L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Productivité · SKILL.md

minibatch_ot_coupling

minibatch_ot_coupling

Compute deterministic squared-cost minibatch optimal transport pairings for OT conditional flow matching recovery runs.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: minibatch_ot_coupling description: Compute deterministic squared-cost minibatch optimal transport pairings for OT conditional flow matching recovery runs.

Minibatch OT Coupling

Use this skill when implementing OT-CFM or validating whether a recovery experiment pairs source and target samples according to a minibatch optimal transport plan. Do not use the exact enumerator for large minibatches.

Inputs

  • Equal-sized source and target minibatches of numeric vectors.
  • Optional comparison pairing, such as an independent or shuffled permutation.

Outputs

  • Minimum-cost permutation mapping each source index to a target index.
  • Squared Euclidean transport cost for the assignment.
  • Pair records that downstream CFM objective code can consume.

Workflow

  1. Build the squared Euclidean cost matrix.
  2. Solve a one-to-one minimum assignment. The bundled script enumerates permutations and is intended for small deterministic tests.
  3. Return paired source/target indices and costs.
  4. Compare against independent pairings when validating the OT-CFM mechanism.

Validation

Run python tests/test_minibatch_ot.py or the Distiller skill-tree validator with tests enabled.

Limitations

The bundled solver is factorial in batch size and should be replaced with a Hungarian, Sinkhorn, or POT implementation for real-scale training.

Skills enregistrées