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least_squares_mask_tuning

least_squares_mask_tuning

Tune surviving pruning mask coefficients with damped least squares for activation reconstruction.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentación de la Skill

GitHub

name: least_squares_mask_tuning description: Tune surviving pruning mask coefficients with damped least squares for activation reconstruction.

Least Squares Mask Tuning

Use this skill for the paper's final post-training pruning stage, after a binary structured mask has been selected and rearranged. It tunes only surviving mask entries to reconstruct original layer activations. Do not use it as model-weight retraining, and never revive pruned entries.

Inputs

  • Matrix A of per-unit activation contributions.
  • Target vector b for reconstruction.
  • Binary keep mask.
  • Damping and acceptable coefficient range.

Outputs

A real-valued mask, baseline/tuned reconstruction errors, and an accepted flag. Pruned entries remain zero.

Workflow

Restrict A to kept columns, solve damped normal equations, insert the coefficients into the full mask, and reject coefficients outside the range. Report whether reconstruction error improved.

Validation

Run the included deterministic synthetic tests.

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