384e87fca1
Unlocks all four Pixal3D flow checkpoints (~20GB) at once - they are pure transformers with no sparse conv. LATO.2 has flow models too (vertex_structured_flow, topo_flow), so these belong in the shared core rather than either port. Three details taken from upstream rather than assumed, each silent when wrong: - norm1/norm3 are NON-affine but norm2 IS affine in the modulated cross block. There is an explicit test asserting that asymmetry. - MultiHeadRMSNorm is written upstream as F.normalize(x)*gamma*sqrt(dim). F.normalize is L2, and the sqrt(d) turns it into RMS - implemented directly as RMS and verified equal to the upstream formulation to 9.5e-7. - RoPE phases are NOT derived: Pixal3D ships rope_phases as a stored tensor, so they are passed in. Tested that the rotation preserves per-pair norms and is not a no-op. Also tested: gates at zero make the block an identity on its residual branches. |
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| .. | ||
| __init__.py | ||
| conv.py | ||
| convert.py | ||
| dit.py | ||
| ops.py | ||
| tensor.py | ||