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Apply lora by patching lora instead of hooks

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This commit is contained in:
Sergey Borisov
2023-06-26 03:57:33 +03:00
parent 1ba94a92b3
commit 5cebf67ee4
4 changed files with 52 additions and 38 deletions
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17
invokeai/app/invocations/compel.py
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@ -65,23 +65,20 @@ class CompelInvocation(BaseInvocation):
**self.clip.text_encoder.dict(),
)
with tokenizer_info as orig_tokenizer,\
text_encoder_info as text_encoder,\
ExitStack() as stack:
text_encoder_info as text_encoder:
loras = [(stack.enter_context(context.services.model_manager.get_model(**lora.dict(exclude={"weight"}))), lora.weight) for lora in self.clip.loras]
loras = [(context.services.model_manager.get_model(**lora.dict(exclude={"weight"})).context.model, lora.weight) for lora in self.clip.loras]
ti_list = []
for trigger in re.findall(r"<[a-zA-Z0-9., _-]+>", self.prompt):
name = trigger[1:-1]
try:
ti_list.append(
stack.enter_context(
context.services.model_manager.get_model(
model_name=name,
base_model=self.clip.text_encoder.base_model,
model_type=ModelType.TextualInversion,
)
)
context.services.model_manager.get_model(
model_name=name,
base_model=self.clip.text_encoder.base_model,
model_type=ModelType.TextualInversion,
).context.model
)
except Exception:
#print(e)