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feat(nodes): add w/h to latents outputs (#3389)

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This reduces the number of nodes needed when working with latents (ie
fewer plain integer value nodes)

Also correct a few mistakes in the fields
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blessedcoolant 2023-05-12 15:40:46 +12:00 committed by GitHub
commit e559730b6e
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1 changed files with 41 additions and 24 deletions
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65
invokeai/app/invocations/latent.py
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@ -41,17 +41,40 @@ class LatentsField(BaseModel):
class LatentsOutput(BaseInvocationOutput):
"""Base class for invocations that output latents"""
#fmt: off
type: Literal["latent_output"] = "latent_output"
latents: LatentsField = Field(default=None, description="The output latents")
type: Literal["latents_output"] = "latents_output"
# Inputs
latents: LatentsField = Field(default=None, description="The output latents")
width: int = Field(description="The width of the latents in pixels")
height: int = Field(description="The height of the latents in pixels")
#fmt: on
def build_latents_output(latents_name: str, latents: torch.Tensor):
return LatentsOutput(
latents=LatentsField(latents_name=latents_name),
width=latents.size()[3] * 8,
height=latents.size()[2] * 8,
)
class NoiseOutput(BaseInvocationOutput):
"""Invocation noise output"""
#fmt: off
type: Literal["noise_output"] = "noise_output"
type: Literal["noise_output"] = "noise_output"
# Inputs
noise: LatentsField = Field(default=None, description="The output noise")
width: int = Field(description="The width of the noise in pixels")
height: int = Field(description="The height of the noise in pixels")
#fmt: on
def build_noise_output(latents_name: str, latents: torch.Tensor):
return NoiseOutput(
noise=LatentsField(latents_name=latents_name),
width=latents.size()[3] * 8,
height=latents.size()[2] * 8,
)
SAMPLER_NAME_VALUES = Literal[
tuple(list(SCHEDULER_MAP.keys()))
@ -122,9 +145,7 @@ class NoiseInvocation(BaseInvocation):
name = f'{context.graph_execution_state_id}__{self.id}'
context.services.latents.set(name, noise)
return NoiseOutput(
noise=LatentsField(latents_name=name)
)
return build_noise_output(latents_name=name, latents=noise)
# Text to image
@ -240,9 +261,7 @@ class TextToLatentsInvocation(BaseInvocation):
name = f'{context.graph_execution_state_id}__{self.id}'
context.services.latents.set(name, result_latents)
return LatentsOutput(
latents=LatentsField(latents_name=name)
)
return build_latents_output(latents_name=name, latents=result_latents)
class LatentsToLatentsInvocation(TextToLatentsInvocation):
@ -301,9 +320,7 @@ class LatentsToLatentsInvocation(TextToLatentsInvocation):
name = f'{context.graph_execution_state_id}__{self.id}'
context.services.latents.set(name, result_latents)
return LatentsOutput(
latents=LatentsField(latents_name=name)
)
return build_latents_output(latents_name=name, latents=result_latents)
# Latent to image
@ -367,11 +384,11 @@ class ResizeLatentsInvocation(BaseInvocation):
type: Literal["lresize"] = "lresize"
# Inputs
latents: Optional[LatentsField] = Field(description="The latents to resize")
width: int = Field(ge=64, multiple_of=8, description="The width to resize to (px)")
height: int = Field(ge=64, multiple_of=8, description="The height to resize to (px)")
mode: Optional[LATENTS_INTERPOLATION_MODE] = Field(default="bilinear", description="The interpolation mode")
antialias: Optional[bool] = Field(default=False, description="Whether or not to antialias (applied in bilinear and bicubic modes only)")
latents: Optional[LatentsField] = Field(description="The latents to resize")
width: int = Field(ge=64, multiple_of=8, description="The width to resize to (px)")
height: int = Field(ge=64, multiple_of=8, description="The height to resize to (px)")
mode: LATENTS_INTERPOLATION_MODE = Field(default="bilinear", description="The interpolation mode")
antialias: bool = Field(default=False, description="Whether or not to antialias (applied in bilinear and bicubic modes only)")
def invoke(self, context: InvocationContext) -> LatentsOutput:
latents = context.services.latents.get(self.latents.latents_name)
@ -388,7 +405,7 @@ class ResizeLatentsInvocation(BaseInvocation):
name = f"{context.graph_execution_state_id}__{self.id}"
context.services.latents.set(name, resized_latents)
return LatentsOutput(latents=LatentsField(latents_name=name))
return build_latents_output(latents_name=name, latents=resized_latents)
class ScaleLatentsInvocation(BaseInvocation):
@ -397,10 +414,10 @@ class ScaleLatentsInvocation(BaseInvocation):
type: Literal["lscale"] = "lscale"
# Inputs
latents: Optional[LatentsField] = Field(description="The latents to scale")
scale_factor: float = Field(gt=0, description="The factor by which to scale the latents")
mode: Optional[LATENTS_INTERPOLATION_MODE] = Field(default="bilinear", description="The interpolation mode")
antialias: Optional[bool] = Field(default=False, description="Whether or not to antialias (applied in bilinear and bicubic modes only)")
latents: Optional[LatentsField] = Field(description="The latents to scale")
scale_factor: float = Field(gt=0, description="The factor by which to scale the latents")
mode: LATENTS_INTERPOLATION_MODE = Field(default="bilinear", description="The interpolation mode")
antialias: bool = Field(default=False, description="Whether or not to antialias (applied in bilinear and bicubic modes only)")
def invoke(self, context: InvocationContext) -> LatentsOutput:
latents = context.services.latents.get(self.latents.latents_name)
@ -418,7 +435,7 @@ class ScaleLatentsInvocation(BaseInvocation):
name = f"{context.graph_execution_state_id}__{self.id}"
context.services.latents.set(name, resized_latents)
return LatentsOutput(latents=LatentsField(latents_name=name))
return build_latents_output(latents_name=name, latents=resized_latents)
class ImageToLatentsInvocation(BaseInvocation):
@ -462,4 +479,4 @@ class ImageToLatentsInvocation(BaseInvocation):
name = f"{context.graph_execution_state_id}__{self.id}"
context.services.latents.set(name, latents)
return LatentsOutput(latents=LatentsField(latents_name=name))
return build_latents_output(latents_name=name, latents=latents)