Mirrored_Repos/InvokeAI
1
0
Fork 0
mirror of https://github.com/invoke-ai/InvokeAI synced 2024-08-30 20:32:17 +00:00
Code Issues Packages Projects Releases Wiki Activity

feat(nodes): hardcode resize latents downsampling

Browse Source
This commit is contained in:
psychedelicious 2023-04-27 09:59:22 +10:00
parent 0453d60c64
commit 4a924c9b54
1 changed files with 3 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

10
invokeai/app/invocations/latent.py
View File

@ -374,7 +374,7 @@ LATENTS_INTERPOLATION_MODE = Literal[
class ResizeLatentsInvocation(BaseInvocation): class ResizeLatentsInvocation(BaseInvocation):
"""Resizes latents to explicit width/height.""" """Resizes latents to explicit width/height (in pixels). Provided dimensions are floor-divided by 8."""
type: Literal["lresize"] = "lresize" type: Literal["lresize"] = "lresize"
@ -382,7 +382,6 @@ class ResizeLatentsInvocation(BaseInvocation):
latents: Optional[LatentsField] = Field(description="The latents to resize") latents: Optional[LatentsField] = Field(description="The latents to resize")
width: int = Field(ge=64, multiple_of=8, description="The width to resize to (px)") 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)") height: int = Field(ge=64, multiple_of=8, description="The height to resize to (px)")
downsample: Optional[int] = Field(default=8, ge=1, description="The downsampling factor (leave at 8 for SD)")
mode: Optional[LATENTS_INTERPOLATION_MODE] = Field(default="bilinear", description="The interpolation mode") 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)") antialias: Optional[bool] = Field(default=False, description="Whether or not to antialias (applied in bilinear and bicubic modes only)")
@ -391,10 +390,7 @@ class ResizeLatentsInvocation(BaseInvocation):
resized_latents = torch.nn.functional.interpolate( resized_latents = torch.nn.functional.interpolate(
latents, latents,
size=( size=(self.height // 8, self.width // 8),
self.height // self.downsample,
self.width // self.downsample,
),
mode=self.mode, mode=self.mode,
antialias=self.antialias if self.mode in ["bilinear", "bicubic"] else False, antialias=self.antialias if self.mode in ["bilinear", "bicubic"] else False,
) )
@ -414,7 +410,7 @@ class ScaleLatentsInvocation(BaseInvocation):
# Inputs # Inputs
latents: Optional[LatentsField] = Field(description="The latents to scale") latents: Optional[LatentsField] = Field(description="The latents to scale")
scale_factor: float = Field(ge=0, description="The factor by which to scale the latents") 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") 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)") antialias: Optional[bool] = Field(default=False, description="Whether or not to antialias (applied in bilinear and bicubic modes only)")