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fix(nodes): restore missing context type annotations

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psychedelicious 2024-02-06 10:22:58 +11:00 committed by Brandon Rising
parent c3bfb4a38f
commit 0ff466ebc4
1 changed files with 9 additions and 9 deletions
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18
invokeai/app/invocations/latent.py
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@ -106,7 +106,7 @@ class SchedulerInvocation(BaseInvocation):
ui_type=UIType.Scheduler,
)
def invoke(self, context) -> SchedulerOutput:
def invoke(self, context: InvocationContext) -> SchedulerOutput:
return SchedulerOutput(scheduler=self.scheduler)
@ -141,7 +141,7 @@ class CreateDenoiseMaskInvocation(BaseInvocation):
return mask_tensor
@torch.no_grad()
def invoke(self, context) -> DenoiseMaskOutput:
def invoke(self, context: InvocationContext) -> DenoiseMaskOutput:
if self.image is not None:
image = context.images.get_pil(self.image.image_name)
image = image_resized_to_grid_as_tensor(image.convert("RGB"))
@ -630,7 +630,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
return 1 - mask, masked_latents
@torch.no_grad()
def invoke(self, context) -> LatentsOutput:
def invoke(self, context: InvocationContext) -> LatentsOutput:
with SilenceWarnings(): # this quenches NSFW nag from diffusers
seed = None
noise = None
@ -777,7 +777,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata):
fp32: bool = InputField(default=DEFAULT_PRECISION == "float32", description=FieldDescriptions.fp32)
@torch.no_grad()
def invoke(self, context) -> ImageOutput:
def invoke(self, context: InvocationContext) -> ImageOutput:
latents = context.latents.get(self.latents.latents_name)
vae_info = context.models.load(**self.vae.vae.model_dump())
@ -868,7 +868,7 @@ class ResizeLatentsInvocation(BaseInvocation):
mode: LATENTS_INTERPOLATION_MODE = InputField(default="bilinear", description=FieldDescriptions.interp_mode)
antialias: bool = InputField(default=False, description=FieldDescriptions.torch_antialias)
def invoke(self, context) -> LatentsOutput:
def invoke(self, context: InvocationContext) -> LatentsOutput:
latents = context.latents.get(self.latents.latents_name)
# TODO:
@ -909,7 +909,7 @@ class ScaleLatentsInvocation(BaseInvocation):
mode: LATENTS_INTERPOLATION_MODE = InputField(default="bilinear", description=FieldDescriptions.interp_mode)
antialias: bool = InputField(default=False, description=FieldDescriptions.torch_antialias)
def invoke(self, context) -> LatentsOutput:
def invoke(self, context: InvocationContext) -> LatentsOutput:
latents = context.latents.get(self.latents.latents_name)
# TODO:
@ -998,7 +998,7 @@ class ImageToLatentsInvocation(BaseInvocation):
return latents
@torch.no_grad()
def invoke(self, context) -> LatentsOutput:
def invoke(self, context: InvocationContext) -> LatentsOutput:
image = context.images.get_pil(self.image.image_name)
vae_info = context.models.load(**self.vae.vae.model_dump())
@ -1046,7 +1046,7 @@ class BlendLatentsInvocation(BaseInvocation):
)
alpha: float = InputField(default=0.5, description=FieldDescriptions.blend_alpha)
def invoke(self, context) -> LatentsOutput:
def invoke(self, context: InvocationContext) -> LatentsOutput:
latents_a = context.latents.get(self.latents_a.latents_name)
latents_b = context.latents.get(self.latents_b.latents_name)
@ -1147,7 +1147,7 @@ class CropLatentsCoreInvocation(BaseInvocation):
description="The height (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.",
)
def invoke(self, context) -> LatentsOutput:
def invoke(self, context: InvocationContext) -> LatentsOutput:
latents = context.latents.get(self.latents.latents_name)
x1 = self.x // LATENT_SCALE_FACTOR