isort wip 2

invokeai/backend/model_management/models/__init__.py

@@ -1,29 +1,30 @@
 import inspect
 from enum import Enum
-from pydantic import BaseModel
 from typing import Literal, get_origin
+
+from pydantic import BaseModel
+
 from .base import (  # noqa: F401
     BaseModelType,
-    ModelType,
-    SubModelType,
+    DuplicateModelException,
+    InvalidModelException,
     ModelBase,
     ModelConfigBase,
+    ModelError,
+    ModelNotFoundException,
+    ModelType,
     ModelVariantType,
     SchedulerPredictionType,
-    ModelError,
     SilenceWarnings,
-    ModelNotFoundException,
-    InvalidModelException,
-    DuplicateModelException,
+    SubModelType,
 )
-from .stable_diffusion import StableDiffusion1Model, StableDiffusion2Model
-from .sdxl import StableDiffusionXLModel
-from .vae import VaeModel
-from .lora import LoRAModel
 from .controlnet import ControlNetModel  # TODO:
-from .textual_inversion import TextualInversionModel
-
+from .lora import LoRAModel
+from .sdxl import StableDiffusionXLModel
+from .stable_diffusion import StableDiffusion1Model, StableDiffusion2Model
 from .stable_diffusion_onnx import ONNXStableDiffusion1Model, ONNXStableDiffusion2Model
+from .textual_inversion import TextualInversionModel
+from .vae import VaeModel
 
 MODEL_CLASSES = {
     BaseModelType.StableDiffusion1: {

invokeai/backend/model_management/models/base.py

@@ -1,29 +1,25 @@
+import inspect
 import json
 import os
 import sys
 import typing
-import inspect
 import warnings
 from abc import ABCMeta, abstractmethod
 from contextlib import suppress
 from enum import Enum
 from pathlib import Path
-from picklescan.scanner import scan_file_path
+from typing import Any, Callable, Dict, Generic, List, Literal, Optional, Type, TypeVar, Union
 
-import torch
 import numpy as np
 import onnx
 import safetensors.torch
-from diffusers import DiffusionPipeline, ConfigMixin
-from onnx import numpy_helper
-from onnxruntime import (
-    InferenceSession,
-    SessionOptions,
-    get_available_providers,
-)
-from pydantic import BaseModel, Field
-from typing import List, Dict, Optional, Type, Literal, TypeVar, Generic, Callable, Any, Union
+import torch
+from diffusers import ConfigMixin, DiffusionPipeline
 from diffusers import logging as diffusers_logging
+from onnx import numpy_helper
+from onnxruntime import InferenceSession, SessionOptions, get_available_providers
+from picklescan.scanner import scan_file_path
+from pydantic import BaseModel, Field
 from transformers import logging as transformers_logging
 
 

invokeai/backend/model_management/models/controlnet.py

@@ -1,23 +1,26 @@
 import os
-import torch
 from enum import Enum
 from pathlib import Path
-from typing import Optional, Literal
+from typing import Literal, Optional
+
+import torch
+
+import invokeai.backend.util.logging as logger
+from invokeai.app.services.config import InvokeAIAppConfig
+
 from .base import (
+    BaseModelType,
+    EmptyConfigLoader,
+    InvalidModelException,
     ModelBase,
     ModelConfigBase,
-    BaseModelType,
+    ModelNotFoundException,
     ModelType,
     SubModelType,
-    EmptyConfigLoader,
-    calc_model_size_by_fs,
     calc_model_size_by_data,
+    calc_model_size_by_fs,
     classproperty,
-    InvalidModelException,
-    ModelNotFoundException,
 )
-from invokeai.app.services.config import InvokeAIAppConfig
-import invokeai.backend.util.logging as logger
 
 
 class ControlNetModelFormat(str, Enum):

invokeai/backend/model_management/models/sdxl.py

@@ -1,19 +1,21 @@
-import os
 import json
+import os
 from enum import Enum
-from pydantic import Field
 from typing import Literal, Optional
+
+from omegaconf import OmegaConf
+from pydantic import Field
+
 from .base import (
-    ModelConfigBase,
     BaseModelType,
+    DiffusersModel,
+    InvalidModelException,
+    ModelConfigBase,
     ModelType,
     ModelVariantType,
-    DiffusersModel,
-    read_checkpoint_meta,
     classproperty,
-    InvalidModelException,
+    read_checkpoint_meta,
 )
-from omegaconf import OmegaConf
 
 
 class StableDiffusionXLModelFormat(str, Enum):

invokeai/backend/model_management/models/stable_diffusion.py

@@ -1,26 +1,29 @@
-import os
 import json
+import os
 from enum import Enum
-from pydantic import Field
 from pathlib import Path
 from typing import Literal, Optional, Union
+
 from diffusers import StableDiffusionInpaintPipeline, StableDiffusionPipeline
-from .base import (
-    ModelConfigBase,
-    BaseModelType,
-    ModelType,
-    ModelVariantType,
-    DiffusersModel,
-    SilenceWarnings,
-    read_checkpoint_meta,
-    classproperty,
-    InvalidModelException,
-    ModelNotFoundException,
-)
-from .sdxl import StableDiffusionXLModel
+from omegaconf import OmegaConf
+from pydantic import Field
+
 import invokeai.backend.util.logging as logger
 from invokeai.app.services.config import InvokeAIAppConfig
-from omegaconf import OmegaConf
+
+from .base import (
+    BaseModelType,
+    DiffusersModel,
+    InvalidModelException,
+    ModelConfigBase,
+    ModelNotFoundException,
+    ModelType,
+    ModelVariantType,
+    SilenceWarnings,
+    classproperty,
+    read_checkpoint_meta,
+)
+from .sdxl import StableDiffusionXLModel
 
 
 class StableDiffusion1ModelFormat(str, Enum):
@@ -272,8 +275,8 @@ def _convert_ckpt_and_cache(
         return output_path
 
     # to avoid circular import errors
-    from ..convert_ckpt_to_diffusers import convert_ckpt_to_diffusers
     from ...util.devices import choose_torch_device, torch_dtype
+    from ..convert_ckpt_to_diffusers import convert_ckpt_to_diffusers
 
     model_base_to_model_type = {
         BaseModelType.StableDiffusion1: "FrozenCLIPEmbedder",

invokeai/backend/model_management/models/stable_diffusion_onnx.py

@@ -2,15 +2,16 @@ from enum import Enum
 from typing import Literal
 
 from diffusers import OnnxRuntimeModel
+
 from .base import (
-    ModelConfigBase,
     BaseModelType,
+    DiffusersModel,
+    IAIOnnxRuntimeModel,
+    ModelConfigBase,
     ModelType,
     ModelVariantType,
-    DiffusersModel,
     SchedulerPredictionType,
     classproperty,
-    IAIOnnxRuntimeModel,
 )
 
 

invokeai/backend/model_management/models/textual_inversion.py

@@ -1,19 +1,20 @@
 import os
-import torch
 from typing import Optional
-from .base import (
-    ModelBase,
-    ModelConfigBase,
-    BaseModelType,
-    ModelType,
-    SubModelType,
-    classproperty,
-    ModelNotFoundException,
-    InvalidModelException,
-)
+
+import torch
 
 # TODO: naming
 from ..lora import TextualInversionModel as TextualInversionModelRaw
+from .base import (
+    BaseModelType,
+    InvalidModelException,
+    ModelBase,
+    ModelConfigBase,
+    ModelNotFoundException,
+    ModelType,
+    SubModelType,
+    classproperty,
+)
 
 
 class TextualInversionModel(ModelBase):

invokeai/backend/model_management/models/vae.py

@@ -8,19 +8,20 @@ import torch
 from omegaconf import OmegaConf
 
 from invokeai.app.services.config import InvokeAIAppConfig
+
 from .base import (
+    BaseModelType,
+    EmptyConfigLoader,
+    InvalidModelException,
     ModelBase,
     ModelConfigBase,
-    BaseModelType,
-    ModelType,
-    SubModelType,
-    ModelVariantType,
-    EmptyConfigLoader,
-    calc_model_size_by_fs,
-    calc_model_size_by_data,
-    classproperty,
-    InvalidModelException,
     ModelNotFoundException,
+    ModelType,
+    ModelVariantType,
+    SubModelType,
+    calc_model_size_by_data,
+    calc_model_size_by_fs,
+    classproperty,
 )