wangbo/ComfyUI
1
0
Fork 0
mirror of https://github.com/comfyanonymous/ComfyUI.git synced 2026-06-12 01:07:30 +08:00
Code Issues Actions 18 Packages Projects Releases Wiki Activity

ops: tolerate already force casted dynamic weight (#14410)

Browse Source 
Some custom nodes .to weights completely out of load context which
can wreak havoc if its for a model that is not active. Detect this
condition and just let it fall-through to the non-dynamic loader
straight up.
This commit is contained in:
rattus 2026-06-11 13:32:57 +10:00 committed by GitHub
parent 33e6ebd0d9
commit bda19b2604
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 8 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

16
comfy/ops.py
View File

@ -299,21 +299,21 @@ def cast_bias_weight(s, input=None, dtype=None, device=None, bias_dtype=None, of
non_blocking = comfy.model_management.device_supports_non_blocking(device)
if hasattr(s, "_v"):
if hasattr(s, "_v") and comfy.model_management.is_device_cpu(device):
#vbar doesn't support CPU weights, but some custom nodes have weird paths
#that might switch the layer to the CPU and expect it to work. We have to take
#a clone conservatively as we are mmapped and some SFT files are packed misaligned
#If you are a custom node author reading this, please move your layer to the GPU
#or declare your ModelPatcher as CPU in the first place.
if comfy.model_management.is_device_cpu(device):
materialize_meta_param(s, ["weight", "bias"])
weight = s.weight.to(dtype=dtype, copy=True)
if isinstance(weight, QuantizedTensor):
weight = weight.dequantize()
bias = s.bias.to(dtype=bias_dtype, copy=True) if s.bias is not None else None
return format_return((weight, bias, (None, None, None)), offloadable)
materialize_meta_param(s, ["weight", "bias"])
weight = s.weight.to(dtype=dtype, copy=True)
if isinstance(weight, QuantizedTensor):
weight = weight.dequantize()
bias = s.bias.to(dtype=bias_dtype, copy=True) if s.bias is not None else None
return format_return((weight, bias, (None, None, None)), offloadable)
elif hasattr(s, "_v") and s.weight.device != device:
prefetched = hasattr(s, "_prefetch")
offload_stream = None
offload_device = None