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302 lines
8.0 KiB
Python
302 lines
8.0 KiB
Python
"""
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This file re-exports all the public API for invocations. This is the only file that should be imported by custom nodes.
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TODO(psyche): Do we want to dogfood this?
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"""
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from invokeai.app.invocations.baseinvocation import (
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BaseInvocation,
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BaseInvocationOutput,
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Bottleneck,
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Classification,
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invocation,
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invocation_output,
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)
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from invokeai.app.invocations.fields import (
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BoardField,
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BoundingBoxField,
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ColorField,
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ConditioningField,
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DenoiseMaskField,
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FieldDescriptions,
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FieldKind,
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FluxConditioningField,
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ImageField,
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Input,
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InputField,
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LatentsField,
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MetadataField,
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OutputField,
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UIComponent,
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UIType,
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WithBoard,
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WithMetadata,
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WithWorkflow,
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)
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from invokeai.app.invocations.metadata import MetadataItemField, MetadataItemOutput, MetadataOutput
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from invokeai.app.invocations.model import (
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CLIPField,
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CLIPOutput,
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ControlLoRAField,
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GlmEncoderField,
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LoRAField,
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LoRALoaderOutput,
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ModelIdentifierField,
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ModelLoaderOutput,
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SDXLLoRALoaderOutput,
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T5EncoderField,
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TransformerField,
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UNetField,
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UNetOutput,
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VAEField,
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VAEOutput,
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)
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from invokeai.app.invocations.primitives import (
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BooleanCollectionOutput,
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BooleanOutput,
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BoundingBoxOutput,
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ColorCollectionOutput,
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ColorOutput,
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ConditioningCollectionOutput,
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ConditioningOutput,
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DenoiseMaskOutput,
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FloatCollectionOutput,
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FloatOutput,
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FluxConditioningCollectionOutput,
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FluxConditioningOutput,
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ImageCollectionOutput,
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ImageOutput,
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IntegerCollectionOutput,
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IntegerOutput,
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LatentsCollectionOutput,
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LatentsOutput,
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StringCollectionOutput,
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StringOutput,
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)
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from invokeai.app.invocations.scheduler import SchedulerOutput
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from invokeai.app.services.boards.boards_common import BoardDTO
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from invokeai.app.services.config.config_default import InvokeAIAppConfig
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from invokeai.app.services.image_records.image_records_common import ImageCategory
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from invokeai.app.services.shared.invocation_context import InvocationContext
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from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
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from invokeai.app.util.misc import SEED_MAX, get_random_seed
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from invokeai.backend.image_util.color_conversion import (
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gamut_clip_tensor,
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hsl_from_linear_srgb,
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hsl_from_srgb,
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lab_from_linear_srgb,
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lab_from_srgb,
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lab_from_xyz,
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linear_srgb_from_hsl,
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linear_srgb_from_lab,
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linear_srgb_from_oklab,
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linear_srgb_from_oklch,
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linear_srgb_from_srgb,
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linear_srgb_from_xyz,
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okhsl_from_srgb,
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okhsv_from_srgb,
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oklab_from_linear_srgb,
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oklab_from_oklch,
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oklab_from_srgb,
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oklab_from_xyz,
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oklch_from_linear_srgb,
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oklch_from_oklab,
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oklch_from_srgb,
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oklch_from_xyz,
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srgb_from_hsl,
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srgb_from_lab,
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srgb_from_linear_srgb,
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srgb_from_okhsl,
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srgb_from_okhsv,
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srgb_from_oklab,
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srgb_from_oklch,
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srgb_from_xyz,
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xyz_d50_to_d65,
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xyz_d65_to_d50,
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xyz_from_lab,
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xyz_from_linear_srgb,
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xyz_from_oklab,
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xyz_from_oklch,
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xyz_from_srgb,
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)
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from invokeai.backend.model_manager.configs.factory import AnyModelConfig, ModelConfigFactory
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from invokeai.backend.model_manager.load.load_base import LoadedModel
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from invokeai.backend.model_manager.taxonomy import (
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BaseModelType,
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ClipVariantType,
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FluxLoRAFormat,
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FluxVariantType,
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ModelFormat,
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ModelSourceType,
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ModelType,
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ModelVariantType,
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SchedulerPredictionType,
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SubModelType,
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)
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from invokeai.backend.stable_diffusion.diffusers_pipeline import PipelineIntermediateState
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from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
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BasicConditioningInfo,
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ConditioningFieldData,
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SDXLConditioningInfo,
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)
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from invokeai.backend.stable_diffusion.schedulers.schedulers import SCHEDULER_NAME_VALUES
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from invokeai.backend.util.devices import CPU_DEVICE, CUDA_DEVICE, MPS_DEVICE, choose_precision, choose_torch_device
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from invokeai.version import __version__
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__all__ = [
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# invokeai.app.invocations.baseinvocation
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"BaseInvocation",
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"BaseInvocationOutput",
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"Bottleneck",
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"Classification",
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"invocation",
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"invocation_output",
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# invokeai.app.services.shared.invocation_context
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"InvocationContext",
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# invokeai.app.invocations.fields
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"BoardField",
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"BoundingBoxField",
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"ColorField",
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"ConditioningField",
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"DenoiseMaskField",
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"FieldDescriptions",
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"FieldKind",
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"FluxConditioningField",
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"ImageField",
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"Input",
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"InputField",
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"LatentsField",
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"MetadataField",
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"OutputField",
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"UIComponent",
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"UIType",
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"WithBoard",
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"WithMetadata",
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"WithWorkflow",
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# invokeai.app.invocations.scheduler
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"SchedulerOutput",
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# invokeai.app.invocations.metadata
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"MetadataItemField",
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"MetadataItemOutput",
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"MetadataOutput",
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# invokeai.app.invocations.model
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"ModelIdentifierField",
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"LoRAField",
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"UNetField",
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"CLIPField",
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"T5EncoderField",
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"GlmEncoderField",
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"VAEField",
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"ControlLoRAField",
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"TransformerField",
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"UNetOutput",
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"VAEOutput",
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"CLIPOutput",
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"ModelLoaderOutput",
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"LoRALoaderOutput",
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"SDXLLoRALoaderOutput",
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# invokeai.app.invocations.primitives
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"BooleanCollectionOutput",
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"BooleanOutput",
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"BoundingBoxOutput",
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"ColorCollectionOutput",
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"ColorOutput",
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"ConditioningCollectionOutput",
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"ConditioningOutput",
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"DenoiseMaskOutput",
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"FloatCollectionOutput",
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"FloatOutput",
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"FluxConditioningCollectionOutput",
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"FluxConditioningOutput",
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"ImageCollectionOutput",
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"ImageOutput",
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"IntegerCollectionOutput",
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"IntegerOutput",
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"LatentsCollectionOutput",
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"LatentsOutput",
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"StringCollectionOutput",
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"StringOutput",
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# invokeai.app.services.image_records.image_records_common
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"ImageCategory",
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# invokeai.app.services.boards.boards_common
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"BoardDTO",
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# invokeai.backend.stable_diffusion.diffusion.conditioning_data
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"BasicConditioningInfo",
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"ConditioningFieldData",
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"SDXLConditioningInfo",
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# invokeai.backend.stable_diffusion.diffusers_pipeline
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"PipelineIntermediateState",
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# invokeai.app.services.workflow_records.workflow_records_common
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"WorkflowWithoutID",
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# invokeai.app.services.config.config_default
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"InvokeAIAppConfig",
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# invokeai.backend.model_management.model_manager
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"LoadedModel",
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# invokeai.backend.model_management.models.base
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# invokeai.backend.stable_diffusion.schedulers.schedulers
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"SCHEDULER_NAME_VALUES",
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# invokeai.version
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"__version__",
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# invokeai.backend.util.devices
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"choose_precision",
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"choose_torch_device",
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"CPU_DEVICE",
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"CUDA_DEVICE",
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"MPS_DEVICE",
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# invokeai.app.util.misc
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"SEED_MAX",
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"get_random_seed",
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# invokeai.backend.image_util.color_conversion
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"linear_srgb_from_srgb",
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"srgb_from_linear_srgb",
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"oklab_from_srgb",
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"oklab_from_linear_srgb",
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"oklab_from_xyz",
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"srgb_from_oklab",
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"linear_srgb_from_oklab",
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"oklch_from_linear_srgb",
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"oklch_from_srgb",
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"oklch_from_oklab",
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"oklch_from_xyz",
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"oklab_from_oklch",
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"linear_srgb_from_oklch",
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"srgb_from_oklch",
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"xyz_from_linear_srgb",
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"linear_srgb_from_xyz",
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"xyz_from_srgb",
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"srgb_from_xyz",
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"xyz_d65_to_d50",
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"xyz_d50_to_d65",
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"xyz_from_oklab",
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"xyz_from_oklch",
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"lab_from_linear_srgb",
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"linear_srgb_from_lab",
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"lab_from_srgb",
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"srgb_from_lab",
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"lab_from_xyz",
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"xyz_from_lab",
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"hsl_from_linear_srgb",
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"hsl_from_srgb",
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"linear_srgb_from_hsl",
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"srgb_from_hsl",
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"okhsl_from_srgb",
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"srgb_from_okhsl",
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"okhsv_from_srgb",
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"srgb_from_okhsv",
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"gamut_clip_tensor",
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# invokeai.backend.model_manager.taxonomy
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"BaseModelType",
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"ModelType",
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"ModelSourceType",
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"ModelFormat",
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"ModelVariantType",
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"SchedulerPredictionType",
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"SubModelType",
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"ClipVariantType",
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"FluxLoRAFormat",
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"FluxVariantType",
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# invokeai.backend.model_manager.configs.factory
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"AnyModelConfig",
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"ModelConfigFactory",
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]
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