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tidy(nodes): rename sd_model_loader to pipeline_model_loader

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this is more accurate bc it can do eg kandinsky also
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psychedelicious 2023-06-22 17:47:58 +10:00
parent 3722cdf5d6
commit 1bc170727b
1 changed files with 3 additions and 208 deletions
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211
invokeai/app/invocations/model.py
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@ -50,10 +50,10 @@ class PipelineModelField(BaseModel):
base_model: BaseModelType = Field(description="Base model") base_model: BaseModelType = Field(description="Base model")
class SDModelLoaderInvocation(BaseInvocation): class PipelineModelLoaderInvocation(BaseInvocation):
"""Loading submodels of selected model.""" """Loads a pipeline model, outputting its submodels."""
type: Literal["sd_model_loader"] = "sd_model_loader" type: Literal["pipeline_model_loader"] = "pipeline_model_loader"
model: PipelineModelField = Field(description="The model to load") model: PipelineModelField = Field(description="The model to load")
# TODO: precision? # TODO: precision?
@ -154,211 +154,6 @@ class SDModelLoaderInvocation(BaseInvocation):
) )
) )
class SD1ModelLoaderInvocation(BaseInvocation):
"""Loading submodels of selected model."""
type: Literal["sd1_model_loader"] = "sd1_model_loader"
model_name: str = Field(default="", description="Model to load")
# TODO: precision?
# Schema customisation
class Config(InvocationConfig):
schema_extra = {
"ui": {
"tags": ["model", "loader"],
"type_hints": {
"model_name": "model" # TODO: rename to model_name?
}
},
}
def invoke(self, context: InvocationContext) -> ModelLoaderOutput:
base_model = BaseModelType.StableDiffusion1 # TODO:
# TODO: not found exceptions
if not context.services.model_manager.model_exists(
model_name=self.model_name,
base_model=base_model,
model_type=ModelType.Pipeline,
):
raise Exception(f"Unkown model name: {self.model_name}!")
"""
if not context.services.model_manager.model_exists(
model_name=self.model_name,
model_type=SDModelType.Diffusers,
submodel=SDModelType.Tokenizer,
):
raise Exception(
f"Failed to find tokenizer submodel in {self.model_name}! Check if model corrupted"
)
if not context.services.model_manager.model_exists(
model_name=self.model_name,
model_type=SDModelType.Diffusers,
submodel=SDModelType.TextEncoder,
):
raise Exception(
f"Failed to find text_encoder submodel in {self.model_name}! Check if model corrupted"
)
if not context.services.model_manager.model_exists(
model_name=self.model_name,
model_type=SDModelType.Diffusers,
submodel=SDModelType.UNet,
):
raise Exception(
f"Failed to find unet submodel from {self.model_name}! Check if model corrupted"
)
"""
return ModelLoaderOutput(
unet=UNetField(
unet=ModelInfo(
model_name=self.model_name,
base_model=base_model,
model_type=ModelType.Pipeline,
submodel=SubModelType.UNet,
),
scheduler=ModelInfo(
model_name=self.model_name,
base_model=base_model,
model_type=ModelType.Pipeline,
submodel=SubModelType.Scheduler,
),
loras=[],
),
clip=ClipField(
tokenizer=ModelInfo(
model_name=self.model_name,
base_model=base_model,
model_type=ModelType.Pipeline,
submodel=SubModelType.Tokenizer,
),
text_encoder=ModelInfo(
model_name=self.model_name,
base_model=base_model,
model_type=ModelType.Pipeline,
submodel=SubModelType.TextEncoder,
),
loras=[],
),
vae=VaeField(
vae=ModelInfo(
model_name=self.model_name,
base_model=base_model,
model_type=ModelType.Pipeline,
submodel=SubModelType.Vae,
),
)
)
# TODO: optimize(less code copy)
class SD2ModelLoaderInvocation(BaseInvocation):
"""Loading submodels of selected model."""
type: Literal["sd2_model_loader"] = "sd2_model_loader"
model_name: str = Field(default="", description="Model to load")
# TODO: precision?
# Schema customisation
class Config(InvocationConfig):
schema_extra = {
"ui": {
"tags": ["model", "loader"],
"type_hints": {
"model_name": "model" # TODO: rename to model_name?
}
},
}
def invoke(self, context: InvocationContext) -> ModelLoaderOutput:
base_model = BaseModelType.StableDiffusion2 # TODO:
# TODO: not found exceptions
if not context.services.model_manager.model_exists(
model_name=self.model_name,
base_model=base_model,
model_type=ModelType.Pipeline,
):
raise Exception(f"Unkown model name: {self.model_name}!")
"""
if not context.services.model_manager.model_exists(
model_name=self.model_name,
model_type=SDModelType.Diffusers,
submodel=SDModelType.Tokenizer,
):
raise Exception(
f"Failed to find tokenizer submodel in {self.model_name}! Check if model corrupted"
)
if not context.services.model_manager.model_exists(
model_name=self.model_name,
model_type=SDModelType.Diffusers,
submodel=SDModelType.TextEncoder,
):
raise Exception(
f"Failed to find text_encoder submodel in {self.model_name}! Check if model corrupted"
)
if not context.services.model_manager.model_exists(
model_name=self.model_name,
model_type=SDModelType.Diffusers,
submodel=SDModelType.UNet,
):
raise Exception(
f"Failed to find unet submodel from {self.model_name}! Check if model corrupted"
)
"""
return ModelLoaderOutput(
unet=UNetField(
unet=ModelInfo(
model_name=self.model_name,
base_model=base_model,
model_type=ModelType.Pipeline,
submodel=SubModelType.UNet,
),
scheduler=ModelInfo(
model_name=self.model_name,
base_model=base_model,
model_type=ModelType.Pipeline,
submodel=SubModelType.Scheduler,
),
loras=[],
),
clip=ClipField(
tokenizer=ModelInfo(
model_name=self.model_name,
base_model=base_model,
model_type=ModelType.Pipeline,
submodel=SubModelType.Tokenizer,
),
text_encoder=ModelInfo(
model_name=self.model_name,
base_model=base_model,
model_type=ModelType.Pipeline,
submodel=SubModelType.TextEncoder,
),
loras=[],
),
vae=VaeField(
vae=ModelInfo(
model_name=self.model_name,
base_model=base_model,
model_type=ModelType.Pipeline,
submodel=SubModelType.Vae,
),
)
)
class LoraLoaderOutput(BaseInvocationOutput): class LoraLoaderOutput(BaseInvocationOutput):
"""Model loader output""" """Model loader output"""