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retune lowVramPatch VRAM accounting #11173

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Merged
comfyanonymous merged 1 commit into from
Dec 8, 2025
Merged

retune lowVramPatch VRAM accounting #11173

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6 changes: 3 additions & 3 deletions comfy/model_patcher.py
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Original file line number Diff line number Diff line change
Expand Up @@ -132,14 +132,14 @@ def __init__(self, key, patches, convert_func=None, set_func=None):
def __call__(self, weight):
return comfy.lora.calculate_weight(self.patches[self.key], weight, self.key, intermediate_dtype=weight.dtype)

#The above patch logic may cast up the weight to fp32, and do math. Go with fp32 x 3
LOWVRAM_PATCH_ESTIMATE_MATH_FACTOR = 3
LOWVRAM_PATCH_ESTIMATE_MATH_FACTOR = 2

def low_vram_patch_estimate_vram(model, key):
weight, set_func, convert_func = get_key_weight(model, key)
if weight is None:
return 0
return weight.numel() * torch.float32.itemsize * LOWVRAM_PATCH_ESTIMATE_MATH_FACTOR
model_dtype = getattr(model, "manual_cast_dtype", torch.float32)
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@mcmonkey4eva mcmonkey4eva Dec 8, 2025

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manual_cast_dtype can be None, this code needs to either exclude that case or have an or torch.float32 on the end (getattr default only fires if the attr doesn't exist, not if it's None, so this PR is erroring for users)

return weight.numel() * model_dtype.itemsize * LOWVRAM_PATCH_ESTIMATE_MATH_FACTOR

def get_key_weight(model, key):
set_func = None
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