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Fixed issue where sampling fails if doing a full finetune for some models

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Jaret Burkett
2025-05-17 19:37:55 +00:00
parent 6174ba474e
commit 4f896c0d8a
1 changed files with 2 additions and 1 deletions
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3
toolkit/models/base_model.py
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@@ -343,7 +343,7 @@ class BaseModel:
pipeline: Union[None, StableDiffusionPipeline, pipeline: Union[None, StableDiffusionPipeline,
StableDiffusionXLPipeline] = None, StableDiffusionXLPipeline] = None,
): ):
network = unwrap_model(self.network) network = self.network
merge_multiplier = 1.0 merge_multiplier = 1.0
flush() flush()
# if using assistant, unfuse it # if using assistant, unfuse it
@@ -364,6 +364,7 @@ class BaseModel:
self.assistant_lora.force_to(self.device_torch, self.torch_dtype) self.assistant_lora.force_to(self.device_torch, self.torch_dtype)
if network is not None: if network is not None:
network = unwrap_model(self.network)
network.eval() network.eval()
# check if we have the same network weight for all samples. If we do, we can merge in th # check if we have the same network weight for all samples. If we do, we can merge in th
# the network to drastically speed up inference # the network to drastically speed up inference