Fix MaskUnitAttention output transpose (0,2,3,1,4 → 0,3,2,1,4) to match PyTorch transpose(1,3) token ordering for windowed attention. Parity results (4 stages): Stage 0: max_abs 2.9e-4, mean 1.6e-5 Stage 1: max_abs 1.3e-4, mean 1.3e-5 Stage 2: max_abs 1.1e-2, mean 5.2e-5 (16 blocks, expected drift) Stage 3: max_abs 5.8e-4, mean 2.6e-5 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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| .. | ||
| __init__.py | ||
| test_conversion.py | ||
| test_decoder_parity.py | ||
| test_hiera_stage_parity.py | ||
| test_hiera_stage_shapes.py | ||
| test_import.py | ||
| test_reference_fixtures.py | ||
| test_refiner_parity.py | ||