Formatting

Author: jazzhaiku

Diff for: invokeai/app/services/model_install/model_install_default.py

@@ -647,14 +647,12 @@ def _probe(self, model_path: Path, config: Optional[ModelRecordChanges] = None):
         config = config or ModelRecordChanges()
         hash_algo = self._app_config.hashing_algorithm
         fields = config.model_dump()
-        overrides = { "hash_algo": hash_algo, **fields}
+        overrides = {"hash_algo": hash_algo, **fields}
 
         try:
             return ModelConfigBase.classify(model_path, **overrides)
         except InvalidModelConfigException:
-            return ModelProbe.probe(
-                model_path=model_path, fields=fields, hash_algo=hash_algo
-            )  # type: ignore
+            return ModelProbe.probe(model_path=model_path, fields=fields, hash_algo=hash_algo)  # type: ignore
 
     def _register(
         self, model_path: Path, config: Optional[ModelRecordChanges] = None, info: Optional[AnyModelConfig] = None

Diff for: invokeai/backend/model_manager/config.py

@@ -202,6 +202,7 @@ class ControlAdapterDefaultSettings(BaseModel):
 
 class ModelOnDisk:
     """A utility class representing a model stored on disk."""
+
     def __init__(self, path: Path):
         self.path = path
         self.format_type = ModelFormat.Diffusers if path.is_dir() else ModelFormat.Checkpoint
@@ -279,7 +280,7 @@ def __init_subclass__(cls, **kwargs):
     @staticmethod
     def all_config_classes():
         subclasses = ModelConfigBase._USING_LEGACY_PROBE | ModelConfigBase._USING_CLASSIFY_API
-        concrete = { cls for cls in subclasses if not isabstract(cls) }
+        concrete = {cls for cls in subclasses if not isabstract(cls)}
         return concrete
 
     @staticmethod
@@ -332,7 +333,7 @@ def from_model_on_disk(cls, mod: ModelOnDisk, **overrides):
 
         fields = cls.parse(mod)
 
-        fields["path"] =  mod.path.as_posix()
+        fields["path"] = mod.path.as_posix()
         fields["source"] = fields.get("source") or fields["path"]
         fields["source_type"] = fields.get("source_type") or ModelSourceType.Path
         fields["name"] = mod.name
@@ -388,17 +389,14 @@ class T5EncoderConfigBase(ABC, BaseModel):
     type: Literal[ModelType.T5Encoder] = ModelType.T5Encoder
 
 
-
 class T5EncoderConfig(T5EncoderConfigBase, LegacyProbeMixin, ModelConfigBase):
     format: Literal[ModelFormat.T5Encoder] = ModelFormat.T5Encoder
 
 
-
 class T5EncoderBnbQuantizedLlmInt8bConfig(T5EncoderConfigBase, LegacyProbeMixin, ModelConfigBase):
     format: Literal[ModelFormat.BnbQuantizedLlmInt8b] = ModelFormat.BnbQuantizedLlmInt8b
 
 
-
 class LoRALyCORISConfig(LoRAConfigBase, LegacyProbeMixin, ModelConfigBase):
     """Model config for LoRA/Lycoris models."""
 
@@ -411,7 +409,6 @@ class ControlAdapterConfigBase(ABC, BaseModel):
     )
 
 
-
 class ControlLoRALyCORISConfig(ControlAdapterConfigBase, LegacyProbeMixin, ModelConfigBase):
     """Model config for Control LoRA models."""
 
@@ -420,7 +417,6 @@ class ControlLoRALyCORISConfig(ControlAdapterConfigBase, LegacyProbeMixin, Model
     format: Literal[ModelFormat.LyCORIS] = ModelFormat.LyCORIS
 
 
-
 class ControlLoRADiffusersConfig(ControlAdapterConfigBase, LegacyProbeMixin, ModelConfigBase):
     """Model config for Control LoRA models."""
 
@@ -429,52 +425,45 @@ class ControlLoRADiffusersConfig(ControlAdapterConfigBase, LegacyProbeMixin, Mod
     format: Literal[ModelFormat.Diffusers] = ModelFormat.Diffusers
 
 
-
 class LoRADiffusersConfig(LoRAConfigBase, LegacyProbeMixin, ModelConfigBase):
     """Model config for LoRA/Diffusers models."""
 
     format: Literal[ModelFormat.Diffusers] = ModelFormat.Diffusers
 
 
-
 class VAECheckpointConfig(CheckpointConfigBase, LegacyProbeMixin, ModelConfigBase):
     """Model config for standalone VAE models."""
 
     type: Literal[ModelType.VAE] = ModelType.VAE
 
 
-
 class VAEDiffusersConfig(LegacyProbeMixin, ModelConfigBase):
     """Model config for standalone VAE models (diffusers version)."""
 
     type: Literal[ModelType.VAE] = ModelType.VAE
     format: Literal[ModelFormat.Diffusers] = ModelFormat.Diffusers
 
 
-
 class ControlNetDiffusersConfig(DiffusersConfigBase, ControlAdapterConfigBase, LegacyProbeMixin, ModelConfigBase):
     """Model config for ControlNet models (diffusers version)."""
 
     type: Literal[ModelType.ControlNet] = ModelType.ControlNet
     format: Literal[ModelFormat.Diffusers] = ModelFormat.Diffusers
 
 
-
 class ControlNetCheckpointConfig(CheckpointConfigBase, ControlAdapterConfigBase, LegacyProbeMixin, ModelConfigBase):
     """Model config for ControlNet models (diffusers version)."""
 
     type: Literal[ModelType.ControlNet] = ModelType.ControlNet
 
 
-
 class TextualInversionFileConfig(LegacyProbeMixin, ModelConfigBase):
     """Model config for textual inversion embeddings."""
 
     type: Literal[ModelType.TextualInversion] = ModelType.TextualInversion
     format: Literal[ModelFormat.EmbeddingFile] = ModelFormat.EmbeddingFile
 
 
-
 class TextualInversionFolderConfig(LegacyProbeMixin, ModelConfigBase):
     """Model config for textual inversion embeddings."""
 
@@ -491,15 +480,13 @@ class MainConfigBase(ABC, BaseModel):
     variant: AnyVariant = ModelVariantType.Normal
 
 
-
 class MainCheckpointConfig(CheckpointConfigBase, MainConfigBase, LegacyProbeMixin, ModelConfigBase):
     """Model config for main checkpoint models."""
 
     prediction_type: SchedulerPredictionType = SchedulerPredictionType.Epsilon
     upcast_attention: bool = False
 
 
-
 class MainBnbQuantized4bCheckpointConfig(CheckpointConfigBase, MainConfigBase, LegacyProbeMixin, ModelConfigBase):
     """Model config for main checkpoint models."""
 
@@ -508,7 +495,6 @@ class MainBnbQuantized4bCheckpointConfig(CheckpointConfigBase, MainConfigBase, L
     upcast_attention: bool = False
 
 
-
 class MainGGUFCheckpointConfig(CheckpointConfigBase, MainConfigBase, LegacyProbeMixin, ModelConfigBase):
     """Model config for main checkpoint models."""
 
@@ -517,7 +503,6 @@ class MainGGUFCheckpointConfig(CheckpointConfigBase, MainConfigBase, LegacyProbe
     upcast_attention: bool = False
 
 
-
 class MainDiffusersConfig(DiffusersConfigBase, MainConfigBase, LegacyProbeMixin, ModelConfigBase):
     """Model config for main diffusers models."""
 
@@ -528,7 +513,6 @@ class IPAdapterConfigBase(ABC, BaseModel):
     type: Literal[ModelType.IPAdapter] = ModelType.IPAdapter
 
 
-
 class IPAdapterInvokeAIConfig(IPAdapterConfigBase, LegacyProbeMixin, ModelConfigBase):
     """Model config for IP Adapter diffusers format models."""
 
@@ -538,7 +522,6 @@ class IPAdapterInvokeAIConfig(IPAdapterConfigBase, LegacyProbeMixin, ModelConfig
     format: Literal[ModelFormat.InvokeAI] = ModelFormat.InvokeAI
 
 
-
 class IPAdapterCheckpointConfig(IPAdapterConfigBase, LegacyProbeMixin, ModelConfigBase):
     """Model config for IP Adapter checkpoint format models."""
 
@@ -553,7 +536,6 @@ class CLIPEmbedDiffusersConfig(DiffusersConfigBase):
     format: Literal[ModelFormat.Diffusers] = ModelFormat.Diffusers
 
 
-
 class CLIPGEmbedDiffusersConfig(CLIPEmbedDiffusersConfig, LegacyProbeMixin, ModelConfigBase):
     """Model config for CLIP-G Embeddings."""
 
@@ -564,7 +546,6 @@ def get_tag(cls) -> Tag:
         return Tag(f"{ModelType.CLIPEmbed.value}.{ModelFormat.Diffusers.value}.{ClipVariantType.G.value}")
 
 
-
 class CLIPLEmbedDiffusersConfig(CLIPEmbedDiffusersConfig, LegacyProbeMixin, ModelConfigBase):
     """Model config for CLIP-L Embeddings."""
 
@@ -575,23 +556,20 @@ def get_tag(cls) -> Tag:
         return Tag(f"{ModelType.CLIPEmbed.value}.{ModelFormat.Diffusers.value}.{ClipVariantType.L.value}")
 
 
-
 class CLIPVisionDiffusersConfig(DiffusersConfigBase, LegacyProbeMixin, ModelConfigBase):
     """Model config for CLIPVision."""
 
     type: Literal[ModelType.CLIPVision] = ModelType.CLIPVision
     format: Literal[ModelFormat.Diffusers] = ModelFormat.Diffusers
 
 
-
 class T2IAdapterConfig(DiffusersConfigBase, ControlAdapterConfigBase, LegacyProbeMixin, ModelConfigBase):
     """Model config for T2I."""
 
     type: Literal[ModelType.T2IAdapter] = ModelType.T2IAdapter
     format: Literal[ModelFormat.Diffusers] = ModelFormat.Diffusers
 
 
-
 class SpandrelImageToImageConfig(LegacyProbeMixin, ModelConfigBase):
     """Model config for Spandrel Image to Image models."""
 
@@ -601,15 +579,13 @@ class SpandrelImageToImageConfig(LegacyProbeMixin, ModelConfigBase):
     format: Literal[ModelFormat.Checkpoint] = ModelFormat.Checkpoint
 
 
-
 class SigLIPConfig(DiffusersConfigBase, LegacyProbeMixin, ModelConfigBase):
     """Model config for SigLIP."""
 
     type: Literal[ModelType.SigLIP] = ModelType.SigLIP
     format: Literal[ModelFormat.Diffusers] = ModelFormat.Diffusers
 
 
-
 class FluxReduxConfig(LegacyProbeMixin, ModelConfigBase):
     """Model config for FLUX Tools Redux model."""
 

Diff for: tests/test_model_probe.py

@@ -177,10 +177,16 @@ def test_serialisation_roundtrip():
     for config_cls in ModelConfigBase.all_config_classes() - excluded:
         trials_per_class = 50
 
-        factory_args = { "__use_defaults__": True, "__random_seed__": 1234, "__check_model__": True, }
+        factory_args = {
+            "__use_defaults__": True,
+            "__random_seed__": 1234,
+            "__check_model__": True,
+        }
         factory = ModelFactory.create_factory(config_cls, **factory_args)
 
-        configs_with_random_data = [factory.build() for _ in range(trials_per_class)] #mocker.mock(config_cls, trials_per_class)
+        configs_with_random_data = [
+            factory.build() for _ in range(trials_per_class)
+        ]  # mocker.mock(config_cls, trials_per_class)
 
         for config in configs_with_random_data:
             as_json = config.model_dump_json()
@@ -204,4 +210,3 @@ def test_inheritance_order():
         excluded = {abc.ABC, pydantic.BaseModel, object}
         inheritance_list = [cls for cls in config_cls.mro() if cls not in excluded]
         assert inheritance_list[-1] is ModelConfigBase
-