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load non comfy weights

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Rattus
2026-02-09 12:40:59 +10:00
parent 6198f7562e
commit 959b3014bb
3 changed files with 13 additions and 9 deletions
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10
comfy/model_management.py
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@@ -1206,8 +1206,6 @@ def cast_to(weight, dtype=None, device=None, non_blocking=False, copy=False, str
if dtype is None:
dtype = weight._model_dtype
r = torch.empty_like(weight, dtype=dtype, device=device)
signature = comfy_aimdo.model_vbar.vbar_fault(weight._v)
if signature is not None:
raw_tensor = comfy_aimdo.torch.aimdo_to_tensor(weight._v, device)
@@ -1216,11 +1214,9 @@ def cast_to(weight, dtype=None, device=None, non_blocking=False, copy=False, str
weight._v_signature = signature
#Send it over
v_tensor.copy_(weight, non_blocking=non_blocking)
#always take a deep copy even if _v is good, as we have no reasonable point to unpin
#a non comfy weight
r.copy_(v_tensor)
comfy_aimdo.model_vbar.vbar_unpin(weight._v)
return r
return v_tensor.to(dtype=dtype)
r = torch.empty_like(weight, dtype=dtype, device=device)
if weight.dtype != r.dtype and weight.dtype != weight._model_dtype:
#Offloaded casting could skip this, however it would make the quantizations