Graphviz 15.1.0 when checking or generating API documentation; pkgx can supply both The pkgx build and documentation launchers supply their required tools ephemerally, including Git, Bash, CMake, @@ -302,10 +304,11 @@ just sync-vcpkg-tool-pins # Sync the vcpkg tool release and Windows hashes just python-sync # Install the locked Python development environment just python-check # Check Python formatting, lint, and types just python-fix # Apply safe Ruff fixes and formatting +just spell-check # Check repository text and identifiers for typos ``` -`check` covers repository-wide C++ formatting, Python formatting/lint/type checks, release metadata and citation -fields, YAML, GitHub Actions syntax and security, whitespace, and CMake preset parsing. `ci` adds the pinact policy +`check` covers repository-wide C++ formatting, Python formatting/lint/type checks, spelling, release metadata and +citation fields, YAML, GitHub Actions syntax and security, whitespace, and CMake preset parsing. `ci` adds the pinact policy check and the supported build/test contract. Documentation validation remains available separately through `just docs-check`. The GitHub Actions Ubuntu GCC, Ubuntu Clang, macOS AppleClang, and Windows MSVC jobs all run `just ci`; the two Ubuntu jobs also @@ -321,7 +324,7 @@ example: ```bash just python-sync -pkgx +just.systems@1.57.0 +git-scm.org +cmake.org@4.4.1 +ninja-build.org +python.org just check +pkgx +just.systems@1.58.0 +git-scm.org +cmake.org@4.4.1 +ninja-build.org +python.org just check ``` All configure paths require CMake 4.4.0 or newer. The Justfile owns the tested @@ -592,7 +595,7 @@ separate branch-coverage rate. ### Static Analysis -Python 3.12 is selected by [`.python-version`](.python-version), uv locks the environment in `uv.lock`, Ruff owns +Python 3.14 is selected by [`.python-version`](.python-version), uv locks the environment in `uv.lock`, Ruff owns Python formatting and linting, and ty owns static type checking. Run `just python-sync` once and then use `just python-check` or `just python-fix`; both commands are also part of the repository-wide validation recipes. @@ -615,24 +618,52 @@ CGAL/TBB path and its parallel contract; ThreadSanitizer exercises the default s ## Optimizing Parameters -[CometML] is used to record [Experiments] conducted by the `cdt-optimize-initialize` command; -`cdt-mnist-experiment` runs the existing TensorFlow MNIST experiment. Both commands are registered in -`pyproject.toml`, while their optional, heavyweight dependencies remain outside the normal development environment. -Synchronize them from the same uv lockfile when working on the experiment scripts: +[CometML] can mirror [Experiments] conducted by `cdt-optimize-initialize` and `cdt-mnist-experiment`. Each command +writes configurations, seeds, metrics, plots or checkpoints, artifact digests, and provenance to its requested local +output directory; Comet is an optional indexed or hosted view and is never the only copy. Preserve that directory +with its retained inputs, source checkout, and `uv.lock` as the reproduction bundle. Both commands are registered in +`pyproject.toml`, while their heavyweight dependencies remain outside the normal development environment. The +default development group contains no PyTorch, TorchVision, Matplotlib, or Comet packages. + +The retained MNIST command is a small PyTorch portability example, not a CDT scientific oracle. It preserves the +historical dense-network shape and requests deterministic PyTorch CPU algorithms for replay within the same supported +software and hardware environment; bitwise identity across PyTorch releases, platforms, or processor architectures +is not guaranteed. It does not implement 4D CDT or supply results for prospective Praxis research. The lockfile +selects PyTorch 2.13 and TorchVision 0.28 regular-CPython 3.14 wheels from PyTorch's explicit CPU index; CUDA, ROCm, +free-threaded Python, and accelerator CI are outside the supported baseline. Comet 3.58 is locked from its universal +wheel. + +Synchronize and verify the optional group separately from ordinary source and C++ checks: ```bash just python-sync-experiments +just python-experiment-check uv run --no-sync cdt-optimize-initialize uv run --no-sync cdt-mnist-experiment ``` -Run these commands from the repository root. Set `COMET_API_KEY` before starting the parameter optimization; use -`--repository-root` when invoking it from another directory. The optimizer uses seed `92` by default for every -parameter pair so stochastic inputs and provenance can be compared; pass `--seed SEED` to select and record another -root seed. Fresh CGAL triangulations are subject to the limits in the -[reproducibility contract](docs/reproducibility.md). The experiment results are then available in Comet. -Migration of these legacy scripts to Python 3.14, PyTorch, and the current Comet API is tracked by -[#104](https://github.com/acgetchell/CDT-plusplus/issues/104). +Run these commands from the repository root. The initializer optimizer writes one directory per parameter pair under +`out/experiments/initialize`; use `--output-directory` to retain the record elsewhere and `--repository-root` when +invoking it from another directory. Each invocation requires a nonexistent output path and publishes that directory +only after the complete sweep succeeds, so select a new path for every retained run. It uses seed `92` by default for +every parameter pair so stochastic inputs and provenance can be compared; pass `--seed SEED` to select and record +another root seed. Each record identifies the initializer by path, size, and SHA-256 digest and records the source +commit, worktree status, and SHA-256 digest of any tracked source changes. Fresh CGAL triangulations are subject to +the limits in the [reproducibility contract](docs/reproducibility.md). + +The MNIST example retains downloaded inputs under `out/experiments/data` and writes `configuration.json`, +`checkpoint.pt`, and a `run.json` manifest containing size and SHA-256 records for its artifacts under +`out/experiments/mnist`. Preserve both directories together; use `--data-directory`, `--output-directory`, and +`--seed` for an explicit layout, or `--no-download` to require already-local inputs. As with the optimizer, every run +requires a nonexistent output path and becomes visible there only after all local and offline-Comet artifacts close +successfully. Tests use synthetic tensors and never download the dataset. + +Comet is disabled by default for both commands. Pass `--comet offline` to create an uploadable local Comet archive, +or set `COMET_API_KEY` and pass `--comet online` to mirror the run to the hosted service. The PyTorch command starts +Comet before importing Torch, enables graph and loss logging, watches weights and gradients, explicitly logs declared +parameters and metrics, and mirrors the final checkpoint with Comet's current `start()`, `watch()`, and `log_model()` +APIs. The migration and its relationship to possible future 4D work are tracked by +[#143](https://github.com/acgetchell/CDT-plusplus/issues/143). ## Visualization diff --git a/docs/Doxyfile b/docs/Doxyfile index 4d3560763..860f0bf41 100644 --- a/docs/Doxyfile +++ b/docs/Doxyfile @@ -562,7 +562,7 @@ INTERNAL_DOCS = NO # names in lower-case letters. If set to YES, upper-case letters are also # allowed. This is useful if you have classes or files whose names only differ # in case and if your file system supports case sensitive file names. Windows -# (including Cygwin) ands Mac users are advised to set this option to NO. +# (including Cygwin) and Mac users are advised to set this option to NO. # The default value is: system dependent. CASE_SENSE_NAMES = NO diff --git a/docs/RELEASING.md b/docs/RELEASING.md index b4ce441dd..d5f10ea81 100644 --- a/docs/RELEASING.md +++ b/docs/RELEASING.md @@ -3,7 +3,7 @@ This guide documents the release flow for CDT++ release candidates and the final `v1.0.0` release: prepare a dedicated release pull request, merge it, create an annotated tag with reviewed release notes, and create the GitHub -release. The final stable release also includes the Zenodo archival handoff +release. The final stable release also includes the Zenodo deposit handoff tracked by [issue #96]. CDT++ is not published to a package registry. The GitHub release and its @@ -279,14 +279,16 @@ jq -e 'select( )' <<<"$ZENODO_DELIVERY" ``` -For an intentionally archived release candidate, verify the Zenodo record and -DOI without treating it as the final archival handoff. For a stable release, +For a release candidate intentionally deposited with Zenodo, verify the record +and DOI without treating it as the final stable handoff. For a stable release, complete the Zenodo handoff tracked in [issue #96]: confirm that Zenodo received the release, verify its version, date, title, authors, license, repository URL, and files, and record the final DOI according to the archival plan. If the DOI was unavailable before tagging, update `CITATION.cff` in a focused follow-up -pull request rather than rewriting the tag. Complete repository archival only -after the GitHub release and Zenodo record are correct. +pull request rather than rewriting the tag. A Zenodo deposit does not make the +GitHub repository read-only. Repository archival is a separate lifecycle action +that requires an explicit maintainer decision; if it is approved later, perform +it only after the GitHub release and Zenodo record are correct. ## Step 4: Clean up diff --git a/docs/multithreading.md b/docs/multithreading.md index a9f47633e..d5e78fd84 100644 --- a/docs/multithreading.md +++ b/docs/multithreading.md @@ -1,6 +1,6 @@ # Multithreaded CGAL contract -CDT++ retains one bounded multithreaded capability for the archived C++ +CDT++ retains one bounded multithreaded capability for the maintained C++ reference: CGAL may use oneTBB for bulk 3D Delaunay insertion and range removal. The deterministic `reference` configuration remains the canonical single-threaded correctness oracle. Enabling the parallel configuration does diff --git a/include/Utilities.hpp b/include/Utilities.hpp index b2c64a366..06e397440 100644 --- a/include/Utilities.hpp +++ b/include/Utilities.hpp @@ -1796,7 +1796,7 @@ namespace cdt::utilities /// @brief Write the runtime results to a file /// @details The filename is generated by the **make_filename()** and - /// writen using another **write_file()** function, which is currently + /// written using another **write_file()** function, which is currently /// implemented using the << operator for triangulations. /// @tparam ManifoldType The manifold type /// @param t_universe The simplicial manifold diff --git a/pyproject.toml b/pyproject.toml index 30f646021..a57a38bbf 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -3,7 +3,7 @@ name = "cdt-plusplus-scripts" # PEP 440 spelling of the CDT++ v1.0.0-rc3 release. version = "1.0.0rc3" description = "Python support and experiment scripts for CDT++" -requires-python = ">=3.12,<3.13" +requires-python = ">=3.14,<3.15" dependencies = [] [project.scripts] @@ -27,13 +27,23 @@ no-build-package = [ "pyyaml", "ruff", "semgrep", - "tensorflow", + "torch", + "torchvision", "ty", "uv-build", "yamllint", ] package = true +[[tool.uv.index]] +name = "pytorch-cpu" +url = "https://download.pytorch.org/whl/cpu" +explicit = true + +[tool.uv.sources] +torch = { index = "pytorch-cpu" } +torchvision = { index = "pytorch-cpu" } + [tool.uv.build-backend] module-name = "scripts" module-root = "" @@ -43,6 +53,7 @@ source-exclude = [ "scripts/generate_changelog.py", "scripts/release_check.py", "scripts/semgrep_fixture_config.py", + "scripts/experiment_tests/**", "scripts/tests/**", ] @@ -60,13 +71,14 @@ experiments = [ "comet-ml>=3.58.3,<4", "matplotlib>=3.10,<4", "numpy>=2,<3", - "tensorflow>=2.21,<2.22", + "torch>=2.13,<2.14", + "torchvision>=0.28,<0.29", ] [tool.ruff] line-length = 160 src = ["scripts"] -target-version = "py312" +target-version = "py314" [tool.ruff.lint] select = [ @@ -148,6 +160,10 @@ ignore = [ ] [tool.ruff.lint.per-file-ignores] +"scripts/experiment_tests/test_*.py" = [ + "PT009", # The optional experiment suite intentionally uses unittest. + "PT027", # The optional experiment suite intentionally uses unittest. +] "scripts/tests/test_*.py" = [ "PT009", # The dependency-free support-script suite intentionally uses unittest. "PT027", # The dependency-free support-script suite intentionally uses unittest. diff --git a/scripts/bootstrap_vcpkg.py b/scripts/bootstrap_vcpkg.py index 77da6154a..ad1379a87 100644 --- a/scripts/bootstrap_vcpkg.py +++ b/scripts/bootstrap_vcpkg.py @@ -1,7 +1,5 @@ """Bootstrap and validate the repository-pinned vcpkg checkout.""" -from __future__ import annotations - import argparse import hashlib import json diff --git a/scripts/experiment_tests/__init__.py b/scripts/experiment_tests/__init__.py new file mode 100644 index 000000000..07c998b0d --- /dev/null +++ b/scripts/experiment_tests/__init__.py @@ -0,0 +1 @@ +"""Offline tests that require the optional experiment dependency group.""" diff --git a/scripts/experiment_tests/test_comet_pytorch.py b/scripts/experiment_tests/test_comet_pytorch.py new file mode 100644 index 000000000..3e105181f --- /dev/null +++ b/scripts/experiment_tests/test_comet_pytorch.py @@ -0,0 +1,71 @@ +"""Offline integration test for Comet's current PyTorch API.""" + +import json +import unittest +from pathlib import Path, PurePosixPath +from tempfile import TemporaryDirectory +from zipfile import ZipFile + +from scripts.mnist_experiment import _build_model, _RunConfig, _start_comet + + +class CometPyTorchIntegrationTests(unittest.TestCase): + """Exercise start, watch, explicit logging, and checkpoint logging offline.""" + + def test_offline_comet_run_records_a_pytorch_checkpoint(self) -> None: + """The integration needs neither credentials nor hosted services.""" + with TemporaryDirectory() as temporary_directory: + root = Path(temporary_directory) + config = _RunConfig( + batch_size=2, + comet_mode="offline", + data_directory=root / "data", + download=False, + epochs=1, + learning_rate=0.001, + output_directory=root / "run", + seed=0, + ) + comet_run = _start_comet(config, config.output_directory) + try: + import torch # noqa: PLC0415 + + torch.manual_seed(config.seed) + model = _build_model(torch) + comet_run.watch(model) + inputs = torch.zeros((2, 1, 28, 28)) + labels = torch.tensor([0, 1]) + loss = torch.nn.CrossEntropyLoss()(model(inputs), labels) + loss.backward() + comet_run.experiment.log_parameters({"seed": config.seed}) + comet_run.experiment.log_metric("loss", float(loss.item()), epoch=1) + checkpoint = {"loss": float(loss.item()), "model_state_dict": model.state_dict()} + comet_run.log_model(comet_run.experiment, checkpoint, model_name="cdt-mnist-smoke") + finally: + comet_run.experiment.end() + + archives = list((config.output_directory / "comet").glob("*.zip")) + self.assertEqual(len(archives), 1) + with ZipFile(archives[0]) as archive: + records = [json.loads(line) for line in archive.read("messages.json").splitlines()] + + metrics = [record["payload"].get("metric", {}) for record in records if record["type"] == "metric_msg"] + parameters = [record["payload"].get("param", {}) for record in records if record["type"] == "parameter_msg"] + uploads = [record["payload"] for record in records if record["type"] == "file_upload"] + self.assertTrue(any(metric.get("metricName") == "loss" and metric.get("epoch") == 1 for metric in metrics)) + self.assertTrue(any(parameter.get("paramName") == "seed" and parameter.get("paramValue") == 0 for parameter in parameters)) + self.assertTrue(any(record["type"] == "graph" for record in records)) + self.assertTrue(any(upload["upload_type"] == "histogram3d" for upload in uploads)) + self.assertTrue( + any( + upload["upload_type"] == "model-element" + and upload["additional_params"].get("groupingName") == "cdt-mnist-smoke" + and PurePosixPath(str(upload["additional_params"].get("fileName", "")).replace("\\", "/")).parent == PurePosixPath("model-data") + and PurePosixPath(str(upload["additional_params"].get("fileName", "")).replace("\\", "/")).name == "comet-torch-model.pth" + for upload in uploads + ) + ) + + +if __name__ == "__main__": + unittest.main() diff --git a/scripts/experiment_tests/test_mnist_training.py b/scripts/experiment_tests/test_mnist_training.py new file mode 100644 index 000000000..9c246cd4f --- /dev/null +++ b/scripts/experiment_tests/test_mnist_training.py @@ -0,0 +1,52 @@ +"""Synthetic-data determinism test for the PyTorch training loop.""" + +import unittest +from typing import Any, NamedTuple + +from scripts.mnist_experiment import _build_model, _evaluate, _train_epoch + + +class _TrainingResult(NamedTuple): + """Replay-sensitive metrics and model state from one training run.""" + + metrics: tuple[float, float, float] + weights: dict[str, Any] + + +class MnistTrainingTests(unittest.TestCase): + """Exercise the CPU baseline without downloading MNIST.""" + + @staticmethod + def _train_once() -> _TrainingResult: + import torch # noqa: PLC0415 + + torch.manual_seed(7) + torch.use_deterministic_algorithms(mode=True) + inputs = torch.arange(16 * 28 * 28, dtype=torch.float32).reshape(16, 1, 28, 28) / 1000.0 + labels = torch.arange(16) % 10 + dataset = torch.utils.data.TensorDataset(inputs, labels) + generator = torch.Generator().manual_seed(7) + training_loader = torch.utils.data.DataLoader(dataset, batch_size=4, generator=generator, num_workers=0, shuffle=True) + test_loader = torch.utils.data.DataLoader(dataset, batch_size=4, num_workers=0, shuffle=False) + model = _build_model(torch) + loss_function = torch.nn.CrossEntropyLoss() + optimizer = torch.optim.Adam(model.parameters(), lr=0.001) + training_loss = _train_epoch(model, training_loader, loss_function, optimizer) + test_loss, accuracy = _evaluate(torch, model, test_loader, loss_function) + return _TrainingResult(metrics=(training_loss, test_loss, accuracy), weights=model.state_dict()) + + def test_training_is_replayable_on_synthetic_cpu_data(self) -> None: + """The same seed and local data produce identical metrics and weights.""" + import torch # noqa: PLC0415 + + first = self._train_once() + second = self._train_once() + self.assertEqual(first.metrics, second.metrics) + self.assertEqual(first.weights.keys(), second.weights.keys()) + for name in first.weights: + with self.subTest(parameter=name): + self.assertTrue(torch.equal(first.weights[name], second.weights[name])) + + +if __name__ == "__main__": + unittest.main() diff --git a/scripts/generate_changelog.py b/scripts/generate_changelog.py index 0a5a6dd8e..0577f513d 100644 --- a/scripts/generate_changelog.py +++ b/scripts/generate_changelog.py @@ -1,7 +1,5 @@ """Generate a deterministic release changelog with git-cliff.""" -from __future__ import annotations - import argparse import json import os diff --git a/scripts/generate_reference_fixtures.py b/scripts/generate_reference_fixtures.py index fee339be8..df35ad8e4 100644 --- a/scripts/generate_reference_fixtures.py +++ b/scripts/generate_reference_fixtures.py @@ -1,7 +1,5 @@ """Regenerate every CDT++ reference artifact from one clean source commit.""" -from __future__ import annotations - import argparse import hashlib import json diff --git a/scripts/mnist_experiment.py b/scripts/mnist_experiment.py index 191f288f5..33e19dd30 100644 --- a/scripts/mnist_experiment.py +++ b/scripts/mnist_experiment.py @@ -1,62 +1,458 @@ -"""Run the CDT++ TensorFlow MNIST experiment.""" - -from __future__ import annotations +"""Run the CDT++ CPU-portable PyTorch MNIST experiment.""" import argparse +import hashlib +import json +import math +import os +import platform +import shutil import sys -from typing import TYPE_CHECKING +import tempfile +from contextlib import contextmanager +from dataclasses import asdict, dataclass +from importlib.metadata import PackageNotFoundError, version +from pathlib import Path +from typing import TYPE_CHECKING, Literal, Protocol, cast if TYPE_CHECKING: - from collections.abc import Sequence + from collections.abc import Iterator, Mapping, Sequence + from types import ModuleType + + from torch import Tensor + from torch.nn import CrossEntropyLoss, Module + from torch.optim import Optimizer + from torch.utils.data import DataLoader + +MIN_TORCH_SEED = -(1 << 63) +MAX_TORCH_SEED = (1 << 64) - 1 +PACKAGE_NAME = "cdt-plusplus-scripts" + + +@dataclass(frozen=True) +class _RunConfig: + """Inputs needed to reproduce one local MNIST run.""" + + batch_size: int + comet_mode: Literal["disabled", "offline", "online"] + data_directory: Path + download: bool + epochs: int + learning_rate: float + output_directory: Path + seed: int + + +class _Experiment(Protocol): + """Comet operations mirrored by the PyTorch experiment.""" + + def log_parameters(self, parameters: Mapping[str, object]) -> object: + """Record the complete declared training configuration.""" + ... + + def log_metric(self, name: str, value: float, *, epoch: int | None = None) -> object: + """Record one training or evaluation metric.""" + ... + + def end(self) -> object: + """Flush and close the Comet run.""" + ... + + +class _Watch(Protocol): + """Callable interface for Comet's PyTorch parameter watcher.""" + + def __call__(self, model: object) -> object: + """Register a model for weight, bias, and gradient logging.""" + ... + + +class _LogModel(Protocol): + """Callable interface for Comet's PyTorch checkpoint logger.""" + + def __call__(self, experiment: _Experiment, model: object, *, model_name: str) -> object: + """Store a model or training checkpoint in Comet.""" + ... + + +@dataclass(frozen=True) +class _CometRun: + """Comet integration functions loaded before PyTorch.""" + + experiment: _Experiment + log_model: _LogModel + watch: _Watch + + +def _positive_int(value: str) -> int: + """Parse a strictly positive integer command-line value.""" + parsed = int(value, 10) + if parsed <= 0: + message = "value must be greater than zero" + raise argparse.ArgumentTypeError(message) + return parsed + + +def _positive_float(value: str) -> float: + """Parse a strictly positive floating-point command-line value.""" + parsed = float(value) + if not math.isfinite(parsed) or parsed <= 0.0: + message = "value must be finite and greater than zero" + raise argparse.ArgumentTypeError(message) + return parsed + + +def _parse_seed(value: str) -> int: + """Parse a seed accepted by both PyTorch CPU generators.""" + try: + seed = int(value, 10) + except ValueError as error: + message = "seed must be an integer" + raise argparse.ArgumentTypeError(message) from error + if seed < MIN_TORCH_SEED or seed > MAX_TORCH_SEED: + message = f"seed must be between {MIN_TORCH_SEED} and {MAX_TORCH_SEED}" + raise argparse.ArgumentTypeError(message) + return seed def _parse_args(argv: Sequence[str]) -> argparse.Namespace: - """Parse command-line arguments without loading TensorFlow.""" + """Parse command-line arguments without loading experiment dependencies.""" parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--batch-size", type=_positive_int, default=64, help="training and evaluation batch size (default: 64)") + parser.add_argument( + "--comet", + choices=("disabled", "offline", "online"), + default="disabled", + help="optional Comet mirror; local artifacts are always canonical (default: disabled)", + ) + parser.add_argument( + "--data-directory", + type=Path, + default=Path("out/experiments/data"), + help="persistent local MNIST input directory (default: out/experiments/data)", + ) + parser.add_argument("--epochs", type=_positive_int, default=5, help="training epochs (default: 5)") + parser.add_argument("--learning-rate", type=_positive_float, default=0.001, help="Adam learning rate (default: 0.001)") + parser.add_argument("--no-download", action="store_false", dest="download", help="require MNIST to exist in the local data directory") + parser.add_argument( + "--output-directory", + type=Path, + default=Path("out/experiments/mnist"), + help="canonical local run-artifact directory (default: out/experiments/mnist)", + ) + parser.add_argument("--seed", type=_parse_seed, default=0, help="PyTorch and data-loader seed (default: 0)") return parser.parse_args(argv) -def _run_experiment() -> None: - """Train and evaluate the historical TensorFlow model.""" - import tensorflow as tf # noqa: PLC0415 +def _config_from_args(args: argparse.Namespace) -> _RunConfig: + """Convert parsed arguments into the immutable run configuration.""" + data_directory = args.data_directory.resolve() + output_directory = args.output_directory.resolve() + dataset_directory = (data_directory / "MNIST").resolve() + if data_directory.is_relative_to(output_directory): + message = "MNIST data directory must not be inside the output directory." + raise ValueError(message) + if output_directory.is_relative_to(dataset_directory): + message = "MNIST output directory must not be inside the retained MNIST dataset directory." + raise ValueError(message) + return _RunConfig( + batch_size=args.batch_size, + comet_mode=args.comet, + data_directory=data_directory, + download=args.download, + epochs=args.epochs, + learning_rate=args.learning_rate, + output_directory=output_directory, + seed=args.seed, + ) + + +def _configuration_payload(config: _RunConfig, *, torch_version: str | None = None, torchvision_version: str | None = None) -> dict[str, object]: + """Return a JSON-safe configuration and runtime record.""" + payload = asdict(config) + payload["data_directory"] = str(config.data_directory) + payload["output_directory"] = str(config.output_directory) + payload["device"] = "cpu" + payload["package"] = PACKAGE_NAME + try: + payload["package_version"] = version(PACKAGE_NAME) + except PackageNotFoundError: + payload["package_version"] = "uninstalled" + payload["platform"] = platform.platform() + payload["python"] = platform.python_version() + payload["script_sha256"] = _sha256(Path(__file__)) + if torch_version is not None: + payload["torch"] = torch_version + if torchvision_version is not None: + payload["torchvision"] = torchvision_version + return payload + + +def _write_json(path: Path, payload: Mapping[str, object]) -> None: + """Write a deterministic local JSON artifact.""" + path.parent.mkdir(parents=True, exist_ok=True) + path.write_text(f"{json.dumps(payload, allow_nan=False, indent=2, sort_keys=True)}\n", encoding="utf-8") - tf.keras.utils.set_random_seed(0) - mnist = tf.keras.datasets.mnist - (x_train, y_train), (x_test, y_test) = mnist.load_data() - x_train, x_test = x_train / 255.0, x_test / 255.0 - model = tf.keras.models.Sequential( - [ - tf.keras.layers.Flatten(input_shape=(28, 28)), - tf.keras.layers.Dense(128, activation="relu"), - tf.keras.layers.Dropout(0.2), - tf.keras.layers.Dense(10), - ] +def _sha256(path: Path) -> str: + """Hash one local input file for the reproducibility record.""" + digest = hashlib.sha256() + with path.open("rb") as stream: + for chunk in iter(lambda: stream.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +def _artifact_record(path: Path, root: Path) -> dict[str, object]: + """Describe one canonical artifact by stable relative path and digest.""" + return { + "bytes": path.stat().st_size, + "path": path.relative_to(root).as_posix(), + "sha256": _sha256(path), + } + + +@contextmanager +def _staged_run_directory(output_directory: Path) -> Iterator[Path]: + """Publish one complete run without mixing it with an older generation.""" + if os.path.lexists(output_directory): + message = f"Output directory already exists: {output_directory}; choose a new --output-directory." + raise ValueError(message) + + output_directory.parent.mkdir(parents=True, exist_ok=True) + staging_directory = Path( + tempfile.mkdtemp( + dir=output_directory.parent, + prefix=f".{output_directory.name}.incomplete-", + ) + ) + try: + yield staging_directory + staging_directory.rename(output_directory) + except BaseException: + shutil.rmtree(staging_directory, ignore_errors=True) + raise + + +def _dataset_manifest(dataset_root: Path) -> list[dict[str, object]]: + """Describe every retained local MNIST input file.""" + return [ + { + "bytes": path.stat().st_size, + "path": path.relative_to(dataset_root).as_posix(), + "sha256": _sha256(path), + } + for path in sorted( + (path for path in dataset_root.rglob("*") if path.is_file()), + key=lambda path: path.relative_to(dataset_root).as_posix(), + ) + ] + + +def _start_comet(config: _RunConfig, artifact_directory: Path) -> _CometRun: + """Start Comet before importing PyTorch so automatic logging can attach.""" + import comet_ml # noqa: PLC0415 + + if config.comet_mode == "online": + api_key = os.environ.get("COMET_API_KEY") + if not api_key: + message = "COMET_API_KEY is required when --comet online is selected." + raise ValueError(message) + experiment_config = comet_ml.ExperimentConfig( + auto_histogram_gradient_logging=True, + auto_histogram_weight_logging=True, + log_env_details=False, + log_env_network=False, + log_git_metadata=False, + log_git_patch=False, + log_graph=True, + name="cdt-mnist", + ) + experiment = comet_ml.start(api_key=api_key, experiment_config=experiment_config, mode="create", project_name="cdt-plusplus") + else: + offline_directory = artifact_directory / "comet" + offline_directory.mkdir(parents=True, exist_ok=True) + experiment_config = comet_ml.ExperimentConfig( + auto_histogram_gradient_logging=True, + auto_histogram_weight_logging=True, + log_env_details=False, + log_env_network=False, + log_git_metadata=False, + log_git_patch=False, + log_graph=True, + name="cdt-mnist", + offline_directory=str(offline_directory), + ) + experiment = comet_ml.start( + experiment_config=experiment_config, + mode="create", + online=False, + project_name="cdt-plusplus", + ) + + from comet_ml.integration.pytorch import log_model, watch # noqa: PLC0415 + + return _CometRun( + experiment=cast("_Experiment", experiment), + log_model=cast("_LogModel", log_model), + watch=cast("_Watch", watch), ) - predictions = model(x_train[:1]).numpy() - tf.nn.softmax(predictions).numpy() - loss_function = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True) - loss_function(y_train[:1], predictions).numpy() - model.compile(optimizer="adam", loss=loss_function, metrics=["accuracy"]) - model.fit(x_train, y_train, epochs=5) - model.evaluate(x_test, y_test, verbose=2) - probability_model = tf.keras.Sequential([model, tf.keras.layers.Softmax()]) - probability_model(x_test[:5]) +def _build_model(torch_module: ModuleType) -> Module: + """Build the historical dense MNIST architecture with PyTorch.""" + return torch_module.nn.Sequential( + torch_module.nn.Flatten(), + torch_module.nn.Linear(28 * 28, 128), + torch_module.nn.ReLU(), + torch_module.nn.Dropout(0.2), + torch_module.nn.Linear(128, 10), + ) + + +def _train_epoch( + model: Module, + data_loader: DataLoader[tuple[Tensor, ...]], + loss_function: CrossEntropyLoss, + optimizer: Optimizer, +) -> float: + """Train one deterministic CPU epoch and return mean loss.""" + model.train() + total_loss = 0.0 + total_examples = 0 + for images, labels in data_loader: + optimizer.zero_grad() + logits = model(images) + loss = loss_function(logits, labels) + loss.backward() + optimizer.step() + examples = int(labels.size(0)) + total_examples += examples + total_loss += float(loss.item()) * examples + return total_loss / total_examples + + +def _evaluate( + torch_module: ModuleType, + model: Module, + data_loader: DataLoader[tuple[Tensor, ...]], + loss_function: CrossEntropyLoss, +) -> tuple[float, float]: + """Evaluate mean loss and accuracy on the deterministic CPU baseline.""" + model.eval() + total_loss = 0.0 + total_examples = 0 + correct = 0 + with torch_module.no_grad(): + for images, labels in data_loader: + logits = model(images) + loss = loss_function(logits, labels) + examples = int(labels.size(0)) + total_examples += examples + total_loss += float(loss.item()) * examples + correct += int((logits.argmax(dim=1) == labels).sum().item()) + return total_loss / total_examples, correct / total_examples + + +def _run_experiment(config: _RunConfig) -> None: # noqa: PLR0915 - Keep the staged experiment lifecycle together. + """Train PyTorch on MNIST and retain a complete local run record.""" + with _staged_run_directory(config.output_directory) as artifact_directory: + configuration_path = artifact_directory / "configuration.json" + + comet_run = _start_comet(config, artifact_directory) if config.comet_mode != "disabled" else None + try: + import torch # noqa: PLC0415 + from torchvision import datasets, transforms # noqa: PLC0415 + + torch.manual_seed(config.seed) + torch.use_deterministic_algorithms(mode=True) + generator = torch.Generator().manual_seed(config.seed) + transform = transforms.ToTensor() + try: + training_data = datasets.MNIST(root=config.data_directory, train=True, download=config.download, transform=transform) + test_data = datasets.MNIST(root=config.data_directory, train=False, download=config.download, transform=transform) + except RuntimeError as error: + message = f"MNIST data is unavailable or incomplete at {config.data_directory}: {error}" + raise ValueError(message) from error + training_loader = torch.utils.data.DataLoader( + training_data, + batch_size=config.batch_size, + generator=generator, + num_workers=0, + shuffle=True, + ) + test_loader = torch.utils.data.DataLoader(test_data, batch_size=config.batch_size, num_workers=0, shuffle=False) + + model = _build_model(torch) + loss_function = torch.nn.CrossEntropyLoss() + optimizer = torch.optim.Adam(model.parameters(), lr=config.learning_rate) + configuration = _configuration_payload(config, torch_version=torch.__version__, torchvision_version=version("torchvision")) + _write_json(configuration_path, configuration) + + if comet_run is not None: + comet_run.experiment.log_parameters(configuration) + comet_run.watch(model) + + training_metrics: list[dict[str, object]] = [] + for epoch in range(1, config.epochs + 1): + training_loss = _train_epoch(model, training_loader, loss_function, optimizer) + training_metrics.append({"epoch": epoch, "loss": training_loss}) + if comet_run is not None: + comet_run.experiment.log_metric("train_loss", training_loss, epoch=epoch) + print(f"Epoch {epoch}/{config.epochs}: loss={training_loss:.6f}") + + test_loss, test_accuracy = _evaluate(torch, model, test_loader, loss_function) + evaluation = {"accuracy": test_accuracy, "loss": test_loss} + if comet_run is not None: + comet_run.experiment.log_metric("test_loss", test_loss) + comet_run.experiment.log_metric("test_accuracy", test_accuracy) + + checkpoint = { + "configuration": configuration, + "evaluation": evaluation, + "model_state_dict": model.state_dict(), + "optimizer_state_dict": optimizer.state_dict(), + "training_metrics": training_metrics, + } + checkpoint_path = artifact_directory / "checkpoint.pt" + torch.save(checkpoint, checkpoint_path) + if comet_run is not None: + comet_run.log_model(comet_run.experiment, checkpoint, model_name="cdt-mnist") + + dataset_root = config.data_directory / "MNIST" + run_record = { + "artifacts": { + "checkpoint": _artifact_record(checkpoint_path, artifact_directory), + "configuration": _artifact_record(configuration_path, artifact_directory), + }, + "configuration": configuration, + "dataset_files": _dataset_manifest(dataset_root), + "evaluation": evaluation, + "training_metrics": training_metrics, + } + _write_json(artifact_directory / "run.json", run_record) + finally: + if comet_run is not None: + comet_run.experiment.end() + + print(f"Test loss={test_loss:.6f}, accuracy={test_accuracy:.4%}") + print(f"Canonical local artifacts: {config.output_directory}") def main(argv: Sequence[str] | None = None) -> int: """Run the MNIST experiment from an installed uv entry point.""" - _parse_args(sys.argv[1:] if argv is None else argv) try: - _run_experiment() + config = _config_from_args(_parse_args(sys.argv[1:] if argv is None else argv)) + _run_experiment(config) except ModuleNotFoundError as error: print( f"Missing experiment dependency {error.name!r}; run `just python-sync-experiments`, then retry with `uv run --no-sync cdt-mnist-experiment`.", file=sys.stderr, ) return 2 + except ValueError as error: + print(str(error), file=sys.stderr) + return 2 return 0 diff --git a/scripts/optimize_initialize.py b/scripts/optimize_initialize.py index e35581a6f..1c31afee9 100644 --- a/scripts/optimize_initialize.py +++ b/scripts/optimize_initialize.py @@ -1,22 +1,32 @@ """Run the CDT++ initializer parameter optimization experiment.""" -from __future__ import annotations - import argparse +import hashlib +import json import os import re +import shutil import sys +import tempfile +from contextlib import contextmanager +from dataclasses import dataclass +from importlib.metadata import PackageNotFoundError, version from pathlib import Path from subprocess import check_output as qx -from typing import TYPE_CHECKING, Protocol +from typing import TYPE_CHECKING, Literal, Protocol, cast if TYPE_CHECKING: - from collections.abc import Callable, Mapping, Sequence + from collections.abc import Callable, Iterator, Mapping, Sequence MAX_RANDOM_SEED = (1 << 64) - 1 +PACKAGE_NAME = "cdt-plusplus-scripts" PARAMETER_PAIRS = tuple((initial_radius, spacing) for initial_radius in range(1, 4) for spacing in (1.0, 1.5, 2.0)) +class OutputDirectoryExistsError(ValueError): + """The requested canonical output directory already exists.""" + + class _Experiment(Protocol): """Comet operations used by the historical parameter sweep.""" @@ -64,11 +74,36 @@ def grid(self, *, visible: bool) -> object: """Configure the plot grid.""" ... + def savefig(self, filename: Path) -> object: + """Save the canonical local volume-profile figure.""" + ... + def clf(self) -> object: """Clear the current figure.""" ... +@dataclass(frozen=True) +class _SweepServices: + """Injected hosted, process, and plotting boundaries for one sweep.""" + + experiment_factory: Callable[[Path], _Experiment | None] + initializer_runner: Callable[[list[str]], str] + plotter: _Plotter + + +@dataclass(frozen=True) +class _SweepConfig: + """Inputs needed to reproduce one initializer parameter sweep.""" + + api_key: str | None + comet_mode: Literal["disabled", "offline", "online"] + initialize_binary: Path + output_directory: Path + repository_root: Path + seed: int + + def _parse_seed(value: str) -> int: """Parse one unsigned 64-bit seed before creating online experiments.""" try: @@ -85,6 +120,18 @@ def _parse_seed(value: str) -> int: def _parse_args(argv: Sequence[str]) -> argparse.Namespace: """Parse command-line arguments without loading experiment dependencies.""" parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument( + "--comet", + choices=("disabled", "offline", "online"), + default="disabled", + help="optional Comet mirror; local artifacts are always canonical (default: disabled)", + ) + parser.add_argument( + "--output-directory", + type=Path, + default=Path("out/experiments/initialize"), + help="canonical local run-artifact directory (default: out/experiments/initialize)", + ) parser.add_argument( "--repository-root", type=Path, @@ -152,106 +199,291 @@ def _initializer_command( ] +def _sha256(path: Path) -> str: + """Hash one local experiment input or artifact.""" + digest = hashlib.sha256() + with path.open("rb") as stream: + for chunk in iter(lambda: stream.read(1024 * 1024), b""): + digest.update(chunk) + return digest.hexdigest() + + +def _artifact_record(path: Path, root: Path) -> dict[str, object]: + """Describe one canonical artifact by stable relative path and digest.""" + return { + "bytes": path.stat().st_size, + "path": path.relative_to(root).as_posix(), + "sha256": _sha256(path), + } + + +def _experiment_provenance(repository_root: Path, initialize_binary: Path) -> dict[str, object]: + """Identify the exact executable, source state, and Python script used.""" + resolved_root = repository_root.resolve() + resolved_binary = initialize_binary.resolve() + git = shutil.which("git") + if git is None: + message = "Git is required to record initializer source provenance." + raise RuntimeError(message) + commit = qx([git, "-C", str(resolved_root), "rev-parse", "HEAD"], text=True).strip() # noqa: S603 + status = qx( # noqa: S603 + [git, "-C", str(resolved_root), "status", "--porcelain=v1", "--untracked-files=all"], + text=True, + ) + tracked_diff = qx([git, "-C", str(resolved_root), "diff", "--binary", "HEAD"]) # noqa: S603 + try: + package_version = version(PACKAGE_NAME) + except PackageNotFoundError: + package_version = "uninstalled" + return { + "initializer": { + "bytes": resolved_binary.stat().st_size, + "path": resolved_binary.relative_to(resolved_root).as_posix(), + "sha256": _sha256(resolved_binary), + }, + "repository": { + "commit": commit, + "dirty": bool(status.strip()), + "tracked_diff_sha256": hashlib.sha256(tracked_diff).hexdigest(), + }, + "script": { + "package": PACKAGE_NAME, + "package_version": package_version, + "sha256": _sha256(Path(__file__)), + }, + } + + +@contextmanager +def _staged_run_directory(output_directory: Path) -> Iterator[Path]: + """Publish one complete sweep without mixing it with an older generation.""" + if os.path.lexists(output_directory): + message = f"Output directory already exists: {output_directory}; choose a new --output-directory." + raise OutputDirectoryExistsError(message) + + output_directory.parent.mkdir(parents=True, exist_ok=True) + staging_directory = Path( + tempfile.mkdtemp( + dir=output_directory.parent, + prefix=f".{output_directory.name}.incomplete-", + ) + ) + try: + yield staging_directory + staging_directory.rename(output_directory) + except BaseException: + shutil.rmtree(staging_directory, ignore_errors=True) + raise + + def _run_parameter_sweep( initialize_binary: Path, seed: int, - experiment_factory: Callable[[], _Experiment], - initializer_runner: Callable[[list[str]], str], - plotter: _Plotter, + output_directory: Path, + provenance: Mapping[str, object], + services: _SweepServices, ) -> None: """Run the parameter sweep through injected initializer and Comet boundaries.""" - for initial_radius, foliation_spacing in PARAMETER_PAIRS: - experiment = experiment_factory() - try: - hyper_params = {"simplices": 12000, "foliations": 12, "seed": seed} - experiment.log_parameters( - { + with _staged_run_directory(output_directory) as staged_output_directory: + for initial_radius, foliation_spacing in PARAMETER_PAIRS: + experiment = services.experiment_factory(staged_output_directory) + try: + hyper_params = {"simplices": 12000, "foliations": 12, "seed": seed} + parameters = { **hyper_params, "initial_radius": initial_radius, "foliation_spacing": foliation_spacing, } - ) - - command = _initializer_command( - initialize_binary, - hyper_params, - initial_radius=initial_radius, - foliation_spacing=foliation_spacing, - ) - print(command) - - output = initializer_runner(command) - final_simplices, graph = _parse_initializer_output(output) - - min_timeslice = min(timeslice for timeslice, _ in graph) - max_timeslice = max(timeslice for timeslice, _ in graph) - result = (final_simplices, min_timeslice, max_timeslice) - - print(result) - print(f"Initial radius is: {initial_radius}") - print(f"Foliation spacing is: {foliation_spacing}") - for timeslice, volume in graph: - print(f"Timeslice {timeslice} has {volume} spacelike faces.") - print() - - target_simplices = hyper_params["simplices"] - score = ((final_simplices - target_simplices) / target_simplices) * 100 - experiment.log_metric("Error %", score) - experiment.log_other("Min Timeslice", result[1]) - experiment.log_other("Max Timeslice", result[2]) - - timeslices = [timeslice for timeslice, _ in graph] - volumes = [volume for _, volume in graph] - plotter.plot(timeslices, volumes) - plotter.xlabel("Timeslice") - plotter.ylabel("Volume (spacelike faces)") - plotter.title("Volume Profile") - plotter.grid(visible=True) - experiment.log_figure(figure_name="Volume per Timeslice", figure=plotter) - plotter.clf() - finally: - experiment.end() - - -def _run_experiments(initialize_binary: Path, api_key: str, seed: int) -> None: - """Run the historical Comet parameter sweep.""" + if experiment is not None: + experiment.log_parameters(parameters) + + command = _initializer_command( + initialize_binary, + hyper_params, + initial_radius=initial_radius, + foliation_spacing=foliation_spacing, + ) + print(command) + run_directory = staged_output_directory / f"radius-{initial_radius}-spacing-{foliation_spacing:g}" + run_directory.mkdir(parents=True, exist_ok=True) + configuration_path = run_directory / "configuration.json" + _write_json( + configuration_path, + { + "command": command, + "parameters": parameters, + "provenance": provenance, + }, + ) + + output = services.initializer_runner(command) + stdout_path = run_directory / "stdout.txt" + stdout_path.write_text(output, encoding="utf-8") + final_simplices, graph = _parse_initializer_output(output) + + min_timeslice = min(timeslice for timeslice, _ in graph) + max_timeslice = max(timeslice for timeslice, _ in graph) + result = (final_simplices, min_timeslice, max_timeslice) + + print(result) + print(f"Initial radius is: {initial_radius}") + print(f"Foliation spacing is: {foliation_spacing}") + for timeslice, volume in graph: + print(f"Timeslice {timeslice} has {volume} spacelike faces.") + print() + + target_simplices = hyper_params["simplices"] + score = ((final_simplices - target_simplices) / target_simplices) * 100 + if experiment is not None: + experiment.log_metric("Error %", score) + experiment.log_other("Min Timeslice", result[1]) + experiment.log_other("Max Timeslice", result[2]) + + timeslices = [timeslice for timeslice, _ in graph] + volumes = [volume for _, volume in graph] + figure_path = run_directory / "volume-profile.png" + _write_volume_profile(timeslices, volumes, figure_path, services, experiment) + + _write_json( + run_directory / "run.json", + { + "artifacts": { + "configuration": _artifact_record(configuration_path, run_directory), + "figure": _artifact_record(figure_path, run_directory), + "stdout": _artifact_record(stdout_path, run_directory), + }, + "metrics": { + "error_percent": score, + "final_simplices": final_simplices, + "max_timeslice": max_timeslice, + "min_timeslice": min_timeslice, + }, + "parameters": parameters, + "provenance": provenance, + "volume_profile": [{"timeslice": timeslice, "volume": volume} for timeslice, volume in graph], + }, + ) + finally: + if experiment is not None: + experiment.end() + + +def _write_volume_profile( + timeslices: list[int], + volumes: list[int], + figure_path: Path, + services: _SweepServices, + experiment: _Experiment | None, +) -> None: + """Write and optionally mirror one parameter pair's volume profile.""" + try: + services.plotter.plot(timeslices, volumes) + services.plotter.xlabel("Timeslice") + services.plotter.ylabel("Volume (spacelike faces)") + services.plotter.title("Volume Profile") + services.plotter.grid(visible=True) + services.plotter.savefig(figure_path) + if experiment is not None: + experiment.log_figure(figure_name="Volume per Timeslice", figure=services.plotter) + finally: + services.plotter.clf() + + +def _write_json(path: Path, payload: Mapping[str, object]) -> None: + """Write one deterministic canonical local experiment artifact.""" + path.parent.mkdir(parents=True, exist_ok=True) + path.write_text(f"{json.dumps(payload, allow_nan=False, indent=2, sort_keys=True)}\n", encoding="utf-8") + + +def _run_experiments(config: _SweepConfig) -> None: + """Run the local-first parameter sweep with an optional Comet mirror.""" import matplotlib.pyplot as plt # noqa: PLC0415 - from comet_ml import Experiment # noqa: PLC0415 - def experiment_factory() -> _Experiment: - return Experiment(api_key=api_key, project_name="cdt-plusplus") + if config.comet_mode != "disabled": + import comet_ml # noqa: PLC0415 + + def experiment_factory(artifact_directory: Path) -> _Experiment | None: + if config.comet_mode == "disabled": + return None + if config.comet_mode == "online": + experiment_config = comet_ml.ExperimentConfig( + log_env_details=False, + log_env_network=False, + log_git_metadata=False, + log_git_patch=False, + name="cdt-optimize-initialize", + ) + return cast( + "_Experiment", + comet_ml.start(api_key=config.api_key, experiment_config=experiment_config, mode="create", project_name="cdt-plusplus"), + ) + offline_directory = artifact_directory / "comet" + offline_directory.mkdir(parents=True, exist_ok=True) + experiment_config = comet_ml.ExperimentConfig( + log_env_details=False, + log_env_network=False, + log_git_metadata=False, + log_git_patch=False, + name="cdt-optimize-initialize", + offline_directory=str(offline_directory), + ) + return cast( + "_Experiment", + comet_ml.start( + experiment_config=experiment_config, + mode="create", + online=False, + project_name="cdt-plusplus", + ), + ) def initializer_runner(command: list[str]) -> str: # The executable and numeric parameters are repository-controlled. return qx(command, text=True) # noqa: S603 - _run_parameter_sweep(initialize_binary, seed, experiment_factory, initializer_runner, plt) + services = _SweepServices(experiment_factory=experiment_factory, initializer_runner=initializer_runner, plotter=cast("_Plotter", plt)) + provenance = _experiment_provenance(config.repository_root, config.initialize_binary) + _run_parameter_sweep(config.initialize_binary, config.seed, config.output_directory, provenance, services) def main(argv: Sequence[str] | None = None) -> int: """Run the parameter sweep from an installed uv entry point.""" args = _parse_args(sys.argv[1:] if argv is None else argv) repository_root = args.repository_root.resolve() + output_directory = args.output_directory.resolve() initialize_binary = _initializer_binary(repository_root) if not initialize_binary.is_file(): print(f"CDT++ initializer not found at {initialize_binary}; run `just build` first.", file=sys.stderr) return 2 api_key = os.environ.get("COMET_API_KEY") - if not api_key: - print("COMET_API_KEY is required for an online Comet experiment.", file=sys.stderr) + if args.comet == "online" and not api_key: + print("COMET_API_KEY is required when --comet online is selected.", file=sys.stderr) return 2 try: - _run_experiments(initialize_binary, api_key, args.seed) + config = _SweepConfig( + api_key=api_key, + comet_mode=args.comet, + initialize_binary=initialize_binary, + output_directory=output_directory, + repository_root=repository_root, + seed=args.seed, + ) + _run_experiments(config) except ModuleNotFoundError as error: print( f"Missing experiment dependency {error.name!r}; run `just python-sync-experiments`, then retry with `uv run --no-sync cdt-optimize-initialize`.", file=sys.stderr, ) return 2 + except OutputDirectoryExistsError as error: + print(str(error), file=sys.stderr) + return 2 - print("All done with parameter optimization; results are available in Comet.") + print(f"All done with parameter optimization; canonical local artifacts: {output_directory}") + if args.comet != "disabled": + print("The run was also mirrored to Comet.") return 0 diff --git a/scripts/pkgx-build.sh b/scripts/pkgx-build.sh index b01d8af6c..3ebad62cf 100755 --- a/scripts/pkgx-build.sh +++ b/scripts/pkgx-build.sh @@ -8,12 +8,13 @@ repo_root="$(cd -- "${script_dir}/.." && pwd)" cmake_version="$(just --justfile "${repo_root}/Justfile" --evaluate cmake_version)" ninja_version="$(just --justfile "${repo_root}/Justfile" --evaluate ninja_version)" ccache_version="$(just --justfile "${repo_root}/Justfile" --evaluate ccache_version)" +python_version="$(just --justfile "${repo_root}/Justfile" --evaluate python_version)" pkgx_tools=( +git-scm.org@2.55.0 "+cmake.org@${cmake_version}" "+ninja-build.org@${ninja_version}" - +python.org@3.11.15 + "+python.org@${python_version}" +gnu.org/m4@1.4.21 +gnu.org/autoconf@2.73.0 +gnu.org/autoconf-archive@2024.10.16 diff --git a/scripts/release_check.py b/scripts/release_check.py index 7b6f1f8f6..4727d4351 100755 --- a/scripts/release_check.py +++ b/scripts/release_check.py @@ -1,8 +1,6 @@ #!/usr/bin/env python3 """Validate CDT++ release metadata and version synchronization.""" -from __future__ import annotations - import argparse import json import re diff --git a/scripts/semgrep_fixture_config.py b/scripts/semgrep_fixture_config.py index 0e79dce33..fba323ff7 100755 --- a/scripts/semgrep_fixture_config.py +++ b/scripts/semgrep_fixture_config.py @@ -50,7 +50,7 @@ def build_fixture_config(fixture_path: Path, source_config_path: Path) -> str: return "rules:\n" + "".join(rule_chunks[rule_id] for rule_id in annotation_ids) -def parse_args(argv: "Sequence[str]") -> argparse.Namespace: +def parse_args(argv: Sequence[str]) -> argparse.Namespace: """Parse command-line arguments.""" parser = argparse.ArgumentParser(description=__doc__) parser.add_argument("fixture", type=Path) @@ -59,7 +59,7 @@ def parse_args(argv: "Sequence[str]") -> argparse.Namespace: return parser.parse_args(argv) -def main(argv: "Sequence[str] | None" = None) -> int: +def main(argv: Sequence[str] | None = None) -> int: """Write the selected rules beside the mirrored fixture path.""" args = parse_args(sys.argv[1:] if argv is None else argv) try: diff --git a/scripts/subprocess_utils.py b/scripts/subprocess_utils.py index 40eeb1b5c..20798a116 100644 --- a/scripts/subprocess_utils.py +++ b/scripts/subprocess_utils.py @@ -1,7 +1,5 @@ """Secure subprocess helpers for repository support scripts.""" -from __future__ import annotations - import shutil import subprocess from typing import TYPE_CHECKING diff --git a/scripts/sync_vcpkg_tool_pins.py b/scripts/sync_vcpkg_tool_pins.py index f6312e1f4..a81a79b45 100644 --- a/scripts/sync_vcpkg_tool_pins.py +++ b/scripts/sync_vcpkg_tool_pins.py @@ -1,7 +1,5 @@ """Synchronize trusted vcpkg tool pins with the manifest's exact baseline.""" -from __future__ import annotations - import argparse import ast import hashlib diff --git a/scripts/tag_release.py b/scripts/tag_release.py index 233717a8f..56bc2288d 100644 --- a/scripts/tag_release.py +++ b/scripts/tag_release.py @@ -1,7 +1,5 @@ """Create a CDT++ annotated release tag from ``CHANGELOG.md``.""" -from __future__ import annotations - import argparse import re import subprocess diff --git a/scripts/tests/test_bootstrap_vcpkg.py b/scripts/tests/test_bootstrap_vcpkg.py index daf35591f..3e602dd20 100644 --- a/scripts/tests/test_bootstrap_vcpkg.py +++ b/scripts/tests/test_bootstrap_vcpkg.py @@ -1,7 +1,5 @@ """Tests for cross-platform vcpkg checkout validation.""" -from __future__ import annotations - import hashlib import shutil import subprocess diff --git a/scripts/tests/test_experiment_imports.py b/scripts/tests/test_experiment_imports.py index 07ab254f7..1cba064e5 100644 --- a/scripts/tests/test_experiment_imports.py +++ b/scripts/tests/test_experiment_imports.py @@ -1,7 +1,5 @@ """Import-safety tests for optional experiment scripts.""" -from __future__ import annotations - import builtins import importlib.util import unittest @@ -13,7 +11,7 @@ class ExperimentImportTests(unittest.TestCase): def test_experiment_scripts_import_without_running_experiments(self) -> None: """Importing either script needs no ML, plotting, Comet, or subprocess work.""" - optional_modules = {"comet_ml", "matplotlib", "numpy", "tensorflow"} + optional_modules = {"comet_ml", "matplotlib", "numpy", "torch", "torchvision"} real_import = builtins.__import__ def guarded_import( diff --git a/scripts/tests/test_generate_changelog.py b/scripts/tests/test_generate_changelog.py index c22355055..5d506aff4 100644 --- a/scripts/tests/test_generate_changelog.py +++ b/scripts/tests/test_generate_changelog.py @@ -1,7 +1,5 @@ """Tests for deterministic changelog generation.""" -from __future__ import annotations - import subprocess import tempfile import unittest diff --git a/scripts/tests/test_generate_reference_fixtures.py b/scripts/tests/test_generate_reference_fixtures.py index 8904ab0f3..65832f8ec 100644 --- a/scripts/tests/test_generate_reference_fixtures.py +++ b/scripts/tests/test_generate_reference_fixtures.py @@ -1,7 +1,5 @@ """Regression tests for complete reference-package regeneration.""" -from __future__ import annotations - import tempfile import unittest from pathlib import Path diff --git a/scripts/tests/test_justfile_discoverability.py b/scripts/tests/test_justfile_discoverability.py new file mode 100644 index 000000000..7a3552b37 --- /dev/null +++ b/scripts/tests/test_justfile_discoverability.py @@ -0,0 +1,171 @@ +"""Regression tests for the public Just recipe surface.""" + +import json +import re +import shutil +import subprocess +import unittest +from collections import defaultdict +from pathlib import Path +from typing import Any, cast + +REPO_ROOT = Path(__file__).resolve().parents[2] +WORKFLOW_VERSION_LOOKUP = re.compile(r"\bjust --evaluate ([a-z][a-z0-9_-]*)") +UV_INVOCATION = re.compile(r"(? subprocess.CompletedProcess[str]: + """Run the repository's installed Just executable without a shell.""" + executable = shutil.which("just") + if executable is None: + message = "Just is required to validate the repository command surface." + raise RuntimeError(message) + return subprocess.run( # noqa: S603 - executable is resolved; arguments are fixed by these tests. + [executable, *args], + cwd=REPO_ROOT, + check=True, + capture_output=True, + encoding="utf-8", + ) + + +def _just_document() -> dict[str, Any]: + """Return the parsed Justfile metadata from the pinned executable.""" + result = _run_just("--dump", "--dump-format", "json") + return cast("dict[str, Any]", json.loads(result.stdout)) + + +def _just_recipes() -> dict[str, dict[str, Any]]: + """Return recipe metadata keyed by recipe name.""" + return cast("dict[str, dict[str, Any]]", _just_document()["recipes"]) + + +def _dependency_names(recipe: dict[str, Any]) -> set[str]: + """Return the direct recipe dependencies recorded by Just.""" + return {dependency["recipe"] for dependency in recipe["dependencies"]} + + +def _body_fragments(value: object) -> list[str]: + """Return every literal string fragment from a parsed recipe body value.""" + if isinstance(value, str): + return [value] + if isinstance(value, list): + return [fragment for item in value for fragment in _body_fragments(item)] + return [] + + +def _recipe_invokes_uv(recipe: dict[str, Any]) -> bool: + """Return whether a parsed recipe body directly invokes uv or uvx.""" + return any(UV_INVOCATION.search("".join(_body_fragments(line))) for line in recipe["body"]) + + +def _recipe_reaches(recipes: dict[str, dict[str, Any]], recipe_name: str, target: str) -> bool: + """Return whether a recipe reaches a target through its dependency graph.""" + pending = list(_dependency_names(recipes[recipe_name])) + visited: set[str] = set() + while pending: + dependency = pending.pop() + if dependency == target: + return True + if dependency in visited: + continue + visited.add(dependency) + pending.extend(_dependency_names(recipes[dependency])) + return False + + +class JustfileDiscoverabilityTests(unittest.TestCase): + """Keep the maintainer-facing Just command layer coherent and discoverable.""" + + def test_bare_just_shows_the_grouped_recipe_reference(self) -> None: + """Invoking Just without a recipe must not start validation or a build.""" + result = _run_just() + + self.assertTrue(result.stdout.startswith("Available recipes:\n")) + self.assertIn("[workflows]", result.stdout) + self.assertIn("check", result.stdout) + self.assertNotIn("Checks complete.", result.stdout) + + def test_default_gates_include_core_checks_and_exclude_opt_in_experiments(self) -> None: + """Default validation stays comprehensive without installing heavyweight experiments.""" + recipes = _just_recipes() + check_dependencies = _dependency_names(recipes["check"]) + ci_dependencies = _dependency_names(recipes["ci"]) + + self.assertTrue( + { + "_justfile-check", + "python-check", + "reference-check", + "release-check", + "semgrep", + "semgrep-test", + "spell-check", + } + <= check_dependencies + ) + self.assertTrue({"check", "python-package-check", "reference-generated-check"} <= ci_dependencies) + self.assertNotIn("python-experiment-check", check_dependencies | ci_dependencies) + + def test_public_recipes_have_one_group_and_a_description(self) -> None: + """Every listed recipe should explain its purpose in one stable section.""" + for name, recipe in _just_recipes().items(): + if recipe["private"]: + continue + groups = [attribute["group"] for attribute in recipe["attributes"] if isinstance(attribute, dict) and "group" in attribute] + with self.subTest(recipe=name): + self.assertTrue(recipe["doc"], f"public recipe {name!r} has no description") + self.assertEqual(len(groups), 1, f"public recipe {name!r} has groups {groups!r}") + + def test_public_recipes_do_not_duplicate_exact_behavior(self) -> None: + """Public names should not expose byte-for-byte duplicate implementations.""" + signatures: defaultdict[str, list[str]] = defaultdict(list) + for name, recipe in _just_recipes().items(): + if recipe["private"]: + continue + signature = json.dumps( + { + "body": recipe["body"], + "dependencies": recipe["dependencies"], + "parameters": recipe["parameters"], + }, + sort_keys=True, + ) + signatures[signature].append(name) + + duplicates = [names for names in signatures.values() if len(names) > 1] + self.assertEqual(duplicates, []) + + def test_uv_backed_recipes_reuse_pinned_guards(self) -> None: + """Every uv consumer should reach the repository's exact-version guard.""" + recipes = _just_recipes() + for name in ("_sync-python-dev", "_sync-python-experiments", "_zizmor"): + with self.subTest(recipe=name): + self.assertIn("_ensure-uv", _dependency_names(recipes[name])) + + uv_consumers = {name for name, recipe in recipes.items() if name != "_ensure-uv" and _recipe_invokes_uv(recipe)} + self.assertTrue(uv_consumers) + for name in sorted(uv_consumers): + with self.subTest(recipe=name): + self.assertTrue( + _recipe_reaches(recipes, name, "_ensure-uv"), + f"uv-backed recipe {name!r} does not reach _ensure-uv", + ) + + def test_workflow_tool_lookups_resolve_from_just(self) -> None: + """GitHub Actions should resolve shared tool pins through Just assignments.""" + workflow_directory = REPO_ROOT / ".github" / "workflows" + workflow_paths = sorted((*workflow_directory.glob("*.yml"), *workflow_directory.glob("*.yaml"))) + workflow_text = "\n".join(path.read_text(encoding="utf-8") for path in workflow_paths) + assignment_names = set(_just_document()["assignments"]) + lookup_names = sorted(set(WORKFLOW_VERSION_LOOKUP.findall(workflow_text))) + + self.assertTrue(lookup_names) + for name in lookup_names: + with self.subTest(assignment=name): + self.assertIn(name, assignment_names) + self.assertTrue(_run_just("--evaluate", name).stdout.strip()) + + +if __name__ == "__main__": + unittest.main() diff --git a/scripts/tests/test_mnist_experiment.py b/scripts/tests/test_mnist_experiment.py new file mode 100644 index 000000000..0799f9cd1 --- /dev/null +++ b/scripts/tests/test_mnist_experiment.py @@ -0,0 +1,138 @@ +"""Dependency-free tests for the PyTorch MNIST command boundary.""" + +import argparse +import unittest +from contextlib import redirect_stderr +from io import StringIO +from pathlib import Path +from tempfile import TemporaryDirectory + +from scripts.mnist_experiment import ( + MAX_TORCH_SEED, + MIN_TORCH_SEED, + _config_from_args, + _parse_args, + _parse_seed, + _positive_float, + _positive_int, + _staged_run_directory, + main, +) + + +class MnistExperimentTests(unittest.TestCase): + """Verify configuration parsing before optional dependencies load.""" + + def test_defaults_preserve_the_cpu_portability_example(self) -> None: + """The retained MNIST command is deterministic, local-first, and opt-in.""" + config = _config_from_args(_parse_args([])) + self.assertEqual(config.seed, 0) + self.assertEqual(config.comet_mode, "disabled") + self.assertTrue(config.download) + self.assertEqual(config.data_directory, Path("out/experiments/data").resolve()) + self.assertEqual(config.output_directory, Path("out/experiments/mnist").resolve()) + + def test_no_download_requires_existing_local_inputs(self) -> None: + """A caller can prohibit network-backed dataset acquisition.""" + self.assertFalse(_config_from_args(_parse_args(["--no-download"])).download) + + def test_data_and_output_paths_must_not_overlap_retained_inputs(self) -> None: + """Invalid path containment fails before creating or importing anything.""" + with TemporaryDirectory() as temporary_directory: + root = Path(temporary_directory) + cases = ( + (root / "output" / "data", root / "output", "data directory must not be inside the output directory"), + (root / "data", root / "data" / "MNIST" / "runs" / "run", "output directory must not be inside the retained MNIST dataset directory"), + ) + for data_directory, output_directory, expected_message in cases: + with self.subTest(data_directory=data_directory, output_directory=output_directory): + stderr = StringIO() + with redirect_stderr(stderr): + status = main( + [ + "--data-directory", + str(data_directory), + "--output-directory", + str(output_directory), + ] + ) + + self.assertEqual(status, 2) + self.assertIn(expected_message, stderr.getvalue()) + self.assertEqual(list(root.iterdir()), []) + + def test_output_may_be_inside_data_directory_outside_retained_inputs(self) -> None: + """Run artifacts may share a parent with, but cannot enter, MNIST inputs.""" + with TemporaryDirectory() as temporary_directory: + data_directory = Path(temporary_directory) / "data" + output_directory = data_directory / "runs" / "run" + + config = _config_from_args( + _parse_args( + [ + "--data-directory", + str(data_directory), + "--output-directory", + str(output_directory), + ] + ) + ) + + self.assertEqual(config.data_directory, data_directory.resolve()) + self.assertEqual(config.output_directory, output_directory.resolve()) + + def test_training_counts_must_be_positive_and_finite(self) -> None: + """Invalid hyperparameters fail before Torch or Comet is imported.""" + with self.assertRaises(argparse.ArgumentTypeError): + _positive_int("0") + for value in ("0", "nan", "inf", "-inf"): + with self.subTest(value=value), self.assertRaises(argparse.ArgumentTypeError): + _positive_float(value) + + def test_seed_must_fit_the_pytorch_generator_range(self) -> None: + """Every accepted seed can be forwarded to both PyTorch generators.""" + self.assertEqual(_parse_seed(str(MIN_TORCH_SEED)), MIN_TORCH_SEED) + self.assertEqual(_parse_seed(str(MAX_TORCH_SEED)), MAX_TORCH_SEED) + for value in (str(MIN_TORCH_SEED - 1), str(MAX_TORCH_SEED + 1)): + with self.subTest(value=value), self.assertRaises(argparse.ArgumentTypeError): + _parse_seed(value) + + def test_completed_run_directory_is_published_once(self) -> None: + """A successful generation appears only after its contents are complete.""" + with TemporaryDirectory() as temporary_directory: + output_directory = Path(temporary_directory) / "run" + with _staged_run_directory(output_directory) as staging_directory: + (staging_directory / "run.json").write_text("complete\n", encoding="utf-8") + self.assertFalse(output_directory.exists()) + + self.assertEqual((output_directory / "run.json").read_text(encoding="utf-8"), "complete\n") + + def test_failed_run_does_not_publish_partial_artifacts(self) -> None: + """A failed generation leaves neither a final nor an incomplete run.""" + with TemporaryDirectory() as temporary_directory: + root = Path(temporary_directory) + output_directory = root / "run" + message = "training failed" + with self.assertRaisesRegex(RuntimeError, message), _staged_run_directory(output_directory) as staging_directory: + (staging_directory / "configuration.json").write_text("partial\n", encoding="utf-8") + raise RuntimeError(message) + + self.assertFalse(output_directory.exists()) + self.assertEqual(list(root.iterdir()), []) + + def test_existing_run_is_never_overwritten(self) -> None: + """A caller must choose a new output path for every generation.""" + with TemporaryDirectory() as temporary_directory: + output_directory = Path(temporary_directory) / "run" + output_directory.mkdir() + sentinel = output_directory / "run.json" + sentinel.write_text("previous\n", encoding="utf-8") + + with self.assertRaisesRegex(ValueError, "already exists"), _staged_run_directory(output_directory): + self.fail("existing output directory was opened for replacement") + + self.assertEqual(sentinel.read_text(encoding="utf-8"), "previous\n") + + +if __name__ == "__main__": + unittest.main() diff --git a/scripts/tests/test_optimize_initialize.py b/scripts/tests/test_optimize_initialize.py index b5e118c11..d6a0c9103 100644 --- a/scripts/tests/test_optimize_initialize.py +++ b/scripts/tests/test_optimize_initialize.py @@ -1,20 +1,23 @@ """Tests for the portable initializer optimization support script.""" -from __future__ import annotations - import argparse +import hashlib +import json import unittest from pathlib import Path +from tempfile import TemporaryDirectory from unittest.mock import Mock, patch from scripts.optimize_initialize import ( PARAMETER_PAIRS, + _experiment_provenance, _initializer_binary, _initializer_command, _parse_args, _parse_initializer_output, _parse_seed, _run_parameter_sweep, + _SweepServices, ) @@ -40,6 +43,10 @@ def test_initializer_seed_defaults_to_replay_value(self) -> None: """The sweep is reproducible without additional seed configuration.""" self.assertEqual(_parse_args([]).seed, 92) + def test_comet_is_an_optional_mirror(self) -> None: + """Local artifacts remain the default experiment destination.""" + self.assertEqual(_parse_args([]).comet, "disabled") + def test_initializer_seed_rejects_values_outside_uint64(self) -> None: """Invalid seeds fail before any online experiment is created.""" with self.assertRaises(argparse.ArgumentTypeError): @@ -97,15 +104,28 @@ def test_parameter_sweep_records_actual_geometry_and_ends_experiment(self) -> No Final number of simplices: 12000""" ) plotter = Mock() - - with patch("builtins.print"): - _run_parameter_sweep( - Path("initialize"), - 92, - experiment_factory, - initializer_runner, - plotter, - ) + plotter.savefig.side_effect = lambda path: path.write_bytes(b"figure") + provenance = {"initializer": {"sha256": "initializer-digest"}} + + with TemporaryDirectory() as temporary_directory, patch("builtins.print"): + output_directory = Path(temporary_directory) / "run" + services = _SweepServices(experiment_factory=experiment_factory, initializer_runner=initializer_runner, plotter=plotter) + _run_parameter_sweep(Path("initialize"), 92, output_directory, provenance, services) + + run_directory = output_directory / "radius-1-spacing-1" + configuration_path = run_directory / "configuration.json" + figure_path = run_directory / "volume-profile.png" + run_path = run_directory / "run.json" + stdout_path = run_directory / "stdout.txt" + self.assertEqual(stdout_path.read_text(encoding="utf-8"), initializer_runner.return_value) + run_record = json.loads(run_path.read_text(encoding="utf-8")) + self.assertEqual(run_record["provenance"], provenance) + for name, path in (("configuration", configuration_path), ("figure", figure_path), ("stdout", stdout_path)): + with self.subTest(artifact=name): + record = run_record["artifacts"][name] + self.assertEqual(record["path"], path.name) + self.assertEqual(record["bytes"], path.stat().st_size) + self.assertEqual(record["sha256"], hashlib.sha256(path.read_bytes()).hexdigest()) for experiment, (initial_radius, foliation_spacing) in zip(experiments, PARAMETER_PAIRS, strict=True): experiment.log_parameters.assert_called_once_with( @@ -117,20 +137,87 @@ def test_parameter_sweep_records_actual_geometry_and_ends_experiment(self) -> No "foliation_spacing": foliation_spacing, } ) + experiment.log_figure.assert_called_once_with(figure_name="Volume per Timeslice", figure=plotter) experiment.end.assert_called_once_with() initializer_runner.assert_any_call(["initialize", "-s", "-n", "12000", "-t", "12", "-i", "3", "-f", "2.0", "--seed", "92"]) + self.assertEqual(plotter.clf.call_count, len(PARAMETER_PAIRS)) def test_parameter_sweep_ends_experiment_when_initializer_fails(self) -> None: """A failed initializer cannot leave its Comet experiment open.""" experiment = Mock() initializer_runner = Mock(side_effect=RuntimeError("initializer failed")) - with patch("builtins.print"), self.assertRaisesRegex(RuntimeError, "initializer failed"): - _run_parameter_sweep(Path("initialize"), 92, Mock(return_value=experiment), initializer_runner, Mock()) + with TemporaryDirectory() as temporary_directory, patch("builtins.print"): + root = Path(temporary_directory) + output_directory = root / "run" + services = _SweepServices( + experiment_factory=Mock(return_value=experiment), + initializer_runner=initializer_runner, + plotter=Mock(), + ) + + with self.assertRaisesRegex(RuntimeError, "initializer failed"): + _run_parameter_sweep(Path("initialize"), 92, output_directory, {}, services) + + self.assertFalse(output_directory.exists()) + self.assertEqual(list(root.glob(".run.incomplete-*")), []) experiment.end.assert_called_once_with() + def test_parameter_sweep_preserves_an_existing_run(self) -> None: + """A replay must use a new output path instead of mixing generations.""" + with TemporaryDirectory() as temporary_directory: + output_directory = Path(temporary_directory) / "run" + output_directory.mkdir() + sentinel = output_directory / "run.json" + sentinel.write_text("previous\n", encoding="utf-8") + experiment_factory = Mock() + services = _SweepServices(experiment_factory=experiment_factory, initializer_runner=Mock(), plotter=Mock()) + + with self.assertRaisesRegex(ValueError, "already exists"): + _run_parameter_sweep(Path("initialize"), 92, output_directory, {}, services) + + self.assertEqual(sentinel.read_text(encoding="utf-8"), "previous\n") + experiment_factory.assert_not_called() + + def test_experiment_provenance_hashes_the_binary_and_records_source_state(self) -> None: + """The canonical record identifies the executable even after it is rebuilt.""" + with TemporaryDirectory() as temporary_directory: + repository_root = Path(temporary_directory) + initialize_binary = repository_root / "out" / "build" / "reference" / "src" / "initialize" + initialize_binary.parent.mkdir(parents=True) + initialize_binary.write_bytes(b"exact executable") + git_binary = repository_root / "git" + git_binary.write_bytes(b"git executable") + + with ( + patch("scripts.optimize_initialize.shutil.which", return_value=str(git_binary)), + patch("scripts.optimize_initialize.qx", side_effect=["abc123\n", " M README.md\n", b"tracked diff"]), + ): + provenance = _experiment_provenance(repository_root, initialize_binary) + + initializer = provenance["initializer"] + repository = provenance["repository"] + if not isinstance(initializer, dict) or not isinstance(repository, dict): + self.fail("provenance sections must be JSON objects") + self.assertEqual( + initializer, + { + "bytes": len(b"exact executable"), + "path": "out/build/reference/src/initialize", + "sha256": hashlib.sha256(b"exact executable").hexdigest(), + }, + ) + self.assertEqual( + repository, + { + "commit": "abc123", + "dirty": True, + "tracked_diff_sha256": hashlib.sha256(b"tracked diff").hexdigest(), + }, + ) + if __name__ == "__main__": unittest.main() diff --git a/scripts/tests/test_release_check.py b/scripts/tests/test_release_check.py index 74e792abb..93c4b2135 100644 --- a/scripts/tests/test_release_check.py +++ b/scripts/tests/test_release_check.py @@ -1,7 +1,5 @@ """Tests for release metadata validation.""" -from __future__ import annotations - import tempfile import unittest from pathlib import Path diff --git a/scripts/tests/test_sync_vcpkg_tool_pins.py b/scripts/tests/test_sync_vcpkg_tool_pins.py index f305d6d76..0b97819fd 100644 --- a/scripts/tests/test_sync_vcpkg_tool_pins.py +++ b/scripts/tests/test_sync_vcpkg_tool_pins.py @@ -1,7 +1,5 @@ """Tests for atomic vcpkg tool-pin synchronization.""" -from __future__ import annotations - import hashlib import tempfile import unittest diff --git a/scripts/tests/test_tag_release.py b/scripts/tests/test_tag_release.py index d2c60347f..9dfc2e473 100644 --- a/scripts/tests/test_tag_release.py +++ b/scripts/tests/test_tag_release.py @@ -1,7 +1,5 @@ """Tests for deterministic release-tag creation.""" -from __future__ import annotations - import shutil import subprocess import tempfile diff --git a/scripts/tests/test_validate_reference_fixtures.py b/scripts/tests/test_validate_reference_fixtures.py index 7b57e388b..13f902a99 100644 --- a/scripts/tests/test_validate_reference_fixtures.py +++ b/scripts/tests/test_validate_reference_fixtures.py @@ -1,7 +1,5 @@ """Regression tests for the cross-language reference-package validator.""" -from __future__ import annotations - import copy import tempfile import unittest diff --git a/scripts/validate_reference_fixtures.py b/scripts/validate_reference_fixtures.py index 9320dc065..d678e07da 100644 --- a/scripts/validate_reference_fixtures.py +++ b/scripts/validate_reference_fixtures.py @@ -1,7 +1,5 @@ """Validate the versioned CDT++ cross-language reference package.""" -from __future__ import annotations - import argparse import hashlib import itertools diff --git a/semgrep.yaml b/semgrep.yaml index 0460befd6..d0b8f5f4f 100644 --- a/semgrep.yaml +++ b/semgrep.yaml @@ -82,7 +82,7 @@ rules: - "/tests/semgrep/.github/**/*.yaml" - "/tests/semgrep/.github/**/*.yml" patterns: - - pattern-regex: '(?m)^\s*(?:-[ \t]+)?uses:\s*(?!\./)(?!docker://)(?!(?:actions/(?:cache|checkout|setup-python|upload-artifact)|astral-sh/setup-uv|codecov/codecov-action|DenverCoder1/doxygen-github-pages-action|github/codeql-action/(?:analyze|init)|ilammy/msvc-dev-cmd|JamesIves/github-pages-deploy-action|lukka/run-vcpkg|pkgxdev/setup|taiki-e/(?:cache-cargo-install-action|install-action))@)[A-Za-z0-9_.-]+/[A-Za-z0-9_.-]+(?:/[A-Za-z0-9_.-]+)*@' # yamllint disable-line rule:line-length + - pattern-regex: '(?m)^\s*(?:-[ \t]+)?uses:\s*(?!\./)(?!docker://)(?!(?:actions/(?:cache|checkout|setup-python|upload-artifact)|astral-sh/setup-uv|codecov/codecov-action|github/codeql-action/(?:analyze|init)|ilammy/msvc-dev-cmd|JamesIves/github-pages-deploy-action|lukka/run-vcpkg|pkgxdev/setup|taiki-e/install-action)@)[A-Za-z0-9_.-]+/[A-Za-z0-9_.-]+(?:/[A-Za-z0-9_.-]+)*@' # yamllint disable-line rule:line-length - id: cdt.github-actions.external-action-version-comment languages: - regex diff --git a/tests/Foliated_triangulation_test.cpp b/tests/Foliated_triangulation_test.cpp index e84963528..e7dbe3113 100644 --- a/tests/Foliated_triangulation_test.cpp +++ b/tests/Foliated_triangulation_test.cpp @@ -619,7 +619,7 @@ SCENARIO("Detecting and fixing problems with vertices and cells" * auto candidate = triangulation.delaunay_snapshot(); CHECK_FALSE(foliated_triangulations::fix_timevalues<3>(candidate)); } - AND_WHEN("Vertices in an owning snapshot are mis-labelled.") + AND_WHEN("Vertices in an owning snapshot are assigned invalid labels.") { auto candidate = triangulation.delaunay_snapshot(); auto break_vertices = [](Vertex_handle_t<3> const& vertex) { @@ -648,7 +648,7 @@ SCENARIO("Detecting and fixing problems with vertices and cells" * } } } - AND_WHEN("Cells in an owning snapshot are mis-labelled.") + AND_WHEN("Cells in an owning snapshot are assigned invalid labels.") { auto candidate = triangulation.delaunay_snapshot(); auto break_cells = [](Cell_handle_t<3> const& cell) { diff --git a/tests/Manifold_test.cpp b/tests/Manifold_test.cpp index 1eae2de17..5fab30ec4 100644 --- a/tests/Manifold_test.cpp +++ b/tests/Manifold_test.cpp @@ -236,7 +236,7 @@ SCENARIO("Manifold functions" * doctest::test_suite("manifold")) CHECK(manifold.is_correct()); } } - AND_WHEN("Vertices in an owning snapshot are mis-labelled.") + AND_WHEN("Vertices in an owning snapshot are assigned invalid labels.") { auto snapshot = manifold.delaunay_snapshot(); for (auto const& vertex : diff --git a/ty.toml b/ty.toml index 2f7105240..4016a28a7 100644 --- a/ty.toml +++ b/ty.toml @@ -2,7 +2,7 @@ include = ["src"] [environment] -python-version = "3.12" +python-version = "3.14" [analysis] # Experiment dependencies are lockfile-managed but omitted from the lightweight @@ -13,8 +13,10 @@ allowed-unresolved-imports = [ "matplotlib.**", "numpy", "numpy.**", - "tensorflow", - "tensorflow.**", + "torch", + "torch.**", + "torchvision", + "torchvision.**", ] [terminal] diff --git a/typos.toml b/typos.toml new file mode 100644 index 000000000..718876396 --- /dev/null +++ b/typos.toml @@ -0,0 +1,9 @@ +# Configuration for typos-cli (https://github.com/crate-ci/typos) + +[files] +# Encapsulated PostScript stores text as drawing commands rather than prose. +extend-exclude = ["docs/images/*.eps"] + +[default.extend-identifiers] +# Doxygen prose uses this conventional plural acronym. +PNGs = "PNGs" diff --git a/uv.lock b/uv.lock index 2776cf734..3dd3cc5c8 100644 --- a/uv.lock +++ b/uv.lock @@ -1,14 +1,9 @@ version = 1 revision = 3 -requires-python = "==3.12.*" - -[[package]] -name = "absl-py" -version = "2.5.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/d0/4f/d79676ab82f2e42fc3611618139f13a9c4c31d0cff4b486982047679a802/absl_py-2.5.0.tar.gz", hash = "sha256:0c996f25c0490700fadabe6351630f6111534fa0ae252cc6d2014ea3b141135f", size = 118119, upload-time = "2026-07-03T10:57:48.157Z" } -wheels = [ - { url = 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