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fix(app): fixed InputField default values #7464

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Dec 19, 2024
Merged

fix(app): fixed InputField default values #7464

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7 changes: 1 addition & 6 deletions invokeai/app/invocations/create_denoise_mask.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,6 @@
from torchvision.transforms.functional import resize as tv_resize

from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.constants import DEFAULT_PRECISION
from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField
from invokeai.app.invocations.image_to_latents import ImageToLatentsInvocation
from invokeai.app.invocations.model import VAEField
Expand All @@ -29,11 +28,7 @@ class CreateDenoiseMaskInvocation(BaseInvocation):
image: Optional[ImageField] = InputField(default=None, description="Image which will be masked", ui_order=1)
mask: ImageField = InputField(description="The mask to use when pasting", ui_order=2)
tiled: bool = InputField(default=False, description=FieldDescriptions.tiled, ui_order=3)
fp32: bool = InputField(
default=DEFAULT_PRECISION == torch.float32,
description=FieldDescriptions.fp32,
ui_order=4,
)
fp32: bool = InputField(default=False, description=FieldDescriptions.fp32, ui_order=4)

def prep_mask_tensor(self, mask_image: Image.Image) -> torch.Tensor:
if mask_image.mode != "L":
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7 changes: 1 addition & 6 deletions invokeai/app/invocations/create_gradient_mask.py
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Expand Up @@ -7,7 +7,6 @@
from torchvision.transforms.functional import resize as tv_resize

from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
from invokeai.app.invocations.constants import DEFAULT_PRECISION
from invokeai.app.invocations.fields import (
DenoiseMaskField,
FieldDescriptions,
Expand Down Expand Up @@ -76,11 +75,7 @@ class CreateGradientMaskInvocation(BaseInvocation):
ui_order=7,
)
tiled: bool = InputField(default=False, description=FieldDescriptions.tiled, ui_order=8)
fp32: bool = InputField(
default=DEFAULT_PRECISION == torch.float32,
description=FieldDescriptions.fp32,
ui_order=9,
)
fp32: bool = InputField(default=False, description=FieldDescriptions.fp32, ui_order=9)

@torch.no_grad()
def invoke(self, context: InvocationContext) -> GradientMaskOutput:
Expand Down
4 changes: 2 additions & 2 deletions invokeai/app/invocations/image_to_latents.py
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Expand Up @@ -13,7 +13,7 @@
from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny

from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.constants import DEFAULT_PRECISION, LATENT_SCALE_FACTOR
from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
from invokeai.app.invocations.fields import (
FieldDescriptions,
ImageField,
Expand Down Expand Up @@ -49,7 +49,7 @@ class ImageToLatentsInvocation(BaseInvocation):
# NOTE: tile_size = 0 is a special value. We use this rather than `int | None`, because the workflow UI does not
# offer a way to directly set None values.
tile_size: int = InputField(default=0, multiple_of=8, description=FieldDescriptions.vae_tile_size)
fp32: bool = InputField(default=DEFAULT_PRECISION == torch.float32, description=FieldDescriptions.fp32)
fp32: bool = InputField(default=False, description=FieldDescriptions.fp32)

@staticmethod
def vae_encode(
Expand Down
4 changes: 2 additions & 2 deletions invokeai/app/invocations/latents_to_image.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,7 @@
from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny

from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.constants import DEFAULT_PRECISION, LATENT_SCALE_FACTOR
from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
from invokeai.app.invocations.fields import (
FieldDescriptions,
Input,
Expand Down Expand Up @@ -51,7 +51,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
# NOTE: tile_size = 0 is a special value. We use this rather than `int | None`, because the workflow UI does not
# offer a way to directly set None values.
tile_size: int = InputField(default=0, multiple_of=8, description=FieldDescriptions.vae_tile_size)
fp32: bool = InputField(default=DEFAULT_PRECISION == torch.float32, description=FieldDescriptions.fp32)
fp32: bool = InputField(default=False, description=FieldDescriptions.fp32)

@torch.no_grad()
def invoke(self, context: InvocationContext) -> ImageOutput:
Expand Down
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