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name: dlr_margin_loss description: Compute DLR-style logit margin losses for APGD-DLR adversarial optimization checks.

DLR Margin Loss

Use this skill when an adversarial attack needs the AutoAttack DLR loss or when validating that a proxy attack preserves APGD-DLR semantics. Do not use it for binary classifiers or tasks without ordered class logits.

Inputs

• A logit vector with at least three classes.
• The true class index.

Outputs

• Scalar untargeted DLR loss.
• Ranking diagnostics from the helper script.

Workflow

1. Sort logits while retaining the true-class position.
2. Identify the strongest non-true competitor.
3. Normalize the true-versus-competitor margin by the spread between top and third logits.
4. Maximize this loss during untargeted APGD.

Validation

Run python tests/test_dlr.py or the generated skill validator.

Limitations

This pure-Python helper is intended for deterministic small examples and mirrors the untargeted loss needed by the recovery harness.