v0.13.0

Ops-and-trust release on the 0.12 stack: default safetensors checkpoints,
fit callbacks and tracking adapters, a config-driven CLI, thin Ray Tune
helpers, homogeneous representation-level explainability, and a broader CI
matrix. Homogeneous scientific defaults and the linear latent operator
contract are unchanged.

Added

• Default checkpoint container safetensors_v1 (directory or .kgckpt /
  .zip bundle) with meta.json / config.json /
  model.safetensors. Core dependency safetensors>=0.4. Load
  auto-detects the safe layout and legacy format-1 .pt pickles. See
  SECURITY.md and Sphinx serialization docs.
• Optional .kgckpt zip packaging of the safetensors directory layout.
• Fit callback protocol (FitCallback / NoOpFitCallback) wired through
  run_fit_loop and GraphKoopmanModel.fit(..., callbacks=). In-tree
  CsvFitLogger and optional TensorBoardFitLogger; W&B / MLflow remain
  examples-only DIY (no cloud SDK pins).
• Console script koopman-graph with train / predict subcommands,
  JSON configs in core and optional YAML via [cli] (PyYAML). Sphinx
  cli page and examples/cli/ smoke config.
• Power-user koopman_graph.tuning: fit_history_metrics, lazy
  run_ray_tune, and example search-space scaffolds. Ray Tune example
  script migrated; Optuna stays examples-only.
• Homogeneous explain_representation /
  RepresentationExplanation (GNNExplainer by default; optional Captum
  integrated gradients via [explain]). Interpretive / non-causal masks;
  not ResDMD and not ModeEnergyAttribution. Tutorial
  examples/46_representation_explain.ipynb. Bib keys
  Ying2019GNNExplainer, Sundararajan2017IntegratedGradients.
• CI: Ubuntu pytest on Python 3.10, 3.11, and 3.12 (coverage on 3.12);
  macOS core smoke on 3.12 with
  -m "not slow and not distributed and not ray" (hard-fail). Notebook
  push shards extended through 46_*.

Changed

• Behavior change: Model.save / the default checkpoint path write
  safetensors_v1 instead of a pickle-only format-1 .pt. Pass
  format="legacy_pt" only when you intentionally need the legacy pickle
  layout. Prefer loading trusted legacy_pt files only (see
  SECURITY.md).

Notes

• Portable inference export (TorchScript / torch.export / ONNX) is
  not shipped in 0.13.0 (Phase 83 cut-candidate). Training checkpoints
  (safetensors_v1) remain the supported weight-sharing path; ONNX stays
  deferred.
• Windows is best-effort community support and is not in the CI matrix.
• Representation explain remains a homogeneous MVP (rejects hetero /
  RelGraph / hypergraph / adaptive topology / delays / controls).
• Homogeneous training defaults are unchanged relative to 0.12.0.

Full changelog: see CHANGELOG.md ([0.13.0] - 2026-08-12).