In weight_decompose(), the 1D dora_scale tensor [N] divided by the
multi-dimensional weight_norm [N, 1, ...] would incorrectly broadcast
to [N, N, ...] (outer-product shape) instead of element-wise [N, 1, ...].
This caused shape mismatches when applying DoRA to non-square weight
matrices (e.g. MLP layers where d_ff != d_model), while silently
producing correct results for square weights (most attention Q/K/V/O).
Fix: explicitly reshape dora_scale to match weight_norm's dimensionality
before the division.
Fixes#12938
Co-Authored-By: Claude (claude-opus-4-6) <noreply@anthropic.com>
e5f6c1ff68