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Merge branch 'main' into refactor/model-manager-3

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This commit is contained in:
Lincoln Stein
2023-11-27 22:15:51 -05:00
committed by GitHub
parent a79e814c8d d971c5fa64
commit ecd3dcd5df
8 changed files with 142 additions and 163 deletions
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23
invokeai/app/api_app.py
View File

@@ -1,14 +1,20 @@
import sys
from typing import Any
from fastapi.responses import HTMLResponse
from .services.config import InvokeAIAppConfig
# parse_args() must be called before any other imports. if it is not called first, consumers of the config
# which are imported/used before parse_args() is called will get the default config values instead of the
# values from the command line or config file.
from invokeai.version.invokeai_version import __version__
from .services.config import InvokeAIAppConfig
app_config = InvokeAIAppConfig.get_config()
app_config.parse_args()
if app_config.version:
print(f"InvokeAI version {__version__}")
sys.exit(0)
if True: # hack to make flake8 happy with imports coming after setting up the config
import asyncio
@@ -34,7 +40,6 @@ if True: # hack to make flake8 happy with imports coming after setting up the c
# noinspection PyUnresolvedReferences
import invokeai.backend.util.hotfixes # noqa: F401 (monkeypatching on import)
import invokeai.frontend.web as web_dir
from invokeai.version.invokeai_version import __version__
from ..backend.util.logging import InvokeAILogger
from .api.dependencies import ApiDependencies
@@ -51,7 +56,12 @@ if True: # hack to make flake8 happy with imports coming after setting up the c
workflows,
)
from .api.sockets import SocketIO
from .invocations.baseinvocation import BaseInvocation, UIConfigBase, _InputField, _OutputField
from .invocations.baseinvocation import (
BaseInvocation,
UIConfigBase,
_InputField,
_OutputField,
)
if is_mps_available():
import invokeai.backend.util.mps_fixes # noqa: F401 (monkeypatching on import)
@@ -273,7 +283,4 @@ def invoke_api() -> None:
if __name__ == "__main__":
if app_config.version:
print(f"InvokeAI version {__version__}")
else:
invoke_api()
invoke_api()

2
invokeai/app/invocations/__init__.py
View File

@@ -5,7 +5,7 @@ from pathlib import Path
from invokeai.app.services.config.config_default import InvokeAIAppConfig
custom_nodes_path = Path(InvokeAIAppConfig.get_config().custom_nodes_path.absolute())
custom_nodes_path = Path(InvokeAIAppConfig.get_config().custom_nodes_path.resolve())
custom_nodes_path.mkdir(parents=True, exist_ok=True)
custom_nodes_init_path = str(custom_nodes_path / "__init__.py")

24
invokeai/app/services/config/config_base.py
View File

@@ -15,7 +15,7 @@ import os
import sys
from argparse import ArgumentParser
from pathlib import Path
from typing import ClassVar, Dict, List, Literal, Optional, Union, get_args, get_origin, get_type_hints
from typing import Any, ClassVar, Dict, List, Literal, Optional, Union, get_args, get_origin, get_type_hints
from omegaconf import DictConfig, ListConfig, OmegaConf
from pydantic_settings import BaseSettings, SettingsConfigDict
@@ -24,10 +24,7 @@ from invokeai.app.services.config.config_common import PagingArgumentParser, int
class InvokeAISettings(BaseSettings):
"""
Runtime configuration settings in which default values are
read from an omegaconf .yaml file.
"""
"""Runtime configuration settings in which default values are read from an omegaconf .yaml file."""
initconf: ClassVar[Optional[DictConfig]] = None
argparse_groups: ClassVar[Dict] = {}
@@ -35,6 +32,7 @@ class InvokeAISettings(BaseSettings):
model_config = SettingsConfigDict(env_file_encoding="utf-8", arbitrary_types_allowed=True, case_sensitive=True)
def parse_args(self, argv: Optional[list] = sys.argv[1:]):
"""Call to parse command-line arguments."""
parser = self.get_parser()
opt, unknown_opts = parser.parse_known_args(argv)
if len(unknown_opts) > 0:
@@ -49,20 +47,19 @@ class InvokeAISettings(BaseSettings):
setattr(self, name, value)
def to_yaml(self) -> str:
"""
Return a YAML string representing our settings. This can be used
as the contents of `invokeai.yaml` to restore settings later.
"""
"""Return a YAML string representing our settings. This can be used as the contents of `invokeai.yaml` to restore settings later."""
cls = self.__class__
type = get_args(get_type_hints(cls)["type"])[0]
field_dict = {type: {}}
field_dict: Dict[str, Dict[str, Any]] = {type: {}}
for name, field in self.model_fields.items():
if name in cls._excluded_from_yaml():
continue
assert isinstance(field.json_schema_extra, dict)
category = (
field.json_schema_extra.get("category", "Uncategorized") if field.json_schema_extra else "Uncategorized"
)
value = getattr(self, name)
assert isinstance(category, str)
if category not in field_dict[type]:
field_dict[type][category] = {}
# keep paths as strings to make it easier to read
@@ -72,6 +69,7 @@ class InvokeAISettings(BaseSettings):
@classmethod
def add_parser_arguments(cls, parser):
"""Dynamically create arguments for a settings parser."""
if "type" in get_type_hints(cls):
settings_stanza = get_args(get_type_hints(cls)["type"])[0]
else:
@@ -116,6 +114,7 @@ class InvokeAISettings(BaseSettings):
@classmethod
def cmd_name(cls, command_field: str = "type") -> str:
"""Return the category of a setting."""
hints = get_type_hints(cls)
if command_field in hints:
return get_args(hints[command_field])[0]
@@ -124,6 +123,7 @@ class InvokeAISettings(BaseSettings):
@classmethod
def get_parser(cls) -> ArgumentParser:
"""Get the command-line parser for a setting."""
parser = PagingArgumentParser(
prog=cls.cmd_name(),
description=cls.__doc__,
@@ -152,10 +152,14 @@ class InvokeAISettings(BaseSettings):
"free_gpu_mem",
"xformers_enabled",
"tiled_decode",
"lora_dir",
"embedding_dir",
"controlnet_dir",
]
@classmethod
def add_field_argument(cls, command_parser, name: str, field, default_override=None):
"""Add the argparse arguments for a setting parser."""
field_type = get_type_hints(cls).get(name)
default = (
default_override

141
invokeai/app/services/config/config_default.py
View File

@@ -177,6 +177,7 @@ from typing import Any, ClassVar, Dict, List, Literal, Optional, Union, get_type
from omegaconf import DictConfig, OmegaConf
from pydantic import Field, TypeAdapter
from pydantic.config import JsonDict
from pydantic_settings import SettingsConfigDict
from .config_base import InvokeAISettings
@@ -188,28 +189,24 @@ DEFAULT_MAX_VRAM = 0.5
class Categories(object):
WebServer = {"category": "Web Server"}
Features = {"category": "Features"}
Paths = {"category": "Paths"}
Logging = {"category": "Logging"}
Development = {"category": "Development"}
Other = {"category": "Other"}
ModelCache = {"category": "Model Cache"}
Device = {"category": "Device"}
Generation = {"category": "Generation"}
Queue = {"category": "Queue"}
Nodes = {"category": "Nodes"}
MemoryPerformance = {"category": "Memory/Performance"}
"""Category headers for configuration variable groups."""
WebServer: JsonDict = {"category": "Web Server"}
Features: JsonDict = {"category": "Features"}
Paths: JsonDict = {"category": "Paths"}
Logging: JsonDict = {"category": "Logging"}
Development: JsonDict = {"category": "Development"}
Other: JsonDict = {"category": "Other"}
ModelCache: JsonDict = {"category": "Model Cache"}
Device: JsonDict = {"category": "Device"}
Generation: JsonDict = {"category": "Generation"}
Queue: JsonDict = {"category": "Queue"}
Nodes: JsonDict = {"category": "Nodes"}
MemoryPerformance: JsonDict = {"category": "Memory/Performance"}
class InvokeAIAppConfig(InvokeAISettings):
"""
Generate images using Stable Diffusion. Use "invokeai" to launch
the command-line client (recommended for experts only), or
"invokeai-web" to launch the web server. Global options
can be changed by editing the file "INVOKEAI_ROOT/invokeai.yaml" or by
setting environment variables INVOKEAI_<setting>.
"""
"""Configuration object for InvokeAI App."""
singleton_config: ClassVar[Optional[InvokeAIAppConfig]] = None
singleton_init: ClassVar[Optional[Dict]] = None
@@ -234,15 +231,12 @@ class InvokeAIAppConfig(InvokeAISettings):
# PATHS
root : Optional[Path] = Field(default=None, description='InvokeAI runtime root directory', json_schema_extra=Categories.Paths)
autoimport_dir : Optional[Path] = Field(default=Path('autoimport'), description='Path to a directory of models files to be imported on startup.', json_schema_extra=Categories.Paths)
lora_dir : Optional[Path] = Field(default=None, description='Path to a directory of LoRA/LyCORIS models to be imported on startup.', json_schema_extra=Categories.Paths)
embedding_dir : Optional[Path] = Field(default=None, description='Path to a directory of Textual Inversion embeddings to be imported on startup.', json_schema_extra=Categories.Paths)
controlnet_dir : Optional[Path] = Field(default=None, description='Path to a directory of ControlNet embeddings to be imported on startup.', json_schema_extra=Categories.Paths)
conf_path : Optional[Path] = Field(default=Path('configs/models.yaml'), description='Path to models definition file', json_schema_extra=Categories.Paths)
models_dir : Optional[Path] = Field(default=Path('models'), description='Path to the models directory', json_schema_extra=Categories.Paths)
legacy_conf_dir : Optional[Path] = Field(default=Path('configs/stable-diffusion'), description='Path to directory of legacy checkpoint config files', json_schema_extra=Categories.Paths)
db_dir : Optional[Path] = Field(default=Path('databases'), description='Path to InvokeAI databases directory', json_schema_extra=Categories.Paths)
outdir : Optional[Path] = Field(default=Path('outputs'), description='Default folder for output images', json_schema_extra=Categories.Paths)
autoimport_dir : Path = Field(default=Path('autoimport'), description='Path to a directory of models files to be imported on startup.', json_schema_extra=Categories.Paths)
conf_path : Path = Field(default=Path('configs/models.yaml'), description='Path to models definition file', json_schema_extra=Categories.Paths)
models_dir : Path = Field(default=Path('models'), description='Path to the models directory', json_schema_extra=Categories.Paths)
legacy_conf_dir : Path = Field(default=Path('configs/stable-diffusion'), description='Path to directory of legacy checkpoint config files', json_schema_extra=Categories.Paths)
db_dir : Path = Field(default=Path('databases'), description='Path to InvokeAI databases directory', json_schema_extra=Categories.Paths)
outdir : Path = Field(default=Path('outputs'), description='Default folder for output images', json_schema_extra=Categories.Paths)
use_memory_db : bool = Field(default=False, description='Use in-memory database for storing image metadata', json_schema_extra=Categories.Paths)
custom_nodes_dir : Path = Field(default=Path('nodes'), description='Path to directory for custom nodes', json_schema_extra=Categories.Paths)
from_file : Optional[Path] = Field(default=None, description='Take command input from the indicated file (command-line client only)', json_schema_extra=Categories.Paths)
@@ -285,11 +279,15 @@ class InvokeAIAppConfig(InvokeAISettings):
# DEPRECATED FIELDS - STILL HERE IN ORDER TO OBTAN VALUES FROM PRE-3.1 CONFIG FILES
always_use_cpu : bool = Field(default=False, description="If true, use the CPU for rendering even if a GPU is available.", json_schema_extra=Categories.MemoryPerformance)
free_gpu_mem : Optional[bool] = Field(default=None, description="If true, purge model from GPU after each generation.", json_schema_extra=Categories.MemoryPerformance)
max_cache_size : Optional[float] = Field(default=None, gt=0, description="Maximum memory amount used by model cache for rapid switching", json_schema_extra=Categories.MemoryPerformance)
max_vram_cache_size : Optional[float] = Field(default=None, ge=0, description="Amount of VRAM reserved for model storage", json_schema_extra=Categories.MemoryPerformance)
xformers_enabled : bool = Field(default=True, description="Enable/disable memory-efficient attention", json_schema_extra=Categories.MemoryPerformance)
tiled_decode : bool = Field(default=False, description="Whether to enable tiled VAE decode (reduces memory consumption with some performance penalty)", json_schema_extra=Categories.MemoryPerformance)
lora_dir : Optional[Path] = Field(default=None, description='Path to a directory of LoRA/LyCORIS models to be imported on startup.', json_schema_extra=Categories.Paths)
embedding_dir : Optional[Path] = Field(default=None, description='Path to a directory of Textual Inversion embeddings to be imported on startup.', json_schema_extra=Categories.Paths)
controlnet_dir : Optional[Path] = Field(default=None, description='Path to a directory of ControlNet embeddings to be imported on startup.', json_schema_extra=Categories.Paths)
# this is not referred to in the source code and can be removed entirely
#free_gpu_mem : Optional[bool] = Field(default=None, description="If true, purge model from GPU after each generation.", json_schema_extra=Categories.MemoryPerformance)
# See InvokeAIAppConfig subclass below for CACHE and DEVICE categories
# fmt: on
@@ -303,8 +301,8 @@ class InvokeAIAppConfig(InvokeAISettings):
clobber=False,
):
"""
Update settings with contents of init file, environment, and
command-line settings.
Update settings with contents of init file, environment, and command-line settings.
:param conf: alternate Omegaconf dictionary object
:param argv: aternate sys.argv list
:param clobber: ovewrite any initialization parameters passed during initialization
@@ -349,9 +347,7 @@ class InvokeAIAppConfig(InvokeAISettings):
@property
def root_path(self) -> Path:
"""
Path to the runtime root directory
"""
"""Path to the runtime root directory."""
if self.root:
root = Path(self.root).expanduser().absolute()
else:
@@ -361,9 +357,7 @@ class InvokeAIAppConfig(InvokeAISettings):
@property
def root_dir(self) -> Path:
"""
Alias for above.
"""
"""Alias for above."""
return self.root_path
def _resolve(self, partial_path: Path) -> Path:
@@ -371,108 +365,95 @@ class InvokeAIAppConfig(InvokeAISettings):
@property
def init_file_path(self) -> Path:
"""
Path to invokeai.yaml
"""
return self._resolve(INIT_FILE)
"""Path to invokeai.yaml."""
resolved_path = self._resolve(INIT_FILE)
assert resolved_path is not None
return resolved_path
@property
def output_path(self) -> Path:
"""
Path to defaults outputs directory.
"""
def output_path(self) -> Optional[Path]:
"""Path to defaults outputs directory."""
return self._resolve(self.outdir)
@property
def db_path(self) -> Path:
"""
Path to the invokeai.db file.
"""
return self._resolve(self.db_dir) / DB_FILE
"""Path to the invokeai.db file."""
db_dir = self._resolve(self.db_dir)
assert db_dir is not None
return db_dir / DB_FILE
@property
def model_conf_path(self) -> Path:
"""
Path to models configuration file.
"""
def model_conf_path(self) -> Optional[Path]:
"""Path to models configuration file."""
return self._resolve(self.conf_path)
@property
def legacy_conf_path(self) -> Path:
"""
Path to directory of legacy configuration files (e.g. v1-inference.yaml)
"""
def legacy_conf_path(self) -> Optional[Path]:
"""Path to directory of legacy configuration files (e.g. v1-inference.yaml)."""
return self._resolve(self.legacy_conf_dir)
@property
def models_path(self) -> Path:
"""
Path to the models directory
"""
def models_path(self) -> Optional[Path]:
"""Path to the models directory."""
return self._resolve(self.models_dir)
@property
def custom_nodes_path(self) -> Path:
"""
Path to the custom nodes directory
"""
return self._resolve(self.custom_nodes_dir)
"""Path to the custom nodes directory."""
custom_nodes_path = self._resolve(self.custom_nodes_dir)
assert custom_nodes_path is not None
return custom_nodes_path
# the following methods support legacy calls leftover from the Globals era
@property
def full_precision(self) -> bool:
"""Return true if precision set to float32"""
"""Return true if precision set to float32."""
return self.precision == "float32"
@property
def try_patchmatch(self) -> bool:
"""Return true if patchmatch true"""
"""Return true if patchmatch true."""
return self.patchmatch
@property
def nsfw_checker(self) -> bool:
"""NSFW node is always active and disabled from Web UIe"""
"""Return value for NSFW checker. The NSFW node is always active and disabled from Web UI."""
return True
@property
def invisible_watermark(self) -> bool:
"""invisible watermark node is always active and disabled from Web UIe"""
"""Return value of invisible watermark. It is always active and disabled from Web UI."""
return True
@property
def ram_cache_size(self) -> Union[Literal["auto"], float]:
"""Return the ram cache size using the legacy or modern setting."""
return self.max_cache_size or self.ram
@property
def vram_cache_size(self) -> Union[Literal["auto"], float]:
"""Return the vram cache size using the legacy or modern setting."""
return self.max_vram_cache_size or self.vram
@property
def use_cpu(self) -> bool:
"""Return true if the device is set to CPU or the always_use_cpu flag is set."""
return self.always_use_cpu or self.device == "cpu"
@property
def disable_xformers(self) -> bool:
"""
Return true if enable_xformers is false (reversed logic)
and attention type is not set to xformers.
"""
"""Return true if enable_xformers is false (reversed logic) and attention type is not set to xformers."""
disabled_in_config = not self.xformers_enabled
return disabled_in_config and self.attention_type != "xformers"
@staticmethod
def find_root() -> Path:
"""
Choose the runtime root directory when not specified on command line or
init file.
"""
"""Choose the runtime root directory when not specified on command line or init file."""
return _find_root()
def get_invokeai_config(**kwargs) -> InvokeAIAppConfig:
"""
Legacy function which returns InvokeAIAppConfig.get_config()
"""
"""Legacy function which returns InvokeAIAppConfig.get_config()."""
return InvokeAIAppConfig.get_config(**kwargs)

9
invokeai/app/services/model_records/model_records_sql.py
View File

@@ -48,7 +48,6 @@ from typing import List, Optional, Union
from invokeai.backend.model_manager.config import (
AnyModelConfig,
BaseModelType,
ModelConfigBase,
ModelConfigFactory,
ModelType,
)
@@ -158,7 +157,7 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
("version", CONFIG_FILE_VERSION),
)
def add_model(self, key: str, config: Union[dict, ModelConfigBase]) -> AnyModelConfig:
def add_model(self, key: str, config: Union[dict, AnyModelConfig]) -> AnyModelConfig:
"""
Add a model to the database.
@@ -255,7 +254,7 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
self._db.conn.rollback()
raise e
def update_model(self, key: str, config: ModelConfigBase) -> AnyModelConfig:
def update_model(self, key: str, config: Union[dict, AnyModelConfig]) -> AnyModelConfig:
"""
Update the model, returning the updated version.
@@ -368,7 +367,7 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
results = [ModelConfigFactory.make_config(json.loads(x[0])) for x in self._cursor.fetchall()]
return results
def search_by_path(self, path: Union[str, Path]) -> List[ModelConfigBase]:
def search_by_path(self, path: Union[str, Path]) -> List[AnyModelConfig]:
"""Return models with the indicated path."""
results = []
with self._db.lock:
@@ -382,7 +381,7 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
results = [ModelConfigFactory.make_config(json.loads(x[0])) for x in self._cursor.fetchall()]
return results
def search_by_hash(self, hash: str) -> List[ModelConfigBase]:
def search_by_hash(self, hash: str) -> List[AnyModelConfig]:
"""Return models with the indicated original_hash."""
results = []
with self._db.lock: