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fid_activation_statistics

fid_activation_statistics

Compute FID-style activation mean/covariance summaries for generated or real feature matrices.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: fid_activation_statistics description: Compute FID-style activation mean/covariance summaries for generated or real feature matrices.

Fid Activation Statistics

Use this skill when a recovery or implementation needs the fid_statistics module from the TTUR/FID paper without rereading the original repository. Do not use it to claim full GAN reproduction unless real image features, dataset statistics, and training evidence are available.

Inputs

  • Numeric arrays or JSON files matching the module contract.
  • For recovery orchestration, a module-plan target and runtime handoff.

Outputs

  • Deterministic JSON-compatible statistics, distances, traces, or recovery checks.
  • Diagnostics sufficient to audit reduced/proxy recovery.

Workflow

  1. Validate input shapes and finite numeric values.
  2. Execute the module-specific deterministic script in scripts/.
  3. Preserve diagnostics and command evidence when used in recovery.
  4. Treat synthetic activations or toy dynamics as proxy evidence only.

Validation

Run python tests/test_fid_activation_statistics.py from this skill directory.

Limitations

This skill is self-contained and does not require the original TTUR repository. It does not download Inception models or train full GANs.

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