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Merge branch 'main' into sdxl-support

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This commit is contained in:
blessedcoolant
2023-07-18 13:34:07 +12:00
parent ada9b06e48 c3a7e35ad8
commit 13da881953
100 changed files with 3322 additions and 10176 deletions
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15
invokeai/app/invocations/latent.py
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@ -83,7 +83,7 @@ def get_scheduler(
scheduler_name, SCHEDULER_MAP['ddim']
)
orig_scheduler_info = context.services.model_manager.get_model(
**scheduler_info.dict()
**scheduler_info.dict(), context=context,
)
with orig_scheduler_info as orig_scheduler:
scheduler_config = orig_scheduler.config
@ -269,6 +269,7 @@ class TextToLatentsInvocation(BaseInvocation):
model_name=control_info.control_model.model_name,
model_type=ModelType.ControlNet,
base_model=control_info.control_model.base_model,
context=context,
)
)
@ -320,14 +321,14 @@ class TextToLatentsInvocation(BaseInvocation):
def _lora_loader():
for lora in self.unet.loras:
lora_info = context.services.model_manager.get_model(
**lora.dict(exclude={"weight"})
**lora.dict(exclude={"weight"}), context=context,
)
yield (lora_info.context.model, lora.weight)
del lora_info
return
unet_info = context.services.model_manager.get_model(
**self.unet.unet.dict()
**self.unet.unet.dict(), context=context,
)
with ExitStack() as exit_stack,\
ModelPatcher.apply_lora_unet(unet_info.context.model, _lora_loader()),\
@ -410,14 +411,14 @@ class LatentsToLatentsInvocation(TextToLatentsInvocation):
def _lora_loader():
for lora in self.unet.loras:
lora_info = context.services.model_manager.get_model(
**lora.dict(exclude={"weight"})
**lora.dict(exclude={"weight"}), context=context,
)
yield (lora_info.context.model, lora.weight)
del lora_info
return
unet_info = context.services.model_manager.get_model(
**self.unet.unet.dict()
**self.unet.unet.dict(), context=context,
)
with ExitStack() as exit_stack,\
ModelPatcher.apply_lora_unet(unet_info.context.model, _lora_loader()),\
@ -498,7 +499,7 @@ class LatentsToImageInvocation(BaseInvocation):
latents = context.services.latents.get(self.latents.latents_name)
vae_info = context.services.model_manager.get_model(
**self.vae.vae.dict(),
**self.vae.vae.dict(), context=context,
)
with vae_info as vae:
@ -670,7 +671,7 @@ class ImageToLatentsInvocation(BaseInvocation):
#vae_info = context.services.model_manager.get_model(**self.vae.vae.dict())
vae_info = context.services.model_manager.get_model(
**self.vae.vae.dict(),
**self.vae.vae.dict(), context=context,
)
image_tensor = image_resized_to_grid_as_tensor(image.convert("RGB"))