dequantization offload accounting (fixes Flux2 OOMs - incl TEs) (#11171)

* make setattr safe for non existent attributes

Handle the case where the attribute doesnt exist by returning a static
sentinel (distinct from None). If the sentinel is passed in as the set
value, del the attr.

* Account for dequantization and type-casts in offload costs

When measuring the cost of offload, identify weights that need a type
change or dequantization and add the size of the conversion result
to the offload cost.

This is mutually exclusive with lowvram patches which already has
a large conservative estimate and wont overlap the dequant cost so\
dont double count.

* Set the compute type on CLIP MPs

So that the loader can know the size of weights for dequant accounting.
This commit is contained in:
rattus
2025-12-09 14:21:31 +10:00
committed by GitHub
parent d50f342c90
commit e136b6dbb0
3 changed files with 22 additions and 8 deletions

View File

@@ -127,6 +127,8 @@ class CLIP:
self.tokenizer = tokenizer(embedding_directory=embedding_directory, tokenizer_data=tokenizer_data)
self.patcher = comfy.model_patcher.ModelPatcher(self.cond_stage_model, load_device=load_device, offload_device=offload_device)
#Match torch.float32 hardcode upcast in TE implemention
self.patcher.set_model_compute_dtype(torch.float32)
self.patcher.hook_mode = comfy.hooks.EnumHookMode.MinVram
self.patcher.is_clip = True
self.apply_hooks_to_conds = None