Merge branch 'lstein/logging-improvements' of github.com:invoke-ai/InvokeAI into lstein/logging-improvements

This commit is contained in:
Lincoln Stein 2023-05-25 09:39:56 -04:00
commit 7f5992d6a5
8 changed files with 70 additions and 43 deletions

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@ -125,6 +125,7 @@ jobs:
--no-nsfw_checker
--precision=float32
--always_use_cpu
--use_memory_db
--outdir ${{ env.INVOKEAI_OUTDIR }}/${{ matrix.python-version }}/${{ matrix.pytorch }}
--from_file ${{ env.TEST_PROMPTS }}

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@ -13,10 +13,13 @@ from typing import (
from pydantic import BaseModel, ValidationError
from pydantic.fields import Field
from invokeai.app.services.image_record_storage import SqliteImageRecordStorage
from invokeai.app.services.images import ImageService
from invokeai.app.services.metadata import CoreMetadataService
from invokeai.app.services.urls import LocalUrlService
import invokeai.backend.util.logging as logger
from invokeai.app.services.metadata import PngMetadataService
from .services.default_graphs import create_system_graphs
from .services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
@ -188,6 +191,9 @@ def invoke_all(context: CliContext):
raise SessionError()
logger = logger.InvokeAILogger.getLogger()
def invoke_cli():
# this gets the basic configuration
config = get_invokeai_config()
@ -206,24 +212,43 @@ def invoke_cli():
events = EventServiceBase()
output_folder = config.output_path
metadata = PngMetadataService()
# TODO: build a file/path manager?
db_location = os.path.join(output_folder, "invokeai.db")
if config.use_memory_db:
db_location = ":memory:"
else:
db_location = os.path.join(output_folder, "invokeai.db")
logger.info(f'InvokeAI database location is "{db_location}"')
graph_execution_manager = SqliteItemStorage[GraphExecutionState](
filename=db_location, table_name="graph_executions"
)
urls = LocalUrlService()
metadata = CoreMetadataService()
image_record_storage = SqliteImageRecordStorage(db_location)
image_file_storage = DiskImageFileStorage(f"{output_folder}/images")
images = ImageService(
image_record_storage=image_record_storage,
image_file_storage=image_file_storage,
metadata=metadata,
url=urls,
logger=logger,
graph_execution_manager=graph_execution_manager,
)
services = InvocationServices(
model_manager=model_manager,
events=events,
latents = ForwardCacheLatentsStorage(DiskLatentsStorage(f'{output_folder}/latents')),
images=DiskImageFileStorage(f'{output_folder}/images', metadata_service=metadata),
metadata=metadata,
images=images,
queue=MemoryInvocationQueue(),
graph_library=SqliteItemStorage[LibraryGraph](
filename=db_location, table_name="graphs"
),
graph_execution_manager=SqliteItemStorage[GraphExecutionState](
filename=db_location, table_name="graph_executions"
),
graph_execution_manager=graph_execution_manager,
processor=DefaultInvocationProcessor(),
restoration=RestorationServices(config,logger=logger),
logger=logger,

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@ -352,6 +352,7 @@ setting environment variables INVOKEAI_<setting>.
sequential_guidance : bool = Field(default=False, description="Whether to calculate guidance in serial instead of in parallel, lowering memory requirements", category='Memory/Performance')
xformers_enabled : bool = Field(default=True, description="Enable/disable memory-efficient attention", category='Memory/Performance')
root : Path = Field(default=_find_root(), description='InvokeAI runtime root directory', category='Paths')
autoconvert_dir : Path = Field(default=None, description='Path to a directory of ckpt files to be converted into diffusers and imported on startup.', category='Paths')
conf_path : Path = Field(default='configs/models.yaml', description='Path to models definition file', category='Paths')
@ -361,6 +362,7 @@ setting environment variables INVOKEAI_<setting>.
lora_dir : Path = Field(default='loras', description='Path to InvokeAI LoRA model directory', category='Paths')
outdir : Path = Field(default='outputs', description='Default folder for output images', category='Paths')
from_file : Path = Field(default=None, description='Take command input from the indicated file (command-line client only)', category='Paths')
use_memory_db : bool = Field(default=False, description='Use in-memory database for storing image metadata', category='Paths')
model : str = Field(default='stable-diffusion-1.5', description='Initial model name', category='Models')
embeddings : bool = Field(default=True, description='Load contents of embeddings directory', category='Models')
@ -515,7 +517,7 @@ class PagingArgumentParser(argparse.ArgumentParser):
text = self.format_help()
pydoc.pager(text)
def get_invokeai_config(cls:Type[InvokeAISettings]=InvokeAIAppConfig,**kwargs)->InvokeAISettings:
def get_invokeai_config(cls:Type[InvokeAISettings]=InvokeAIAppConfig,**kwargs)->InvokeAIAppConfig:
'''
This returns a singleton InvokeAIAppConfig configuration object.
'''

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@ -1,18 +1,17 @@
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
from __future__ import annotations
from typing import TYPE_CHECKING
from logging import Logger
from invokeai.app.services.images import ImageService
from invokeai.backend import ModelManager
from .events import EventServiceBase
from .latent_storage import LatentsStorageBase
from .restoration_services import RestorationServices
from .invocation_queue import InvocationQueueABC
from .item_storage import ItemStorageABC
from .config import InvokeAISettings
if TYPE_CHECKING:
from logging import Logger
from invokeai.app.services.images import ImageService
from invokeai.backend import ModelManager
from invokeai.app.services.events import EventServiceBase
from invokeai.app.services.latent_storage import LatentsStorageBase
from invokeai.app.services.restoration_services import RestorationServices
from invokeai.app.services.invocation_queue import InvocationQueueABC
from invokeai.app.services.item_storage import ItemStorageABC
from invokeai.app.services.config import InvokeAISettings
from invokeai.app.services.graph import GraphExecutionState, LibraryGraph
from invokeai.app.services.invoker import InvocationProcessorABC
@ -20,32 +19,33 @@ if TYPE_CHECKING:
class InvocationServices:
"""Services that can be used by invocations"""
events: EventServiceBase
latents: LatentsStorageBase
queue: InvocationQueueABC
model_manager: ModelManager
restoration: RestorationServices
configuration: InvokeAISettings
images: ImageService
# TODO: Just forward-declared everything due to circular dependencies. Fix structure.
events: "EventServiceBase"
latents: "LatentsStorageBase"
queue: "InvocationQueueABC"
model_manager: "ModelManager"
restoration: "RestorationServices"
configuration: "InvokeAISettings"
images: "ImageService"
# NOTE: we must forward-declare any types that include invocations, since invocations can use services
graph_library: ItemStorageABC["LibraryGraph"]
graph_execution_manager: ItemStorageABC["GraphExecutionState"]
graph_library: "ItemStorageABC"["LibraryGraph"]
graph_execution_manager: "ItemStorageABC"["GraphExecutionState"]
processor: "InvocationProcessorABC"
def __init__(
self,
model_manager: ModelManager,
events: EventServiceBase,
logger: Logger,
latents: LatentsStorageBase,
images: ImageService,
queue: InvocationQueueABC,
graph_library: ItemStorageABC["LibraryGraph"],
graph_execution_manager: ItemStorageABC["GraphExecutionState"],
model_manager: "ModelManager",
events: "EventServiceBase",
logger: "Logger",
latents: "LatentsStorageBase",
images: "ImageService",
queue: "InvocationQueueABC",
graph_library: "ItemStorageABC"["LibraryGraph"],
graph_execution_manager: "ItemStorageABC"["GraphExecutionState"],
processor: "InvocationProcessorABC",
restoration: RestorationServices,
configuration: InvokeAISettings = None,
restoration: "RestorationServices",
configuration: "InvokeAISettings",
):
self.model_manager = model_manager
self.events = events

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@ -1,10 +1,7 @@
import time
import traceback
from threading import Event, Thread, BoundedSemaphore
from typing import Any, TypeGuard
from invokeai.app.invocations.image import ImageOutput
from invokeai.app.models.image import ImageType
from ..invocations.baseinvocation import InvocationContext
from .invocation_queue import InvocationQueueItem
from .invoker import InvocationProcessorABC, Invoker

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@ -35,6 +35,7 @@ def mock_services():
graph_execution_manager = SqliteItemStorage[GraphExecutionState](filename = sqlite_memory, table_name = 'graph_executions'),
processor = DefaultInvocationProcessor(),
restoration = None, # type: ignore
configuration = None, # type: ignore
)
def invoke_next(g: GraphExecutionState, services: InvocationServices) -> tuple[BaseInvocation, BaseInvocationOutput]:

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@ -33,6 +33,7 @@ def mock_services() -> InvocationServices:
graph_execution_manager = SqliteItemStorage[GraphExecutionState](filename = sqlite_memory, table_name = 'graph_executions'),
processor = DefaultInvocationProcessor(),
restoration = None, # type: ignore
configuration = None, # type: ignore
)
@pytest.fixture()

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@ -49,7 +49,7 @@ class ImageTestInvocation(BaseInvocation):
prompt: str = Field(default = "")
def invoke(self, context: InvocationContext) -> ImageTestInvocationOutput:
return ImageTestInvocationOutput(image=ImageField(image_name=self.id, width=512, height=512, mode="", info={}))
return ImageTestInvocationOutput(image=ImageField(image_name=self.id))
class PromptCollectionTestInvocationOutput(BaseInvocationOutput):
type: Literal['test_prompt_collection_output'] = 'test_prompt_collection_output'