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https://github.com/invoke-ai/InvokeAI
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feat(nodes): use LATENT_SCALE_FACTOR in primitives.py, noise.py
- LatentsOutput.build - NoiseOutput.build - Noise.width, Noise.height multiple_of
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@ -4,6 +4,7 @@
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import torch
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import torch
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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.constants import LATENT_SCALE_FACTOR
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from invokeai.app.invocations.fields import FieldDescriptions, InputField, LatentsField, OutputField
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from invokeai.app.invocations.fields import FieldDescriptions, InputField, LatentsField, OutputField
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from invokeai.app.services.shared.invocation_context import InvocationContext
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from invokeai.app.services.shared.invocation_context import InvocationContext
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from invokeai.app.util.misc import SEED_MAX
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from invokeai.app.util.misc import SEED_MAX
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@ -70,8 +71,8 @@ class NoiseOutput(BaseInvocationOutput):
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def build(cls, latents_name: str, latents: torch.Tensor, seed: int) -> "NoiseOutput":
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def build(cls, latents_name: str, latents: torch.Tensor, seed: int) -> "NoiseOutput":
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return cls(
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return cls(
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noise=LatentsField(latents_name=latents_name, seed=seed),
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noise=LatentsField(latents_name=latents_name, seed=seed),
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width=latents.size()[3] * 8,
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width=latents.size()[3] * LATENT_SCALE_FACTOR,
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height=latents.size()[2] * 8,
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height=latents.size()[2] * LATENT_SCALE_FACTOR,
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)
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)
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@ -93,13 +94,13 @@ class NoiseInvocation(BaseInvocation):
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)
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)
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width: int = InputField(
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width: int = InputField(
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default=512,
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default=512,
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multiple_of=8,
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multiple_of=LATENT_SCALE_FACTOR,
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gt=0,
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gt=0,
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description=FieldDescriptions.width,
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description=FieldDescriptions.width,
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)
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)
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height: int = InputField(
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height: int = InputField(
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default=512,
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default=512,
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multiple_of=8,
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multiple_of=LATENT_SCALE_FACTOR,
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gt=0,
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gt=0,
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description=FieldDescriptions.height,
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description=FieldDescriptions.height,
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)
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)
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@ -4,6 +4,7 @@ from typing import Optional
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import torch
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import torch
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from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
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from invokeai.app.invocations.fields import (
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from invokeai.app.invocations.fields import (
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ColorField,
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ColorField,
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ConditioningField,
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ConditioningField,
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@ -321,8 +322,8 @@ class LatentsOutput(BaseInvocationOutput):
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def build(cls, latents_name: str, latents: torch.Tensor, seed: Optional[int] = None) -> "LatentsOutput":
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def build(cls, latents_name: str, latents: torch.Tensor, seed: Optional[int] = None) -> "LatentsOutput":
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return cls(
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return cls(
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latents=LatentsField(latents_name=latents_name, seed=seed),
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latents=LatentsField(latents_name=latents_name, seed=seed),
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width=latents.size()[3] * 8,
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width=latents.size()[3] * LATENT_SCALE_FACTOR,
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height=latents.size()[2] * 8,
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height=latents.size()[2] * LATENT_SCALE_FACTOR,
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)
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)
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