mirror of
https://github.com/invoke-ai/InvokeAI
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d9dc5d58be
Turns out they are just different enough in purpose that the implementations would be rather unintuitive. I've made a separate ObjectSerializer service to handle tensors and conditioning. Refined the class a bit too.
99 lines
4.3 KiB
Python
99 lines
4.3 KiB
Python
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
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from __future__ import annotations
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from typing import TYPE_CHECKING
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from invokeai.app.services.object_serializer.object_serializer_base import ObjectSerializerBase
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if TYPE_CHECKING:
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from logging import Logger
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import torch
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from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData
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from .board_image_records.board_image_records_base import BoardImageRecordStorageBase
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from .board_images.board_images_base import BoardImagesServiceABC
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from .board_records.board_records_base import BoardRecordStorageBase
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from .boards.boards_base import BoardServiceABC
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from .config import InvokeAIAppConfig
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from .download import DownloadQueueServiceBase
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from .events.events_base import EventServiceBase
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from .image_files.image_files_base import ImageFileStorageBase
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from .image_records.image_records_base import ImageRecordStorageBase
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from .images.images_base import ImageServiceABC
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from .invocation_cache.invocation_cache_base import InvocationCacheBase
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from .invocation_processor.invocation_processor_base import InvocationProcessorABC
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from .invocation_queue.invocation_queue_base import InvocationQueueABC
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from .invocation_stats.invocation_stats_base import InvocationStatsServiceBase
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from .item_storage.item_storage_base import ItemStorageABC
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from .model_install import ModelInstallServiceBase
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from .model_manager.model_manager_base import ModelManagerServiceBase
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from .model_records import ModelRecordServiceBase
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from .names.names_base import NameServiceBase
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from .session_processor.session_processor_base import SessionProcessorBase
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from .session_queue.session_queue_base import SessionQueueBase
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from .shared.graph import GraphExecutionState
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from .urls.urls_base import UrlServiceBase
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from .workflow_records.workflow_records_base import WorkflowRecordsStorageBase
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class InvocationServices:
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"""Services that can be used by invocations"""
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def __init__(
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self,
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board_images: "BoardImagesServiceABC",
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board_image_records: "BoardImageRecordStorageBase",
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boards: "BoardServiceABC",
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board_records: "BoardRecordStorageBase",
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configuration: "InvokeAIAppConfig",
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events: "EventServiceBase",
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graph_execution_manager: "ItemStorageABC[GraphExecutionState]",
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images: "ImageServiceABC",
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image_files: "ImageFileStorageBase",
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image_records: "ImageRecordStorageBase",
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logger: "Logger",
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model_manager: "ModelManagerServiceBase",
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model_records: "ModelRecordServiceBase",
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download_queue: "DownloadQueueServiceBase",
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model_install: "ModelInstallServiceBase",
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processor: "InvocationProcessorABC",
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performance_statistics: "InvocationStatsServiceBase",
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queue: "InvocationQueueABC",
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session_queue: "SessionQueueBase",
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session_processor: "SessionProcessorBase",
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invocation_cache: "InvocationCacheBase",
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names: "NameServiceBase",
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urls: "UrlServiceBase",
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workflow_records: "WorkflowRecordsStorageBase",
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tensors: "ObjectSerializerBase[torch.Tensor]",
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conditioning: "ObjectSerializerBase[ConditioningFieldData]",
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):
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self.board_images = board_images
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self.board_image_records = board_image_records
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self.boards = boards
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self.board_records = board_records
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self.configuration = configuration
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self.events = events
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self.graph_execution_manager = graph_execution_manager
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self.images = images
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self.image_files = image_files
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self.image_records = image_records
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self.logger = logger
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self.model_manager = model_manager
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self.model_records = model_records
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self.download_queue = download_queue
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self.model_install = model_install
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self.processor = processor
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self.performance_statistics = performance_statistics
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self.queue = queue
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self.session_queue = session_queue
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self.session_processor = session_processor
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self.invocation_cache = invocation_cache
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self.names = names
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self.urls = urls
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self.workflow_records = workflow_records
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self.tensors = tensors
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self.conditioning = conditioning
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