mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
Remove references to model_records service, change submodel property on ModelInfo to submodel_type to support new params in model manager
This commit is contained in:
parent
3e82f63c7e
commit
86ac55ab5f
@ -1627,7 +1627,7 @@ payload=dict(
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queue_batch_id=queue_batch_id,
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queue_batch_id=queue_batch_id,
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graph_execution_state_id=graph_execution_state_id,
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graph_execution_state_id=graph_execution_state_id,
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model_key=model_key,
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model_key=model_key,
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submodel=submodel,
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submodel_type=submodel,
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hash=model_info.hash,
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hash=model_info.hash,
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location=str(model_info.location),
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location=str(model_info.location),
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precision=str(model_info.precision),
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precision=str(model_info.precision),
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@ -812,7 +812,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
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)
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)
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with set_seamless(vae_info.model, self.vae.seamless_axes), vae_info as vae:
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with set_seamless(vae_info.model, self.vae.seamless_axes), vae_info as vae:
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assert isinstance(vae, torch.Tensor)
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assert isinstance(vae, torch.nn.Module)
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latents = latents.to(vae.device)
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latents = latents.to(vae.device)
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if self.fp32:
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if self.fp32:
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vae.to(dtype=torch.float32)
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vae.to(dtype=torch.float32)
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@ -18,7 +18,7 @@ from .baseinvocation import (
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class ModelInfo(BaseModel):
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class ModelInfo(BaseModel):
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key: str = Field(description="Key of model as returned by ModelRecordServiceBase.get_model()")
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key: str = Field(description="Key of model as returned by ModelRecordServiceBase.get_model()")
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submodel: Optional[SubModelType] = Field(default=None, description="Info to load submodel")
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submodel_type: Optional[SubModelType] = Field(default=None, description="Info to load submodel")
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class LoraInfo(ModelInfo):
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class LoraInfo(ModelInfo):
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@ -110,22 +110,22 @@ class MainModelLoaderInvocation(BaseInvocation):
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unet=UNetField(
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unet=UNetField(
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unet=ModelInfo(
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unet=ModelInfo(
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key=key,
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key=key,
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submodel=SubModelType.UNet,
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submodel_type=SubModelType.UNet,
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),
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),
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scheduler=ModelInfo(
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scheduler=ModelInfo(
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key=key,
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key=key,
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submodel=SubModelType.Scheduler,
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submodel_type=SubModelType.Scheduler,
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),
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),
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loras=[],
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loras=[],
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),
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),
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clip=ClipField(
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clip=ClipField(
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tokenizer=ModelInfo(
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tokenizer=ModelInfo(
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key=key,
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key=key,
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submodel=SubModelType.Tokenizer,
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submodel_type=SubModelType.Tokenizer,
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),
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),
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text_encoder=ModelInfo(
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text_encoder=ModelInfo(
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key=key,
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key=key,
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submodel=SubModelType.TextEncoder,
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submodel_type=SubModelType.TextEncoder,
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),
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),
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loras=[],
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loras=[],
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skipped_layers=0,
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skipped_layers=0,
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@ -133,7 +133,7 @@ class MainModelLoaderInvocation(BaseInvocation):
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vae=VaeField(
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vae=VaeField(
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vae=ModelInfo(
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vae=ModelInfo(
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key=key,
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key=key,
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submodel=SubModelType.Vae,
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submodel_type=SubModelType.Vae,
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),
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),
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),
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),
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)
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)
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@ -188,7 +188,7 @@ class LoraLoaderInvocation(BaseInvocation):
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output.unet.loras.append(
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output.unet.loras.append(
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LoraInfo(
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LoraInfo(
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key=lora_key,
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key=lora_key,
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submodel=None,
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submodel_type=None,
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weight=self.weight,
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weight=self.weight,
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)
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)
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)
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)
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@ -198,7 +198,7 @@ class LoraLoaderInvocation(BaseInvocation):
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output.clip.loras.append(
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output.clip.loras.append(
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LoraInfo(
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LoraInfo(
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key=lora_key,
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key=lora_key,
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submodel=None,
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submodel_type=None,
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weight=self.weight,
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weight=self.weight,
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)
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)
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)
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)
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@ -271,7 +271,7 @@ class SDXLLoraLoaderInvocation(BaseInvocation):
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output.unet.loras.append(
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output.unet.loras.append(
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LoraInfo(
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LoraInfo(
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key=lora_key,
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key=lora_key,
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submodel=None,
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submodel_type=None,
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weight=self.weight,
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weight=self.weight,
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)
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)
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)
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)
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@ -281,7 +281,7 @@ class SDXLLoraLoaderInvocation(BaseInvocation):
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output.clip.loras.append(
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output.clip.loras.append(
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LoraInfo(
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LoraInfo(
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key=lora_key,
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key=lora_key,
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submodel=None,
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submodel_type=None,
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weight=self.weight,
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weight=self.weight,
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)
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)
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)
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)
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@ -291,7 +291,7 @@ class SDXLLoraLoaderInvocation(BaseInvocation):
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output.clip2.loras.append(
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output.clip2.loras.append(
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LoraInfo(
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LoraInfo(
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key=lora_key,
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key=lora_key,
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submodel=None,
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submodel_type=None,
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weight=self.weight,
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weight=self.weight,
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)
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)
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)
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)
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@ -43,29 +43,29 @@ class SDXLModelLoaderInvocation(BaseInvocation):
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model_key = self.model.key
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model_key = self.model.key
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# TODO: not found exceptions
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# TODO: not found exceptions
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if not context.services.model_records.exists(model_key):
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if not context.services.model_manager.store.exists(model_key):
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raise Exception(f"Unknown model: {model_key}")
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raise Exception(f"Unknown model: {model_key}")
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return SDXLModelLoaderOutput(
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return SDXLModelLoaderOutput(
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unet=UNetField(
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unet=UNetField(
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unet=ModelInfo(
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unet=ModelInfo(
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key=model_key,
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key=model_key,
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submodel=SubModelType.UNet,
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submodel_type=SubModelType.UNet,
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),
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),
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scheduler=ModelInfo(
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scheduler=ModelInfo(
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key=model_key,
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key=model_key,
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submodel=SubModelType.Scheduler,
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submodel_type=SubModelType.Scheduler,
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),
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),
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loras=[],
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loras=[],
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),
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),
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clip=ClipField(
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clip=ClipField(
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tokenizer=ModelInfo(
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tokenizer=ModelInfo(
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key=model_key,
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key=model_key,
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submodel=SubModelType.Tokenizer,
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submodel_type=SubModelType.Tokenizer,
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),
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),
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text_encoder=ModelInfo(
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text_encoder=ModelInfo(
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key=model_key,
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key=model_key,
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submodel=SubModelType.TextEncoder,
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submodel_type=SubModelType.TextEncoder,
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),
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),
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loras=[],
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loras=[],
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skipped_layers=0,
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skipped_layers=0,
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@ -73,11 +73,11 @@ class SDXLModelLoaderInvocation(BaseInvocation):
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clip2=ClipField(
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clip2=ClipField(
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tokenizer=ModelInfo(
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tokenizer=ModelInfo(
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key=model_key,
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key=model_key,
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submodel=SubModelType.Tokenizer2,
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submodel_type=SubModelType.Tokenizer2,
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),
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),
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text_encoder=ModelInfo(
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text_encoder=ModelInfo(
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key=model_key,
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key=model_key,
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submodel=SubModelType.TextEncoder2,
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submodel_type=SubModelType.TextEncoder2,
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),
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),
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loras=[],
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loras=[],
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skipped_layers=0,
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skipped_layers=0,
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@ -85,7 +85,7 @@ class SDXLModelLoaderInvocation(BaseInvocation):
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vae=VaeField(
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vae=VaeField(
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vae=ModelInfo(
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vae=ModelInfo(
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key=model_key,
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key=model_key,
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submodel=SubModelType.Vae,
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submodel_type=SubModelType.Vae,
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),
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),
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),
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),
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)
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)
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@ -112,29 +112,29 @@ class SDXLRefinerModelLoaderInvocation(BaseInvocation):
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model_key = self.model.key
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model_key = self.model.key
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# TODO: not found exceptions
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# TODO: not found exceptions
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if not context.services.model_records.exists(model_key):
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if not context.services.model_manager.store.exists(model_key):
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raise Exception(f"Unknown model: {model_key}")
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raise Exception(f"Unknown model: {model_key}")
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return SDXLRefinerModelLoaderOutput(
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return SDXLRefinerModelLoaderOutput(
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unet=UNetField(
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unet=UNetField(
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unet=ModelInfo(
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unet=ModelInfo(
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key=model_key,
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key=model_key,
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submodel=SubModelType.UNet,
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submodel_type=SubModelType.UNet,
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),
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),
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scheduler=ModelInfo(
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scheduler=ModelInfo(
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key=model_key,
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key=model_key,
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submodel=SubModelType.Scheduler,
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submodel_type=SubModelType.Scheduler,
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),
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),
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loras=[],
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loras=[],
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),
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),
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clip2=ClipField(
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clip2=ClipField(
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tokenizer=ModelInfo(
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tokenizer=ModelInfo(
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key=model_key,
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key=model_key,
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submodel=SubModelType.Tokenizer2,
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submodel_type=SubModelType.Tokenizer2,
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),
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),
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text_encoder=ModelInfo(
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text_encoder=ModelInfo(
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key=model_key,
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key=model_key,
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submodel=SubModelType.TextEncoder2,
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submodel_type=SubModelType.TextEncoder2,
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),
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),
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loras=[],
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loras=[],
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skipped_layers=0,
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skipped_layers=0,
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@ -142,7 +142,7 @@ class SDXLRefinerModelLoaderInvocation(BaseInvocation):
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vae=VaeField(
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vae=VaeField(
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vae=ModelInfo(
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vae=ModelInfo(
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key=model_key,
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key=model_key,
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submodel=SubModelType.Vae,
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submodel_type=SubModelType.Vae,
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),
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),
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),
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),
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)
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)
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@ -499,7 +499,7 @@ class ModelManager(object):
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model_class=model_class,
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model_class=model_class,
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base_model=base_model,
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base_model=base_model,
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model_type=model_type,
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model_type=model_type,
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submodel=submodel_type,
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submodel_type=submodel_type,
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)
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)
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if model_key not in self.cache_keys:
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if model_key not in self.cache_keys:
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@ -245,7 +245,7 @@ module = [
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"invokeai.app.services.invocation_stats.invocation_stats_default",
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"invokeai.app.services.invocation_stats.invocation_stats_default",
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"invokeai.app.services.model_manager.model_manager_base",
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"invokeai.app.services.model_manager.model_manager_base",
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"invokeai.app.services.model_manager.model_manager_default",
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"invokeai.app.services.model_manager.model_manager_default",
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"invokeai.app.services.model_records.model_records_sql",
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"invokeai.app.services.model_manager.store.model_records_sql",
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"invokeai.app.util.controlnet_utils",
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"invokeai.app.util.controlnet_utils",
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"invokeai.backend.image_util.txt2mask",
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"invokeai.backend.image_util.txt2mask",
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"invokeai.backend.image_util.safety_checker",
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"invokeai.backend.image_util.safety_checker",
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