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https://github.com/invoke-ai/InvokeAI
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chore(nodes): "SAMPLER_NAME_VALUES" -> "SCHEDULER_NAME_VALUES"
This was named inaccurately.
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@ -1,3 +1,7 @@
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from typing import Literal
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from invokeai.backend.stable_diffusion.schedulers import SCHEDULER_MAP
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LATENT_SCALE_FACTOR = 8
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"""
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HACK: Many nodes are currently hard-coded to use a fixed latent scale factor of 8. This is fragile, and will need to
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@ -5,3 +9,6 @@ be addressed if future models use a different latent scale factor. Also, note th
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factor is hard-coded to a literal '8' rather than using this constant.
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The ratio of image:latent dimensions is LATENT_SCALE_FACTOR:1, or 8:1.
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"""
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SCHEDULER_NAME_VALUES = Literal[tuple(SCHEDULER_MAP.keys())]
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"""A literal type representing the valid scheduler names."""
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@ -23,7 +23,7 @@ from diffusers.schedulers import SchedulerMixin as Scheduler
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from pydantic import field_validator
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from torchvision.transforms.functional import resize as tv_resize
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from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
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from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR, SCHEDULER_NAME_VALUES
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from invokeai.app.invocations.fields import (
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ConditioningField,
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DenoiseMaskField,
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@ -78,12 +78,10 @@ if choose_torch_device() == torch.device("mps"):
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DEFAULT_PRECISION = choose_precision(choose_torch_device())
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SAMPLER_NAME_VALUES = Literal[tuple(SCHEDULER_MAP.keys())]
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@invocation_output("scheduler_output")
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class SchedulerOutput(BaseInvocationOutput):
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scheduler: SAMPLER_NAME_VALUES = OutputField(description=FieldDescriptions.scheduler, ui_type=UIType.Scheduler)
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scheduler: SCHEDULER_NAME_VALUES = OutputField(description=FieldDescriptions.scheduler, ui_type=UIType.Scheduler)
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@invocation(
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@ -96,7 +94,7 @@ class SchedulerOutput(BaseInvocationOutput):
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class SchedulerInvocation(BaseInvocation):
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"""Selects a scheduler."""
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scheduler: SAMPLER_NAME_VALUES = InputField(
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scheduler: SCHEDULER_NAME_VALUES = InputField(
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default="euler",
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description=FieldDescriptions.scheduler,
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ui_type=UIType.Scheduler,
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@ -234,7 +232,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
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description=FieldDescriptions.denoising_start,
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)
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denoising_end: float = InputField(default=1.0, ge=0, le=1, description=FieldDescriptions.denoising_end)
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scheduler: SAMPLER_NAME_VALUES = InputField(
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scheduler: SCHEDULER_NAME_VALUES = InputField(
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default="euler",
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description=FieldDescriptions.scheduler,
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ui_type=UIType.Scheduler,
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