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Mark TiledMultiDiffusionDenoiseLatents as a Beta node.
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@ -7,7 +7,7 @@ from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel
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from diffusers.schedulers.scheduling_utils import SchedulerMixin
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from diffusers.schedulers.scheduling_utils import SchedulerMixin
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from pydantic import field_validator
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from pydantic import field_validator
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from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
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from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, 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.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.controlnet_image_processors import ControlField
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from invokeai.app.invocations.denoise_latents import DenoiseLatentsInvocation, get_scheduler
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from invokeai.app.invocations.denoise_latents import DenoiseLatentsInvocation, get_scheduler
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@ -55,6 +55,7 @@ def crop_controlnet_data(control_data: ControlNetData, latent_region: TBLR) -> C
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title="Tiled Multi-Diffusion Denoise Latents",
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title="Tiled Multi-Diffusion Denoise Latents",
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tags=["upscale", "denoise"],
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tags=["upscale", "denoise"],
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category="latents",
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category="latents",
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classification=Classification.Beta,
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version="1.0.0",
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version="1.0.0",
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)
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)
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class TiledMultiDiffusionDenoiseLatents(BaseInvocation):
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class TiledMultiDiffusionDenoiseLatents(BaseInvocation):
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