---

name: reduced_training_harness description: Execute a bounded finite-difference optimizer step for DCL proxy recovery and emit validator-compatible training traces.

Reduced DCL Training Harness

Use this skill only when full GAN training is blocked and soft-mode reduced recovery is allowed. It runs a tiny optimizer step over target feature parameters using the generated DCL loss implementation. Do not mark this as full model training.

Inputs

• Latent-paired feature batch.
• DCL loss function.
• Learning rate and finite-difference epsilon.

Outputs

• loss_before, loss_after, params_before, and params_after.
• Optimizer-state change evidence.
• Reduced-mode mechanism checks.

Workflow

1. Flatten target generated features as trainable parameters.
2. Estimate finite-difference gradients of DCL proxy loss.
3. Apply one gradient descent step.
4. Write a trace proving parameters changed and loss decreased.

Validation

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

Limitations

This skill is a proxy for objective mechanics, not a StyleGAN or discriminator implementation.