wangbo/ComfyUI
1
0
Fork 0
mirror of https://github.com/comfyanonymous/ComfyUI.git synced 2026-02-10 05:22:34 +08:00
Code Issues Actions 14 Packages Projects Releases Wiki Activity

Merge 8c374c8b90 into 0c18842acb

Browse Source
This commit is contained in:
Dustin 2025-11-25 15:26:07 -05:00 committed by GitHub
commit 7bdd0105c2
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 22 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

25
comfy/model_patcher.py
View File

@ -130,9 +130,22 @@ class LowVramPatch:
self.set_func = set_func
def __call__(self, weight):
# Detect SageAttention and skip conversion for compatibility
sage_attention_active = False
try:
import comfy.cli_args
sage_attention_active = hasattr(comfy.cli_args.args, 'use_sage_attention') and \
comfy.cli_args.args.use_sage_attention
except:
pass
intermediate_dtype = weight.dtype
if self.convert_func is not None:
# Skip convert_func when SageAttention is active (compatibility mode)
if self.convert_func is not None and not sage_attention_active:
weight = self.convert_func(weight.to(dtype=torch.float32, copy=True), inplace=True)
elif sage_attention_active and self.convert_func is not None:
logging.debug(f"Skipping convert_func for {self.key} (SageAttention compatibility)")
if intermediate_dtype not in [torch.float32, torch.float16, torch.bfloat16]: #intermediate_dtype has to be one that is supported in math ops
intermediate_dtype = torch.float32
@ -140,10 +153,16 @@ class LowVramPatch:
if self.set_func is None:
return comfy.float.stochastic_rounding(out, weight.dtype, seed=string_to_seed(self.key))
else:
return self.set_func(out, seed=string_to_seed(self.key), return_weight=True)
# Skip set_func when SageAttention is active (compatibility mode)
if not sage_attention_active:
return self.set_func(out, seed=string_to_seed(self.key), return_weight=True)
else:
return comfy.float.stochastic_rounding(out, weight.dtype, seed=string_to_seed(self.key))
out = comfy.lora.calculate_weight(self.patches[self.key], weight, self.key, intermediate_dtype=intermediate_dtype)
if self.set_func is not None:
# Skip set_func when SageAttention is active (compatibility mode)
if self.set_func is not None and not sage_attention_active:
return self.set_func(out, seed=string_to_seed(self.key), return_weight=True).to(dtype=intermediate_dtype)
else:
return out