blackify and isort

invokeai/app/api/dependencies.py

@@ -25,7 +25,6 @@ from ..services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsSto
 from ..services.model_manager_service import ModelManagerService
 from ..services.processor import DefaultInvocationProcessor
 from ..services.sqlite import SqliteItemStorage
-from ..services.invocation_stats import InvocationStatsService
 from .events import FastAPIEventService
 
 

invokeai/app/api/routers/models.py

@@ -10,13 +10,13 @@ from pydantic import BaseModel, parse_obj_as
 from starlette.exceptions import HTTPException
 
 from invokeai.backend import BaseModelType, ModelType
-from invokeai.backend.model_manager import MergeInterpolationMethod
 from invokeai.backend.model_manager import (
     OPENAPI_MODEL_CONFIGS,
-    ModelConfigBase,
     InvalidModelException,
-    UnknownModelException,
+    MergeInterpolationMethod,
+    ModelConfigBase,
     SchedulerPredictionType,
+    UnknownModelException,
 )
 
 from ..dependencies import ApiDependencies

invokeai/app/invocations/controlnet_image_processors.py

@@ -28,7 +28,6 @@ from pydantic import BaseModel, Field, validator
 
 from invokeai.app.invocations.primitives import ImageField, ImageOutput
 
-
 from ...backend.model_manager import BaseModelType
 from ..models.image import ImageCategory, ResourceOrigin
 from .baseinvocation import (

invokeai/app/invocations/latent.py

@@ -34,8 +34,8 @@ from invokeai.app.util.step_callback import stable_diffusion_step_callback
 from invokeai.backend.model_manager import BaseModelType, ModelType, SilenceWarnings
 
 from ...backend.model_manager.lora import ModelPatcher
-from ...backend.model_manager.seamless import set_seamless
 from ...backend.model_manager.models import BaseModelType
+from ...backend.model_manager.seamless import set_seamless
 from ...backend.stable_diffusion import PipelineIntermediateState
 from ...backend.stable_diffusion.diffusers_pipeline import (
     ConditioningData,

invokeai/app/invocations/math.py

@@ -178,7 +178,7 @@ class IntegerMathInvocation(BaseInvocation):
         elif self.operation == "DIV":
             return IntegerOutput(value=int(self.a / self.b))
         elif self.operation == "EXP":
-            return IntegerOutput(value=self.a**self.b)
+            return IntegerOutput(value=self.a ** self.b)
         elif self.operation == "MOD":
             return IntegerOutput(value=self.a % self.b)
         elif self.operation == "ABS":
@@ -252,7 +252,7 @@ class FloatMathInvocation(BaseInvocation):
         elif self.operation == "DIV":
             return FloatOutput(value=self.a / self.b)
         elif self.operation == "EXP":
-            return FloatOutput(value=self.a**self.b)
+            return FloatOutput(value=self.a ** self.b)
         elif self.operation == "SQRT":
             return FloatOutput(value=np.sqrt(self.a))
         elif self.operation == "ABS":

invokeai/app/services/download_manager.py

@@ -5,10 +5,13 @@ Model download service.
 
 from abc import ABC, abstractmethod
 from pathlib import Path
-from typing import Optional, List, Union
+from typing import List, Optional, Union
+
 from pydantic.networks import AnyHttpUrl
+
+from invokeai.backend.model_manager.download import DownloadEventHandler, DownloadJobBase, DownloadQueue
+
 from .events import EventServiceBase
-from invokeai.backend.model_manager.download import DownloadQueue, DownloadJobBase, DownloadEventHandler
 
 
 class DownloadQueueServiceBase(ABC):

invokeai/app/services/events.py

@@ -5,12 +5,6 @@ from typing import Any, Optional
 from invokeai.app.models.image import ProgressImage
 from invokeai.app.services.model_manager_service import BaseModelType, ModelInfo, ModelType, SubModelType
 from invokeai.app.util.misc import get_timestamp
-from invokeai.app.services.model_manager_service import (
-    BaseModelType,
-    ModelType,
-    SubModelType,
-    ModelInfo,
-)
 from invokeai.backend.model_manager.download import DownloadJobBase
 
 

invokeai/app/services/invocation_services.py

@@ -1,5 +1,6 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
 from __future__ import annotations
+
 from typing import TYPE_CHECKING, Optional
 
 if TYPE_CHECKING:

invokeai/app/services/invocation_stats.py

@@ -44,7 +44,6 @@ from ..invocations.baseinvocation import BaseInvocation
 from .graph import GraphExecutionState
 from .item_storage import ItemStorageABC
 from .model_manager_service import ModelManagerService
-from invokeai.backend.model_manager.cache import CacheStats
 
 # size of GIG in bytes
 GIG = 1073741824

invokeai/app/services/model_manager_service.py

@@ -5,9 +5,15 @@ from __future__ import annotations
 import shutil
 from abc import ABC, abstractmethod
 from pathlib import Path
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
 
+from pydantic import Field
+from pydantic.networks import AnyHttpUrl
+
+from invokeai.app.models.exceptions import CanceledException
 from invokeai.backend.model_manager import (
     BaseModelType,
+    DuplicateModelException,
     MergeInterpolationMethod,
     ModelConfigBase,
     ModelInfo,
@@ -18,15 +24,9 @@ from invokeai.backend.model_manager import (
     ModelType,
     SubModelType,
     UnknownModelException,
-    DuplicateModelException,
 )
 from invokeai.backend.model_manager.cache import CacheStats
-from typing import TYPE_CHECKING, List, Optional, Union, Dict, Any
 
-from pydantic import Field
-from pydantic.networks import AnyHttpUrl
-
-from invokeai.app.models.exceptions import CanceledException
 from .config import InvokeAIAppConfig
 from .events import EventServiceBase
 

invokeai/app/util/step_callback.py

@@ -3,10 +3,11 @@ from PIL import Image
 
 from invokeai.app.models.exceptions import CanceledException
 from invokeai.app.models.image import ProgressImage
-from ..invocations.baseinvocation import InvocationContext
-from ...backend.util.util import image_to_dataURL
-from ...backend.stable_diffusion import PipelineIntermediateState
+
 from ...backend.model_manager import BaseModelType
+from ...backend.stable_diffusion import PipelineIntermediateState
+from ...backend.util.util import image_to_dataURL
+from ..invocations.baseinvocation import InvocationContext
 
 
 def sample_to_lowres_estimated_image(samples, latent_rgb_factors, smooth_matrix=None):

invokeai/backend/__init__.py

@@ -2,15 +2,15 @@
 Initialization file for invokeai.backend
 """
 from .model_manager import (  # noqa F401
-    ModelLoader,
-    ModelInstall,
-    ModelConfigStore,
-    SilenceWarnings,
+    BaseModelType,
     DuplicateModelException,
     InvalidModelException,
-    BaseModelType,
+    ModelConfigStore,
+    ModelInstall,
+    ModelLoader,
     ModelType,
-    SubModelType,
-    SchedulerPredictionType,
     ModelVariantType,
+    SchedulerPredictionType,
+    SilenceWarnings,
+    SubModelType,
 )

invokeai/backend/model_manager/__init__.py

@@ -1,7 +1,6 @@
 """
 Initialization file for invokeai.backend.model_manager.config
 """
-from .models import read_checkpoint_meta, OPENAPI_MODEL_CONFIGS  # noqa F401
 from .config import (  # noqa F401
     BaseModelType,
     InvalidModelConfigException,
@@ -11,19 +10,20 @@ from .config import (  # noqa F401
     ModelType,
     ModelVariantType,
     SchedulerPredictionType,
-    SubModelType,
     SilenceWarnings,
+    SubModelType,
 )
-from .lora import ONNXModelPatcher, ModelPatcher
-from .loader import ModelLoader, ModelInfo  # noqa F401
 from .install import ModelInstall, ModelInstallJob  # noqa F401
-from .probe import ModelProbe, InvalidModelException  # noqa F401
-from .storage import (
-    UnknownModelException,
+from .loader import ModelInfo, ModelLoader  # noqa F401
+from .lora import ModelPatcher, ONNXModelPatcher
+from .merge import MergeInterpolationMethod, ModelMerger
+from .models import OPENAPI_MODEL_CONFIGS, read_checkpoint_meta  # noqa F401
+from .probe import InvalidModelException, ModelProbe  # noqa F401
+from .search import ModelSearch  # noqa F401
+from .storage import (  # noqa F401
     DuplicateModelException,
     ModelConfigStore,
-    ModelConfigStoreYAML,
     ModelConfigStoreSQL,
-)  # noqa F401
-from .search import ModelSearch  # noqa F401
-from .merge import MergeInterpolationMethod, ModelMerger
+    ModelConfigStoreYAML,
+    UnknownModelException,
+)

invokeai/backend/model_manager/config.py

@@ -20,16 +20,16 @@ Validation errors will raise an InvalidModelConfigException error.
 
 """
 import warnings
-
 from enum import Enum
-from typing import Optional, Literal, List, Union, Type
-from omegaconf.listconfig import ListConfig  # to support the yaml backend
+from typing import List, Literal, Optional, Type, Union
+
 import pydantic
-from pydantic import BaseModel, Field, Extra
-from pydantic.error_wrappers import ValidationError
 
 # import these so that we can silence them
 from diffusers import logging as diffusers_logging
+from omegaconf.listconfig import ListConfig  # to support the yaml backend
+from pydantic import BaseModel, Extra, Field
+from pydantic.error_wrappers import ValidationError
 from transformers import logging as transformers_logging
 
 

invokeai/backend/model_manager/download/__init__.py

@@ -1,14 +1,13 @@
 """Initialization file for threaded download manager."""
 
 from .base import (  # noqa F401
-    DownloadQueueBase,
-    DownloadJobStatus,
-    DownloadEventHandler,
-    UnknownJobIDException,
-    DownloadJobBase,
-    ModelSourceMetadata,
-    REPO_ID_RE,
     HTTP_RE,
+    REPO_ID_RE,
+    DownloadEventHandler,
+    DownloadJobBase,
+    DownloadJobStatus,
+    DownloadQueueBase,
+    ModelSourceMetadata,
+    UnknownJobIDException,
 )
-
 from .queue import DownloadQueue  # noqa F401

invokeai/backend/model_manager/download/base.py

@@ -7,7 +7,8 @@ from abc import ABC, abstractmethod
 from enum import Enum
 from functools import total_ordering
 from pathlib import Path
-from typing import List, Optional, Callable, Union
+from typing import Callable, List, Optional, Union
+
 from pydantic import BaseModel, Field
 from pydantic.networks import AnyHttpUrl
 

invokeai/backend/model_manager/download/queue.py

@@ -1,37 +1,36 @@
 # Copyright (c) 2023, Lincoln D. Stein
 """Implementation of multithreaded download queue for invokeai."""
 
-import re
 import os
-import requests
+import re
 import shutil
 import threading
 import time
 import traceback
-
 from json import JSONDecodeError
 from pathlib import Path
-from requests import HTTPError
-from typing import Dict, Optional, Set, List, Tuple, Union
-
-from pydantic import Field, validator, ValidationError
-from pydantic.networks import AnyHttpUrl
 from queue import PriorityQueue
+from typing import Dict, List, Optional, Set, Tuple, Union
 
+import requests
 from huggingface_hub import HfApi, hf_hub_url
+from pydantic import Field, ValidationError, validator
+from pydantic.networks import AnyHttpUrl
+from requests import HTTPError
 
-from invokeai.backend.util.logging import InvokeAILogger
 from invokeai.app.services.config import InvokeAIAppConfig
-from . import REPO_ID_RE, HTTP_RE
-from .base import (
-    DownloadQueueBase,
-    DownloadJobStatus,
-    DownloadEventHandler,
-    UnknownJobIDException,
-    DownloadJobBase,
-    ModelSourceMetadata,
-)
+from invokeai.backend.util.logging import InvokeAILogger
+
 from ..storage import DuplicateModelException
+from . import HTTP_RE, REPO_ID_RE
+from .base import (
+    DownloadEventHandler,
+    DownloadJobBase,
+    DownloadJobStatus,
+    DownloadQueueBase,
+    ModelSourceMetadata,
+    UnknownJobIDException,
+)
 
 # Maximum number of bytes to download during each call to requests.iter_content()
 DOWNLOAD_CHUNK_SIZE = 100000

invokeai/backend/model_manager/hash.py

@@ -8,12 +8,13 @@ from invokeai.backend.model_managre.model_hash import FastModelHash
 'a8e693a126ea5b831c96064dc569956f'
 """
 
-import os
 import hashlib
-from imohash import hashfile
+import os
 from pathlib import Path
 from typing import Dict, Union
 
+from imohash import hashfile
+
 
 class FastModelHash(object):
     """FastModelHash obect provides one public class method, hash()."""

invokeai/backend/model_manager/install.py

@@ -53,32 +53,29 @@ import tempfile
 from abc import ABC, abstractmethod
 from pathlib import Path
 from shutil import rmtree
-from typing import Optional, List, Union, Dict, Set, Any, Callable
+from typing import Any, Callable, Dict, List, Optional, Set, Union
+
 from pydantic import Field
 from pydantic.networks import AnyHttpUrl
+
 from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.backend.util.logging import InvokeAILogger
-from .search import ModelSearch
-from .storage import ModelConfigStore, DuplicateModelException, get_config_store
+
+from .config import BaseModelType, ModelFormat, ModelType, ModelVariantType, SchedulerPredictionType
 from .download import (
-    DownloadQueueBase,
-    DownloadQueue,
-    DownloadJobBase,
-    ModelSourceMetadata,
-    DownloadEventHandler,
-    REPO_ID_RE,
     HTTP_RE,
+    REPO_ID_RE,
+    DownloadEventHandler,
+    DownloadJobBase,
+    DownloadQueue,
+    DownloadQueueBase,
+    ModelSourceMetadata,
 )
-from .download.queue import DownloadJobURL, DownloadJobRepoID, DownloadJobPath
+from .download.queue import DownloadJobPath, DownloadJobRepoID, DownloadJobURL
 from .hash import FastModelHash
-from .probe import ModelProbe, ModelProbeInfo, InvalidModelException
-from .config import (
-    ModelType,
-    BaseModelType,
-    ModelVariantType,
-    ModelFormat,
-    SchedulerPredictionType,
-)
+from .probe import InvalidModelException, ModelProbe, ModelProbeInfo
+from .search import ModelSearch
+from .storage import DuplicateModelException, ModelConfigStore, get_config_store
 
 
 class ModelInstallJob(DownloadJobBase):

invokeai/backend/model_manager/loader.py

@@ -5,18 +5,19 @@ import hashlib
 from abc import ABC, abstractmethod
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Union, Optional, List
+from typing import List, Optional, Union
 
 import torch
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.util import choose_precision, choose_torch_device, InvokeAILogger, Chdir
-from .config import BaseModelType, ModelType, SubModelType, ModelConfigBase
-from .install import ModelInstallBase, ModelInstall
-from .storage import ModelConfigStore, get_config_store
-from .cache import ModelCache, ModelLocker, CacheStats
-from .models import InvalidModelException, ModelBase, MODEL_CLASSES
+from invokeai.backend.util import Chdir, InvokeAILogger, choose_precision, choose_torch_device
+
+from .cache import CacheStats, ModelCache, ModelLocker
+from .config import BaseModelType, ModelConfigBase, ModelType, SubModelType
 from .download import DownloadEventHandler
+from .install import ModelInstall, ModelInstallBase
+from .models import MODEL_CLASSES, InvalidModelException, ModelBase
+from .storage import ModelConfigStore, get_config_store
 
 
 @dataclass

invokeai/backend/model_manager/merge.py

@@ -16,7 +16,7 @@ from diffusers import logging as dlogging
 
 import invokeai.backend.util.logging as logger
 
-from . import ModelLoader, ModelType, BaseModelType, ModelVariantType, ModelConfigBase
+from . import BaseModelType, ModelConfigBase, ModelLoader, ModelType, ModelVariantType
 
 
 class MergeInterpolationMethod(str, Enum):

invokeai/backend/model_manager/models/__init__.py

@@ -11,10 +11,9 @@ from .base import (  # noqa: F401
     ModelConfigBase,
     ModelNotFoundException,
     ModelType,
-    SubModelType,
     ModelVariantType,
     SchedulerPredictionType,
-    InvalidModelException,
+    SubModelType,
     read_checkpoint_meta,
 )
 from .controlnet import ControlNetModel  # TODO:

invokeai/backend/model_manager/models/base.py

@@ -2,33 +2,30 @@ import inspect
 import json
 import os
 import sys
-import torch
 import typing
 from abc import ABCMeta, abstractmethod
 from contextlib import suppress
 from enum import Enum
 from pathlib import Path
-from typing import List, Dict, Optional, Type, Literal, TypeVar, Generic, Callable, Any, Union
+from typing import Any, Callable, Dict, Generic, List, Literal, Optional, Type, TypeVar, Union
 
 import numpy as np
 import onnx
 import safetensors.torch
-from diffusers import DiffusionPipeline, ConfigMixin
+import torch
+from diffusers import ConfigMixin, DiffusionPipeline
 from onnx import numpy_helper
-from onnxruntime import (
-    InferenceSession,
-    SessionOptions,
-    get_available_providers,
-)
+from onnxruntime import InferenceSession, SessionOptions, get_available_providers
 from picklescan.scanner import scan_file_path
+
 from ..config import (  # noqa F401
     BaseModelType,
-    ModelType,
-    SubModelType,
-    ModelVariantType,
-    ModelFormat,
-    SchedulerPredictionType,
     ModelConfigBase,
+    ModelFormat,
+    ModelType,
+    ModelVariantType,
+    SchedulerPredictionType,
+    SubModelType,
 )
 
 

invokeai/backend/model_manager/models/controlnet.py

@@ -7,7 +7,8 @@ import torch
 
 import invokeai.backend.util.logging as logger
 from invokeai.app.services.config import InvokeAIAppConfig
-from ..config import ControlNetDiffusersConfig, ControlNetCheckpointConfig
+
+from ..config import ControlNetCheckpointConfig, ControlNetDiffusersConfig
 from .base import (
     BaseModelType,
     EmptyConfigLoader,

invokeai/backend/model_manager/models/lora.py

@@ -2,10 +2,11 @@ import bisect
 import os
 from enum import Enum
 from pathlib import Path
-from typing import Dict, Optional, Union, Literal
+from typing import Dict, Literal, Optional, Union
 
 import torch
 from safetensors.torch import load_file
+
 from ..config import LoRAConfig
 from .base import (
     BaseModelType,

invokeai/backend/model_manager/models/sdxl.py

@@ -5,7 +5,8 @@ from typing import Literal, Optional
 
 from omegaconf import OmegaConf
 from pydantic import Field
-from ..config import MainDiffusersConfig, MainCheckpointConfig
+
+from ..config import MainCheckpointConfig, MainDiffusersConfig
 from .base import (
     BaseModelType,
     DiffusersModel,

invokeai/backend/model_manager/models/stable_diffusion.py

@@ -4,15 +4,14 @@ from enum import Enum
 from pathlib import Path
 from typing import Literal, Optional, Union
 
+from diffusers import StableDiffusionInpaintPipeline, StableDiffusionPipeline
 from omegaconf import OmegaConf
 from pydantic import Field
 
-from diffusers import StableDiffusionInpaintPipeline, StableDiffusionPipeline
-from ..config import SilenceWarnings
 import invokeai.backend.util.logging as logger
 from invokeai.app.services.config import InvokeAIAppConfig
 
-from ..config import MainCheckpointConfig, MainDiffusersConfig
+from ..config import MainCheckpointConfig, MainDiffusersConfig, SilenceWarnings
 from .base import (
     BaseModelType,
     DiffusersModel,

invokeai/backend/model_manager/models/stable_diffusion_onnx.py

@@ -2,6 +2,7 @@ from enum import Enum
 from typing import Literal
 
 from diffusers import OnnxRuntimeModel
+
 from ..config import ONNXSD1Config, ONNXSD2Config
 from .base import (
     BaseModelType,

invokeai/backend/model_manager/models/textual_inversion.py

@@ -1,11 +1,12 @@
 import os
-from typing import Optional, Literal
+from typing import Literal, Optional
 
 import torch
 
+from ..config import ModelFormat, TextualInversionConfig
+
 # TODO: naming
 from ..lora import TextualInversionModel as TextualInversionModelRaw
-from ..config import ModelFormat, TextualInversionConfig
 from .base import (
     BaseModelType,
     InvalidModelException,

invokeai/backend/model_manager/models/vae.py

@@ -1,14 +1,15 @@
 import os
 from enum import Enum
 from pathlib import Path
-from typing import Optional, Literal
+from typing import Literal, Optional
 
 import safetensors
 import torch
 from omegaconf import OmegaConf
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from ..config import VaeDiffusersConfig, VaeCheckpointConfig
+
+from ..config import VaeCheckpointConfig, VaeDiffusersConfig
 from .base import (
     BaseModelType,
     EmptyConfigLoader,

invokeai/backend/model_manager/probe.py

@@ -10,21 +10,14 @@ import json
 from abc import ABC, abstractmethod
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Optional, Callable
+from typing import Callable, Optional
+
+import safetensors.torch
+import torch
 from picklescan.scanner import scan_file_path
 
-import torch
-import safetensors.torch
-
-from .util import read_checkpoint_meta
-from .config import (
-    ModelType,
-    BaseModelType,
-    ModelVariantType,
-    ModelFormat,
-    SchedulerPredictionType,
-)
-from .util import SilenceWarnings, lora_token_vector_length
+from .config import BaseModelType, ModelFormat, ModelType, ModelVariantType, SchedulerPredictionType
+from .util import SilenceWarnings, lora_token_vector_length, read_checkpoint_meta
 
 
 class InvalidModelException(Exception):

invokeai/backend/model_manager/search.py

@@ -22,11 +22,12 @@ Example usage:
 
 import os
 from abc import ABC, abstractmethod
-from typing import Set, Optional, Callable, Union
 from pathlib import Path
+from typing import Callable, Optional, Set, Union
+
+from pydantic import BaseModel, Field
 
 from invokeai.backend.util.logging import InvokeAILogger
-from pydantic import Field, BaseModel
 
 default_logger = InvokeAILogger.getLogger()
 

invokeai/backend/model_manager/storage/__init__.py

@@ -3,9 +3,9 @@ Initialization file for invokeai.backend.model_manager.storage
 """
 import pathlib
 
-from .base import ModelConfigStore, UnknownModelException, DuplicateModelException  # noqa F401
-from .yaml import ModelConfigStoreYAML  # noqa F401
+from .base import DuplicateModelException, ModelConfigStore, UnknownModelException  # noqa F401
 from .sql import ModelConfigStoreSQL  # noqa F401
+from .yaml import ModelConfigStoreYAML  # noqa F401
 
 
 def get_config_store(location: pathlib.Path) -> ModelConfigStore:

invokeai/backend/model_manager/storage/base.py

@@ -4,9 +4,9 @@ Abstract base class for storing and retrieving model configuration records.
 """
 
 from abc import ABC, abstractmethod
-from typing import Union, Set, List, Optional
+from typing import List, Optional, Set, Union
 
-from ..config import ModelConfigBase, BaseModelType, ModelType
+from ..config import BaseModelType, ModelConfigBase, ModelType
 
 # should match the InvokeAI version when this is first released.
 CONFIG_FILE_VERSION = "3.1.1"

invokeai/backend/model_manager/storage/sql.py

@@ -40,26 +40,14 @@ Typical usage:
   configs = store.search_by_name(base_model='sd-2', model_type='main')
 """
 
-import threading
-import sqlite3
 import json
+import sqlite3
+import threading
 from pathlib import Path
-from typing import Union, List, Optional, Set
+from typing import List, Optional, Set, Union
 
-
-from ..config import (
-    ModelConfigBase,
-    ModelConfigFactory,
-    BaseModelType,
-    ModelType,
-)
-
-from .base import (
-    DuplicateModelException,
-    UnknownModelException,
-    ModelConfigStore,
-    CONFIG_FILE_VERSION,
-)
+from ..config import BaseModelType, ModelConfigBase, ModelConfigFactory, ModelType
+from .base import CONFIG_FILE_VERSION, DuplicateModelException, ModelConfigStore, UnknownModelException
 
 
 class ModelConfigStoreSQL(ModelConfigStore):

invokeai/backend/model_manager/storage/yaml.py

@@ -41,26 +41,16 @@ Typical usage:
 """
 
 import threading
-import yaml
 from enum import Enum
 from pathlib import Path
-from typing import Union, Set, List, Optional
+from typing import List, Optional, Set, Union
+
+import yaml
 from omegaconf import OmegaConf
 from omegaconf.dictconfig import DictConfig
 
-from ..config import (
-    ModelConfigBase,
-    ModelConfigFactory,
-    BaseModelType,
-    ModelType,
-)
-
-from .base import (
-    DuplicateModelException,
-    UnknownModelException,
-    ModelConfigStore,
-    CONFIG_FILE_VERSION,
-)
+from ..config import BaseModelType, ModelConfigBase, ModelConfigFactory, ModelType
+from .base import CONFIG_FILE_VERSION, DuplicateModelException, ModelConfigStore, UnknownModelException
 
 
 class ModelConfigStoreYAML(ModelConfigStore):

invokeai/backend/model_manager/util.py

@@ -4,13 +4,14 @@ Various utilities used by the model manager.
 """
 import json
 import warnings
-import torch
-import safetensors
 from pathlib import Path
 from typing import Optional, Union
+
+import safetensors
+import torch
 from diffusers import logging as diffusers_logging
-from transformers import logging as transformers_logging
 from picklescan.scanner import scan_file_path
+from transformers import logging as transformers_logging
 
 
 class SilenceWarnings(object):

invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py

@@ -261,7 +261,7 @@ class InvokeAICrossAttentionMixin:
         if q.shape[1] <= 4096:  # (512x512) max q.shape[1]: 4096
             return self.einsum_lowest_level(q, k, v, None, None, None)
         else:
-            slice_size = math.floor(2**30 / (q.shape[0] * q.shape[1]))
+            slice_size = math.floor(2 ** 30 / (q.shape[0] * q.shape[1]))
             return self.einsum_op_slice_dim1(q, k, v, slice_size)
 
     def einsum_op_mps_v2(self, q, k, v):

invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py

@@ -215,10 +215,7 @@ class InvokeAIDiffuserComponent:
                                 dim=0,
                             ),
                         }
-                    (
-                        encoder_hidden_states,
-                        encoder_attention_mask,
-                    ) = self._concat_conditionings_for_batch(
+                    (encoder_hidden_states, encoder_attention_mask,) = self._concat_conditionings_for_batch(
                         conditioning_data.unconditioned_embeddings.embeds,
                         conditioning_data.text_embeddings.embeds,
                     )
@@ -280,10 +277,7 @@ class InvokeAIDiffuserComponent:
         wants_cross_attention_control = len(cross_attention_control_types_to_do) > 0
 
         if wants_cross_attention_control:
-            (
-                unconditioned_next_x,
-                conditioned_next_x,
-            ) = self._apply_cross_attention_controlled_conditioning(
+            (unconditioned_next_x, conditioned_next_x,) = self._apply_cross_attention_controlled_conditioning(
                 sample,
                 timestep,
                 conditioning_data,
@@ -291,10 +285,7 @@ class InvokeAIDiffuserComponent:
                 **kwargs,
             )
         elif self.sequential_guidance:
-            (
-                unconditioned_next_x,
-                conditioned_next_x,
-            ) = self._apply_standard_conditioning_sequentially(
+            (unconditioned_next_x, conditioned_next_x,) = self._apply_standard_conditioning_sequentially(
                 sample,
                 timestep,
                 conditioning_data,
@@ -302,10 +293,7 @@ class InvokeAIDiffuserComponent:
             )
 
         else:
-            (
-                unconditioned_next_x,
-                conditioned_next_x,
-            ) = self._apply_standard_conditioning(
+            (unconditioned_next_x, conditioned_next_x,) = self._apply_standard_conditioning(
                 sample,
                 timestep,
                 conditioning_data,

invokeai/backend/training/textual_inversion_training.py

@@ -470,10 +470,7 @@ class TextualInversionDataset(Dataset):
 
         if self.center_crop:
             crop = min(img.shape[0], img.shape[1])
-            (
-                h,
-                w,
-            ) = (
+            (h, w,) = (
                 img.shape[0],
                 img.shape[1],
             )

invokeai/backend/util/__init__.py

@@ -11,12 +11,5 @@ from .devices import (  # noqa: F401
     normalize_device,
     torch_dtype,
 )
-from .util import (  # noqa: F401
-    ask_user,
-    download_with_resume,
-    instantiate_from_config,
-    url_attachment_name,
-    Chdir,
-)
-from .attention import auto_detect_slice_size  # noqa: F401
 from .logging import InvokeAILogger  # noqa: F401
+from .util import Chdir, ask_user, download_with_resume, instantiate_from_config, url_attachment_name  # noqa: F401

invokeai/backend/util/mps_fixes.py

@@ -203,7 +203,7 @@ class ChunkedSlicedAttnProcessor:
         if attn.upcast_attention:
             out_item_size = 4
 
-        chunk_size = 2**29
+        chunk_size = 2 ** 29
 
         out_size = query.shape[1] * key.shape[1] * out_item_size
         chunks_count = min(query.shape[1], math.ceil((out_size - 1) / chunk_size))

invokeai/backend/util/util.py

@@ -207,7 +207,7 @@ def parallel_data_prefetch(
         return gather_res
 
 
-def rand_perlin_2d(shape, res, device, fade=lambda t: 6 * t**5 - 15 * t**4 + 10 * t**3):
+def rand_perlin_2d(shape, res, device, fade=lambda t: 6 * t ** 5 - 15 * t ** 4 + 10 * t ** 3):
     delta = (res[0] / shape[0], res[1] / shape[1])
     d = (shape[0] // res[0], shape[1] // res[1])