make config migrator into an instance; refactor location of get_config()

invokeai/app/api_app.py

@@ -26,7 +26,7 @@ import invokeai.backend.util.hotfixes  # noqa: F401 (monkeypatching on import)
 import invokeai.frontend.web as web_dir
 from invokeai.app.api.no_cache_staticfiles import NoCacheStaticFiles
 from invokeai.app.invocations.model import ModelIdentifierField
-from invokeai.app.services.config.config_default import get_config
+from invokeai.app.services.config import get_config
 from invokeai.app.services.session_processor.session_processor_common import ProgressImage
 from invokeai.backend.util.devices import TorchDevice
 

invokeai/app/invocations/__init__.py

@@ -3,7 +3,7 @@ import sys
 from importlib.util import module_from_spec, spec_from_file_location
 from pathlib import Path
 
-from invokeai.app.services.config.config_default import get_config
+from invokeai.app.services.config import get_config
 
 custom_nodes_path = Path(get_config().custom_nodes_path)
 custom_nodes_path.mkdir(parents=True, exist_ok=True)

invokeai/app/invocations/baseinvocation.py

@@ -33,7 +33,7 @@ from invokeai.app.invocations.fields import (
     FieldKind,
     Input,
 )
-from invokeai.app.services.config.config_default import get_config
+from invokeai.app.services.config import get_config
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.metaenum import MetaEnum
 from invokeai.app.util.misc import uuid_string

invokeai/app/services/config/__init__.py

@@ -2,6 +2,7 @@
 
 from invokeai.app.services.config.config_common import PagingArgumentParser
 
-from .config_default import InvokeAIAppConfig, get_config
+from .config_default import InvokeAIAppConfig
+from .config_migrate import get_config
 
 __all__ = ["InvokeAIAppConfig", "get_config", "PagingArgumentParser"]

invokeai/app/services/config/config_default.py

@@ -3,11 +3,8 @@
 
 from __future__ import annotations
 
-import locale
 import os
 import re
-import shutil
-from functools import lru_cache
 from pathlib import Path
 from typing import Any, Literal, Optional
 
@@ -16,11 +13,7 @@ import yaml
 from pydantic import BaseModel, Field, PrivateAttr, field_validator
 from pydantic_settings import BaseSettings, PydanticBaseSettingsSource, SettingsConfigDict
 
-import invokeai.configs as model_configs
 from invokeai.backend.model_hash.model_hash import HASHING_ALGORITHMS
-from invokeai.frontend.cli.arg_parser import InvokeAIArgs
-
-from .config_migrate import ConfigMigrator
 
 INIT_FILE = Path("invokeai.yaml")
 DB_FILE = Path("invokeai.db")
@@ -348,162 +341,3 @@ class DefaultInvokeAIAppConfig(InvokeAIAppConfig):
         file_secret_settings: PydanticBaseSettingsSource,
     ) -> tuple[PydanticBaseSettingsSource, ...]:
         return (init_settings,)
-
-
-def load_and_migrate_config(config_path: Path) -> InvokeAIAppConfig:
-    """Load and migrate a config file to the latest version.
-
-    Args:
-        config_path: Path to the config file.
-
-    Returns:
-        An instance of `InvokeAIAppConfig` with the loaded and migrated settings.
-    """
-    assert config_path.suffix == ".yaml"
-    with open(config_path, "rt", encoding=locale.getpreferredencoding()) as file:
-        loaded_config_dict = yaml.safe_load(file)
-
-    assert isinstance(loaded_config_dict, dict)
-
-    shutil.copy(config_path, config_path.with_suffix(".yaml.bak"))
-    try:
-        # loaded_config_dict could be the wrong shape, but we will catch all exceptions below
-        migrated_config_dict = ConfigMigrator.migrate(loaded_config_dict)  # pyright: ignore [reportUnknownArgumentType]
-    except Exception as e:
-        shutil.copy(config_path.with_suffix(".yaml.bak"), config_path)
-        raise RuntimeError(f"Failed to load and migrate config file {config_path}: {e}") from e
-
-    # Attempt to load as a v4 config file
-    try:
-        config = InvokeAIAppConfig.model_validate(migrated_config_dict)
-        assert (
-            config.schema_version == CONFIG_SCHEMA_VERSION
-        ), f"Invalid schema version, expected {CONFIG_SCHEMA_VERSION} but got {config.schema_version}"
-        return config
-    except Exception as e:
-        raise RuntimeError(f"Failed to load config file {config_path}: {e}") from e
-
-
-@lru_cache(maxsize=1)
-def get_config() -> InvokeAIAppConfig:
-    """Get the global singleton app config.
-
-    When first called, this function:
-    - Creates a config object. `pydantic-settings` handles merging of settings from environment variables, but not the init file.
-    - Retrieves any provided CLI args from the InvokeAIArgs class. It does not _parse_ the CLI args; that is done in the main entrypoint.
-    - Sets the root dir, if provided via CLI args.
-    - Logs in to HF if there is no valid token already.
-    - Copies all legacy configs to the legacy conf dir (needed for conversion from ckpt to diffusers).
-    - Reads and merges in settings from the config file if it exists, else writes out a default config file.
-
-    On subsequent calls, the object is returned from the cache.
-    """
-    # This object includes environment variables, as parsed by pydantic-settings
-    config = InvokeAIAppConfig()
-
-    args = InvokeAIArgs.args
-
-    # This flag serves as a proxy for whether the config was retrieved in the context of the full application or not.
-    # If it is False, we should just return a default config and not set the root, log in to HF, etc.
-    if not InvokeAIArgs.did_parse:
-        return config
-
-    # Set CLI args
-    if root := getattr(args, "root", None):
-        config._root = Path(root)
-    if config_file := getattr(args, "config_file", None):
-        config._config_file = Path(config_file)
-
-    # Create the example config file, with some extra example values provided
-    example_config = DefaultInvokeAIAppConfig()
-    example_config.remote_api_tokens = [
-        URLRegexTokenPair(url_regex="cool-models.com", token="my_secret_token"),
-        URLRegexTokenPair(url_regex="nifty-models.com", token="some_other_token"),
-    ]
-    example_config.write_file(config.config_file_path.with_suffix(".example.yaml"), as_example=True)
-
-    # Copy all legacy configs - We know `__path__[0]` is correct here
-    configs_src = Path(model_configs.__path__[0])  # pyright: ignore [reportUnknownMemberType, reportUnknownArgumentType, reportAttributeAccessIssue]
-    shutil.copytree(configs_src, config.legacy_conf_path, dirs_exist_ok=True)
-
-    if config.config_file_path.exists():
-        config_from_file = load_and_migrate_config(config.config_file_path)
-        config_from_file.write_file(config.config_file_path)
-        # Clobbering here will overwrite any settings that were set via environment variables
-        config.update_config(config_from_file, clobber=False)
-    else:
-        # We should never write env vars to the config file
-        default_config = DefaultInvokeAIAppConfig()
-        default_config.write_file(config.config_file_path, as_example=False)
-
-    return config
-
-
-####################################################
-# VERSION MIGRATIONS
-####################################################
-
-
-@ConfigMigrator.register(from_version="3.0.0", to_version="4.0.0")
-def migrate_1(config_dict: dict[str, Any]) -> dict[str, Any]:
-    """Migrate a v3 config dictionary to a current config object.
-
-    Args:
-        config_dict: A dictionary of settings from a v3 config file.
-
-    Returns:
-        A dictionary of settings from a 4.0.0 config file.
-
-    """
-    parsed_config_dict: dict[str, Any] = {}
-    for _category_name, category_dict in config_dict["InvokeAI"].items():
-        for k, v in category_dict.items():
-            # `outdir` was renamed to `outputs_dir` in v4
-            if k == "outdir":
-                parsed_config_dict["outputs_dir"] = v
-            # `max_cache_size` was renamed to `ram` some time in v3, but both names were used
-            if k == "max_cache_size" and "ram" not in category_dict:
-                parsed_config_dict["ram"] = v
-            # `max_vram_cache_size` was renamed to `vram` some time in v3, but both names were used
-            if k == "max_vram_cache_size" and "vram" not in category_dict:
-                parsed_config_dict["vram"] = v
-            # autocast was removed in v4.0.1
-            if k == "precision" and v == "autocast":
-                parsed_config_dict["precision"] = "auto"
-            if k == "conf_path":
-                parsed_config_dict["legacy_models_yaml_path"] = v
-            if k == "legacy_conf_dir":
-                # The old default for this was "configs/stable-diffusion" ("configs\stable-diffusion" on Windows).
-                if v == "configs/stable-diffusion" or v == "configs\\stable-diffusion":
-                    # If if the incoming config has the default value, skip
-                    continue
-                elif Path(v).name == "stable-diffusion":
-                    # Else if the path ends in "stable-diffusion", we assume the parent is the new correct path.
-                    parsed_config_dict["legacy_conf_dir"] = str(Path(v).parent)
-                else:
-                    # Else we do not attempt to migrate this setting
-                    parsed_config_dict["legacy_conf_dir"] = v
-            elif k in InvokeAIAppConfig.model_fields:
-                # skip unknown fields
-                parsed_config_dict[k] = v
-    return parsed_config_dict
-
-
-@ConfigMigrator.register(from_version="4.0.0", to_version="4.0.1")
-def migrate_2(config_dict: dict[str, Any]) -> dict[str, Any]:
-    """Migrate v4.0.0 config dictionary to v4.0.1.
-
-    Args:
-        config_dict: A dictionary of settings from a v4.0.0 config file.
-
-    Returns:
-        A dictionary of settings from a v4.0.1 config file
-    """
-    parsed_config_dict: dict[str, Any] = {}
-    for k, v in config_dict.items():
-        # autocast was removed from precision in v4.0.1
-        if k == "precision" and v == "autocast":
-            parsed_config_dict["precision"] = "auto"
-        else:
-            parsed_config_dict[k] = v
-    return parsed_config_dict

invokeai/app/services/config/config_migrate.py

@@ -4,12 +4,22 @@
 Utility class for migrating among versions of the InvokeAI app config schema.
 """
 
+import locale
+import shutil
 from dataclasses import dataclass
-from typing import Any, Callable, List, TypeAlias
+from functools import lru_cache
+from pathlib import Path
+from typing import Callable, List, TypeAlias
 
+import yaml
 from packaging.version import Version
 
-AppConfigDict: TypeAlias = dict[str, Any]
+import invokeai.configs as model_configs
+from invokeai.frontend.cli.arg_parser import InvokeAIArgs
+
+from .config_default import CONFIG_SCHEMA_VERSION, DefaultInvokeAIAppConfig, InvokeAIAppConfig, URLRegexTokenPair
+from .migrations import AppConfigDict, Migrations, MigrationsBase
+
 MigrationFunction: TypeAlias = Callable[[AppConfigDict], AppConfigDict]
 
 
@@ -25,22 +35,23 @@ class MigrationEntry:
 class ConfigMigrator:
     """This class allows migrators to register their input and output versions."""
 
-    _migrations: List[MigrationEntry] = []
+    def __init__(self, migrations: type[MigrationsBase]) -> None:
+        self._migrations: List[MigrationEntry] = []
+        migrations.load(self)
 
-    @classmethod
     def register(
-        cls,
+        self,
         from_version: str,
         to_version: str,
     ) -> Callable[[MigrationFunction], MigrationFunction]:
         """Define a decorator which registers the migration between two versions."""
 
         def decorator(function: MigrationFunction) -> MigrationFunction:
-            if any(from_version == m.from_version for m in cls._migrations):
+            if any((from_version == m.from_version) or (to_version == m.to_version) for m in self._migrations):
                 raise ValueError(
                     f"function {function.__name__} is trying to register a migration for version {str(from_version)}, but this migration has already been registered."
                 )
-            cls._migrations.append(
+            self._migrations.append(
                 MigrationEntry(from_version=Version(from_version), to_version=Version(to_version), function=function)
             )
             return function
@@ -57,8 +68,7 @@ class ConfigMigrator:
                 )
             current_version = m.to_version
 
-    @classmethod
+    def run_migrations(self, config_dict: AppConfigDict) -> AppConfigDict:
-    def migrate(cls, config_dict: AppConfigDict) -> AppConfigDict:
         """
         Use the registered migration steps to bring config up to latest version.
 
@@ -72,8 +82,8 @@ class ConfigMigrator:
         """
         # Sort migrations by version number and raise a ValueError if
         # any version range overlaps are detected.
-        sorted_migrations = sorted(cls._migrations, key=lambda x: x.from_version)
+        sorted_migrations = sorted(self._migrations, key=lambda x: x.from_version)
-        cls._check_for_discontinuities(sorted_migrations)
+        self._check_for_discontinuities(sorted_migrations)
 
         if "InvokeAI" in config_dict:
             version = Version("3.0.0")
@@ -87,3 +97,92 @@ class ConfigMigrator:
 
         config_dict["schema_version"] = str(version)
         return config_dict
+
+
+@lru_cache(maxsize=1)
+def get_config() -> InvokeAIAppConfig:
+    """Get the global singleton app config.
+
+    When first called, this function:
+    - Creates a config object. `pydantic-settings` handles merging of settings from environment variables, but not the init file.
+    - Retrieves any provided CLI args from the InvokeAIArgs class. It does not _parse_ the CLI args; that is done in the main entrypoint.
+    - Sets the root dir, if provided via CLI args.
+    - Logs in to HF if there is no valid token already.
+    - Copies all legacy configs to the legacy conf dir (needed for conversion from ckpt to diffusers).
+    - Reads and merges in settings from the config file if it exists, else writes out a default config file.
+
+    On subsequent calls, the object is returned from the cache.
+    """
+    # This object includes environment variables, as parsed by pydantic-settings
+    config = InvokeAIAppConfig()
+
+    args = InvokeAIArgs.args
+
+    # This flag serves as a proxy for whether the config was retrieved in the context of the full application or not.
+    # If it is False, we should just return a default config and not set the root, log in to HF, etc.
+    if not InvokeAIArgs.did_parse:
+        return config
+
+    # Set CLI args
+    if root := getattr(args, "root", None):
+        config._root = Path(root)
+    if config_file := getattr(args, "config_file", None):
+        config._config_file = Path(config_file)
+
+    # Create the example config file, with some extra example values provided
+    example_config = DefaultInvokeAIAppConfig()
+    example_config.remote_api_tokens = [
+        URLRegexTokenPair(url_regex="cool-models.com", token="my_secret_token"),
+        URLRegexTokenPair(url_regex="nifty-models.com", token="some_other_token"),
+    ]
+    example_config.write_file(config.config_file_path.with_suffix(".example.yaml"), as_example=True)
+
+    # Copy all legacy configs - We know `__path__[0]` is correct here
+    configs_src = Path(model_configs.__path__[0])  # pyright: ignore [reportUnknownMemberType, reportUnknownArgumentType, reportAttributeAccessIssue]
+    shutil.copytree(configs_src, config.legacy_conf_path, dirs_exist_ok=True)
+
+    if config.config_file_path.exists():
+        config_from_file = load_and_migrate_config(config.config_file_path)
+        config_from_file.write_file(config.config_file_path)
+        # Clobbering here will overwrite any settings that were set via environment variables
+        config.update_config(config_from_file, clobber=False)
+    else:
+        # We should never write env vars to the config file
+        default_config = DefaultInvokeAIAppConfig()
+        default_config.write_file(config.config_file_path, as_example=False)
+
+    return config
+
+
+def load_and_migrate_config(config_path: Path) -> InvokeAIAppConfig:
+    """Load and migrate a config file to the latest version.
+
+    Args:
+        config_path: Path to the config file.
+
+    Returns:
+        An instance of `InvokeAIAppConfig` with the loaded and migrated settings.
+    """
+    assert config_path.suffix == ".yaml"
+    with open(config_path, "rt", encoding=locale.getpreferredencoding()) as file:
+        loaded_config_dict = yaml.safe_load(file)
+
+    assert isinstance(loaded_config_dict, dict)
+
+    shutil.copy(config_path, config_path.with_suffix(".yaml.bak"))
+    try:
+        migrator = ConfigMigrator(Migrations)
+        migrated_config_dict = migrator.run_migrations(loaded_config_dict)  # pyright: ignore [reportUnknownArgumentType]
+    except Exception as e:
+        shutil.copy(config_path.with_suffix(".yaml.bak"), config_path)
+        raise RuntimeError(f"Failed to load and migrate config file {config_path}: {e}") from e
+
+    # Attempt to load as a v4 config file
+    try:
+        config = InvokeAIAppConfig.model_validate(migrated_config_dict)
+        assert (
+            config.schema_version == CONFIG_SCHEMA_VERSION
+        ), f"Invalid schema version, expected {CONFIG_SCHEMA_VERSION} but got {config.schema_version}"
+        return config
+    except Exception as e:
+        raise RuntimeError(f"Failed to load config file {config_path}: {e}") from e

invokeai/app/services/config/migrations.py

@@ -0,0 +1,108 @@
+# Copyright 2024 Lincoln D. Stein and the InvokeAI Development Team
+
+"""
+Schema migrations to perform on an InvokeAIAppConfig object.
+
+The Migrations class defined in this module defines a series of
+schema version migration steps for the InvokeAIConfig object.
+
+To define a new migration, add a migration function to
+Migrations.load_migrations() following the existing examples.
+"""
+
+from abc import ABC, abstractmethod
+from pathlib import Path
+from typing import TYPE_CHECKING, Any, TypeAlias
+
+from .config_default import InvokeAIAppConfig
+
+if TYPE_CHECKING:
+    from .config_migrate import ConfigMigrator
+
+AppConfigDict: TypeAlias = dict[str, Any]
+
+
+class MigrationsBase(ABC):
+    """Define the config file migration steps to apply, abstract base class."""
+
+    @classmethod
+    @abstractmethod
+    def load(cls, migrator: "ConfigMigrator") -> None:
+        """Use the provided migrator to register the configuration migrations to be run."""
+
+
+class Migrations(MigrationsBase):
+    """Configuration migration steps to apply."""
+
+    @classmethod
+    def load(cls, migrator: "ConfigMigrator") -> None:
+        """Define migrations to perform."""
+
+        ##################
+        # 3.0.0 -> 4.0.0 #
+        ##################
+        @migrator.register(from_version="3.0.0", to_version="4.0.0")
+        def migrate_1(config_dict: dict[str, Any]) -> dict[str, Any]:
+            """Migrate a v3 config dictionary to a current config object.
+
+            Args:
+                config_dict: A dictionary of settings from a v3 config file.
+
+            Returns:
+                A dictionary of settings from a 4.0.0 config file.
+
+            """
+            parsed_config_dict: dict[str, Any] = {}
+            for _category_name, category_dict in config_dict["InvokeAI"].items():
+                for k, v in category_dict.items():
+                    # `outdir` was renamed to `outputs_dir` in v4
+                    if k == "outdir":
+                        parsed_config_dict["outputs_dir"] = v
+                    # `max_cache_size` was renamed to `ram` some time in v3, but both names were used
+                    if k == "max_cache_size" and "ram" not in category_dict:
+                        parsed_config_dict["ram"] = v
+                    # `max_vram_cache_size` was renamed to `vram` some time in v3, but both names were used
+                    if k == "max_vram_cache_size" and "vram" not in category_dict:
+                        parsed_config_dict["vram"] = v
+                    # autocast was removed in v4.0.1
+                    if k == "precision" and v == "autocast":
+                        parsed_config_dict["precision"] = "auto"
+                    if k == "conf_path":
+                        parsed_config_dict["legacy_models_yaml_path"] = v
+                    if k == "legacy_conf_dir":
+                        # The old default for this was "configs/stable-diffusion" ("configs\stable-diffusion" on Windows).
+                        if v == "configs/stable-diffusion" or v == "configs\\stable-diffusion":
+                            # If if the incoming config has the default value, skip
+                            continue
+                        elif Path(v).name == "stable-diffusion":
+                            # Else if the path ends in "stable-diffusion", we assume the parent is the new correct path.
+                            parsed_config_dict["legacy_conf_dir"] = str(Path(v).parent)
+                        else:
+                            # Else we do not attempt to migrate this setting
+                            parsed_config_dict["legacy_conf_dir"] = v
+                    elif k in InvokeAIAppConfig.model_fields:
+                        # skip unknown fields
+                        parsed_config_dict[k] = v
+            return parsed_config_dict
+
+        ##################
+        # 4.0.0 -> 4.0.1 #
+        ##################
+        @migrator.register(from_version="4.0.0", to_version="4.0.1")
+        def migrate_2(config_dict: dict[str, Any]) -> dict[str, Any]:
+            """Migrate v4.0.0 config dictionary to v4.0.1.
+
+            Args:
+                config_dict: A dictionary of settings from a v4.0.0 config file.
+
+            Returns:
+                A dictionary of settings from a v4.0.1 config file
+            """
+            parsed_config_dict: dict[str, Any] = {}
+            for k, v in config_dict.items():
+                # autocast was removed from precision in v4.0.1
+                if k == "precision" and v == "autocast":
+                    parsed_config_dict["precision"] = "auto"
+                else:
+                    parsed_config_dict[k] = v
+            return parsed_config_dict

invokeai/app/services/shared/invocation_context.py

@@ -9,7 +9,7 @@ from torch import Tensor
 from invokeai.app.invocations.constants import IMAGE_MODES
 from invokeai.app.invocations.fields import MetadataField, WithBoard, WithMetadata
 from invokeai.app.services.boards.boards_common import BoardDTO
-from invokeai.app.services.config.config_default import InvokeAIAppConfig
+from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 from invokeai.app.services.images.images_common import ImageDTO
 from invokeai.app.services.invocation_services import InvocationServices

invokeai/app/services/shared/sqlite/sqlite_util.py

@@ -1,6 +1,6 @@
 from logging import Logger
 
-from invokeai.app.services.config.config_default import InvokeAIAppConfig
+from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.app.services.image_files.image_files_base import ImageFileStorageBase
 from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_1 import build_migration_1

invokeai/app/services/shared/sqlite_migrator/migrations/migration_8.py

@@ -1,7 +1,7 @@
 import sqlite3
 from pathlib import Path
 
-from invokeai.app.services.config.config_default import InvokeAIAppConfig
+from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_common import Migration
 
 

invokeai/backend/image_util/depth_anything/__init__.py

@@ -9,7 +9,7 @@ from einops import repeat
 from PIL import Image
 from torchvision.transforms import Compose
 
-from invokeai.app.services.config.config_default import get_config
+from invokeai.app.services.config import get_config
 from invokeai.app.util.download_with_progress import download_with_progress_bar
 from invokeai.backend.image_util.depth_anything.model.dpt import DPT_DINOv2
 from invokeai.backend.image_util.depth_anything.utilities.util import NormalizeImage, PrepareForNet, Resize

invokeai/backend/image_util/dw_openpose/wholebody.py

@@ -5,7 +5,7 @@
 import numpy as np
 import onnxruntime as ort
 
-from invokeai.app.services.config.config_default import get_config
+from invokeai.app.services.config import get_config
 from invokeai.app.util.download_with_progress import download_with_progress_bar
 from invokeai.backend.util.devices import TorchDevice
 

invokeai/backend/image_util/infill_methods/lama.py

@@ -6,7 +6,7 @@ import torch
 from PIL import Image
 
 import invokeai.backend.util.logging as logger
-from invokeai.app.services.config.config_default import get_config
+from invokeai.app.services.config import get_config
 from invokeai.app.util.download_with_progress import download_with_progress_bar
 from invokeai.backend.util.devices import TorchDevice
 

invokeai/backend/image_util/infill_methods/patchmatch.py

@@ -9,7 +9,7 @@ import numpy as np
 from PIL import Image
 
 import invokeai.backend.util.logging as logger
-from invokeai.app.services.config.config_default import get_config
+from invokeai.app.services.config import get_config
 
 
 class PatchMatch:

invokeai/backend/image_util/invisible_watermark.py

@@ -10,7 +10,7 @@ from imwatermark import WatermarkEncoder
 from PIL import Image
 
 import invokeai.backend.util.logging as logger
-from invokeai.app.services.config.config_default import get_config
+from invokeai.app.services.config import get_config
 
 config = get_config()
 

invokeai/backend/image_util/safety_checker.py

@@ -12,7 +12,7 @@ from PIL import Image
 from transformers import AutoFeatureExtractor
 
 import invokeai.backend.util.logging as logger
-from invokeai.app.services.config.config_default import get_config
+from invokeai.app.services.config import get_config
 from invokeai.backend.util.devices import TorchDevice
 from invokeai.backend.util.silence_warnings import SilenceWarnings
 

invokeai/backend/stable_diffusion/diffusers_pipeline.py

@@ -20,7 +20,7 @@ from diffusers.utils.import_utils import is_xformers_available
 from pydantic import Field
 from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
 
-from invokeai.app.services.config.config_default import get_config
+from invokeai.app.services.config import get_config
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import IPAdapterData, TextConditioningData
 from invokeai.backend.stable_diffusion.diffusion.shared_invokeai_diffusion import InvokeAIDiffuserComponent
 from invokeai.backend.stable_diffusion.diffusion.unet_attention_patcher import UNetAttentionPatcher, UNetIPAdapterData

invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py

@@ -6,7 +6,7 @@ from typing import Any, Callable, Optional, Union
 import torch
 from typing_extensions import TypeAlias
 
-from invokeai.app.services.config.config_default import get_config
+from invokeai.app.services.config import get_config
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     IPAdapterData,
     Range,

invokeai/backend/util/devices.py

@@ -3,7 +3,7 @@ from typing import Dict, Literal, Optional, Union
 import torch
 from deprecated import deprecated
 
-from invokeai.app.services.config.config_default import get_config
+from invokeai.app.services.config import get_config
 
 # legacy APIs
 TorchPrecisionNames = Literal["float32", "float16", "bfloat16"]

invokeai/backend/util/logging.py

@@ -180,8 +180,7 @@ import urllib.parse
 from pathlib import Path
 from typing import Any, Dict, Optional
 
-from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.config import InvokeAIAppConfig, get_config
-from invokeai.app.services.config.config_default import get_config
 
 try:
     import syslog

tests/test_config.py

@@ -12,10 +12,9 @@ from invokeai.app.services.config.config_default import (
     CONFIG_SCHEMA_VERSION,
     DefaultInvokeAIAppConfig,
     InvokeAIAppConfig,
-    get_config,
-    load_and_migrate_config,
 )
-from invokeai.app.services.config.config_migrate import ConfigMigrator
+from invokeai.app.services.config.config_migrate import ConfigMigrator, get_config, load_and_migrate_config
+from invokeai.app.services.config.migrations import Migrations, MigrationsBase
 from invokeai.app.services.shared.graph import Graph
 from invokeai.frontend.cli.arg_parser import InvokeAIArgs
 
@@ -72,6 +71,68 @@ i like turtles
 """
 
 
+class GoodMigrations(MigrationsBase):
+    @classmethod
+    def load(cls, migrator: ConfigMigrator) -> None:
+        """Define migrations to perform."""
+
+        @migrator.register(from_version="3.0.0", to_version="10.0.0")
+        def migration_1(config_dict: dict[str, Any]) -> dict[str, Any]:
+            return config_dict
+
+        @migrator.register(from_version="10.0.0", to_version="10.0.1")
+        def migration_2(config_dict: dict[str, Any]) -> dict[str, Any]:
+            return config_dict
+
+        @migrator.register(from_version="10.0.1", to_version="10.0.2")
+        def migration_3(config_dict: dict[str, Any]) -> dict[str, Any]:
+            return config_dict
+
+
+class BadMigrations1(MigrationsBase):
+    """This one fails because there is no path from 10.0.1 to 10.0.2"""
+
+    @classmethod
+    def load(cls, migrator: ConfigMigrator) -> None:
+        """Define migrations to perform."""
+
+        @migrator.register(from_version="3.0.0", to_version="10.0.0")
+        def migration_1(config_dict: dict[str, Any]) -> dict[str, Any]:
+            return config_dict
+
+        @migrator.register(from_version="10.0.0", to_version="10.0.1")
+        def migration_2(config_dict: dict[str, Any]) -> dict[str, Any]:
+            return config_dict
+
+        @migrator.register(from_version="10.0.2", to_version="10.0.3")
+        def migration_3(config_dict: dict[str, Any]) -> dict[str, Any]:
+            return config_dict
+
+
+class BadMigrations2(MigrationsBase):
+    """This one fails because the path to 10.0.2 is registered twice"""
+
+    @classmethod
+    def load(cls, migrator: ConfigMigrator) -> None:
+        """Define migrations to perform."""
+
+        @migrator.register(from_version="3.0.0", to_version="10.0.0")
+        def migration_1(config_dict: dict[str, Any]) -> dict[str, Any]:
+            return config_dict
+
+        @migrator.register(from_version="10.0.0", to_version="10.0.1")
+        def migration_2(config_dict: dict[str, Any]) -> dict[str, Any]:
+            return config_dict
+
+        @migrator.register(from_version="10.0.1", to_version="10.0.2")
+        def migration_3(config_dict: dict[str, Any]) -> dict[str, Any]:
+            return config_dict
+
+        @migrator.register(from_version="10.0.0", to_version="10.0.2")
+        def migration_4(config_dict: dict[str, Any]) -> dict[str, Any]:
+            return config_dict
+
+
 @pytest.fixture
 def patch_rootdir(tmp_path: Path, monkeypatch: Any) -> None:
     """This may be overkill since the current tests don't need the root dir to exist"""
@@ -291,33 +352,26 @@ def test_get_config_writing(patch_rootdir: None, monkeypatch: pytest.MonkeyPatch
 
 
 def test_migration_check() -> None:
-    new_config = ConfigMigrator.migrate({"schema_version": "4.0.0"})
+    # Test the default set of migrations
+    migrator = ConfigMigrator(Migrations)
+    new_config = migrator.run_migrations({"schema_version": "4.0.0"})
     assert new_config is not None
     assert new_config["schema_version"] == CONFIG_SCHEMA_VERSION
 
-    # Does this execute at compile time or run time?
+    # Test a custom set of migrations
-    @ConfigMigrator.register(from_version=CONFIG_SCHEMA_VERSION, to_version=CONFIG_SCHEMA_VERSION + ".1")
+    migrator = ConfigMigrator(GoodMigrations)
-    def ok_migration(config_dict: dict[str, Any]) -> dict[str, Any]:
+    new_config = migrator.run_migrations({"schema_version": "10.0.0"})
-        return config_dict
+    assert new_config["schema_version"] == "10.0.2"
 
-    new_config = ConfigMigrator.migrate({"schema_version": "4.0.0"})
+    # Test a migration that should fail validation
-    assert new_config["schema_version"] == CONFIG_SCHEMA_VERSION + ".1"
+    migrator = ConfigMigrator(BadMigrations1)
-
-    @ConfigMigrator.register(from_version=CONFIG_SCHEMA_VERSION + ".2", to_version=CONFIG_SCHEMA_VERSION + ".3")
-    def bad_migration(config_dict: dict[str, Any]) -> dict[str, Any]:
-        return config_dict
-
-    # Because there is no version for "*.1" => "*.2", this should fail.
     with pytest.raises(ValueError):
-        ConfigMigrator.migrate({"schema_version": "4.0.0"})
+        new_config = migrator.run_migrations({"schema_version": "10.0.0"})
 
-    @ConfigMigrator.register(from_version=CONFIG_SCHEMA_VERSION + ".1", to_version=CONFIG_SCHEMA_VERSION + ".2")
+    # Test another bad migration
-    def good_migration(config_dict: dict[str, Any]) -> dict[str, Any]:
+    migrator = ConfigMigrator(BadMigrations2)
-        return config_dict
+    with pytest.raises(ValueError):
-
+        new_config = migrator.run_migrations({"schema_version": "10.0.0"})
-    # should work now, because there is a continuous path to *.3
-    new_config = ConfigMigrator.migrate(new_config)
-    assert new_config["schema_version"] == CONFIG_SCHEMA_VERSION + ".3"
 
 
 @contextmanager