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score_sde_recovery_harness

score_sde_recovery_harness

Execute a bounded soft-mode Score SDE recovery experiment using generated skills and mechanism checks.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: score_sde_recovery_harness description: Execute a bounded soft-mode Score SDE recovery experiment using generated skills and mechanism checks.

Score SDE Recovery Harness

Use this skill after module skills and runtime handoff exist. It assembles the generated SDE, loss, sampler, and probability-flow skills into an executable reduced experiment without reading the original repository.

Inputs

  • Attempt directory.
  • Generated skills root.
  • Runtime handoff path.
  • Module plan target.

Outputs

  • recovery/recovery_result.json.
  • recovery/logs/training_trace.json.
  • recovery/logs/generated_data_item.json.
  • recovery/logs/generated_skill_invocations.json.
  • recovery/source_manifest.json.

Workflow

  1. Read the module plan and runtime handoff.
  2. Construct a deterministic tiny synthetic batch.
  3. Import or call every generated core skill.
  4. Run one denoising score matching optimizer update.
  5. Run PC sampler and probability-flow diagnostics.
  6. Write all recovery artifacts and mechanism checks.
  7. Run the Distiller recovery experiment validator.

Validation

Run:

python tests/test_recovery_harness.py
python scripts/run_recovery.py --attempt-dir <attempt_dir> --skills-root <generated_skills_root>

Limitations

This is a declared soft-mode proxy. It must not be reported as full CIFAR-10 FID, Inception Score, or bits/dim reproduction.

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