mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2026-03-22 17:43:33 +08:00
Merge e5f6c1ff68 into 8b9d039f26
This commit is contained in:
commit
4ed7bedd37
@ -298,6 +298,16 @@ def weight_decompose(
|
|||||||
)
|
)
|
||||||
weight_norm = weight_norm + torch.finfo(weight.dtype).eps
|
weight_norm = weight_norm + torch.finfo(weight.dtype).eps
|
||||||
|
|
||||||
|
# Reshape dora_scale to match weight_norm dimensionality to avoid
|
||||||
|
# incorrect broadcasting. Without this, a 1D dora_scale [N] divided by
|
||||||
|
# a multi-dim weight_norm [N, 1] would broadcast to [N, N] instead of
|
||||||
|
# the intended element-wise [N, 1]. This caused shape mismatches for
|
||||||
|
# non-square weights (e.g. MLP layers where d_ff != d_model).
|
||||||
|
if wd_on_output_axis:
|
||||||
|
dora_scale = dora_scale.reshape(weight.shape[0], *[1] * (weight.dim() - 1))
|
||||||
|
else:
|
||||||
|
dora_scale = dora_scale.reshape(*[1] * (weight.dim() - 1), weight.shape[-1])
|
||||||
|
|
||||||
weight_calc *= (dora_scale / weight_norm).type(weight.dtype)
|
weight_calc *= (dora_scale / weight_norm).type(weight.dtype)
|
||||||
if strength != 1.0:
|
if strength != 1.0:
|
||||||
weight_calc -= weight
|
weight_calc -= weight
|
||||||
|
|||||||
Loading…
Reference in New Issue
Block a user