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Tidy denoise_latents.py imports to all use absolute import paths.
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@ -16,7 +16,9 @@ from pydantic import field_validator
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from torchvision.transforms.functional import resize as tv_resize
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from transformers import CLIPVisionModelWithProjection
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from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
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from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR, SCHEDULER_NAME_VALUES
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from invokeai.app.invocations.controlnet_image_processors import ControlField
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from invokeai.app.invocations.fields import (
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ConditioningField,
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DenoiseMaskField,
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@ -27,6 +29,7 @@ from invokeai.app.invocations.fields import (
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UIType,
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)
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from invokeai.app.invocations.ip_adapter import IPAdapterField
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from invokeai.app.invocations.model import ModelIdentifierField, UNetField
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from invokeai.app.invocations.primitives import LatentsOutput
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from invokeai.app.invocations.t2i_adapter import T2IAdapterField
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from invokeai.app.services.shared.invocation_context import InvocationContext
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@ -36,6 +39,11 @@ from invokeai.backend.lora import LoRAModelRaw
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from invokeai.backend.model_manager import BaseModelType
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from invokeai.backend.model_patcher import ModelPatcher
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from invokeai.backend.stable_diffusion import PipelineIntermediateState, set_seamless
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from invokeai.backend.stable_diffusion.diffusers_pipeline import (
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ControlNetData,
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StableDiffusionGeneratorPipeline,
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T2IAdapterData,
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)
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from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
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BasicConditioningInfo,
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IPAdapterConditioningInfo,
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@ -45,20 +53,11 @@ from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
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TextConditioningData,
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TextConditioningRegions,
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)
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from invokeai.backend.stable_diffusion.schedulers import SCHEDULER_MAP
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from invokeai.backend.util.devices import TorchDevice
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from invokeai.backend.util.mask import to_standard_float_mask
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from invokeai.backend.util.silence_warnings import SilenceWarnings
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from ...backend.stable_diffusion.diffusers_pipeline import (
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ControlNetData,
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StableDiffusionGeneratorPipeline,
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T2IAdapterData,
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)
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from ...backend.stable_diffusion.schedulers import SCHEDULER_MAP
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from ...backend.util.devices import TorchDevice
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from .baseinvocation import BaseInvocation, invocation
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from .controlnet_image_processors import ControlField
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from .model import ModelIdentifierField, UNetField
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def get_scheduler(
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context: InvocationContext,
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