feat(nodes): update field constraints for clip_skip

invokeai/app/invocations/blend_latents.py

@@ -63,7 +63,7 @@ def slerp(
     title="Blend Latents",
     tags=["latents", "blend", "mask"],
     category="latents",
-    version="1.1.0",
+    version="1.1.1",
 )
 class BlendLatentsInvocation(BaseInvocation):
     """Blend two latents using a given alpha. If a mask is provided, the second latents will be masked before blending.
@@ -72,7 +72,7 @@ class BlendLatentsInvocation(BaseInvocation):
     latents_a: LatentsField = InputField(description=FieldDescriptions.latents, input=Input.Connection)
     latents_b: LatentsField = InputField(description=FieldDescriptions.latents, input=Input.Connection)
     mask: Optional[ImageField] = InputField(default=None, description="Mask for blending in latents B")
-    alpha: float = InputField(ge=0, default=0.5, description=FieldDescriptions.blend_alpha)
+    alpha: float = InputField(ge=0.0, default=0.5, le=1.0, description=FieldDescriptions.blend_alpha)
 
     def prep_mask_tensor(self, mask_image: Image.Image) -> torch.Tensor:
         if mask_image.mode != "L":

invokeai/app/invocations/compel.py

@@ -236,7 +236,7 @@ class SDXLPromptInvocationBase:
     title="SDXL Prompt",
     tags=["sdxl", "compel", "prompt"],
     category="conditioning",
-    version="1.2.0",
+    version="1.2.1",
 )
 class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
     """Parse prompt using compel package to conditioning."""
@@ -251,12 +251,12 @@ class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
         description=FieldDescriptions.compel_prompt,
         ui_component=UIComponent.Textarea,
     )
-    original_width: int = InputField(default=1024, description="")
-    original_height: int = InputField(default=1024, description="")
-    crop_top: int = InputField(default=0, description="")
-    crop_left: int = InputField(default=0, description="")
-    target_width: int = InputField(default=1024, description="")
-    target_height: int = InputField(default=1024, description="")
+    original_width: int = InputField(ge=8, default=1024, description="")
+    original_height: int = InputField(ge=8, default=1024, description="")
+    crop_top: int = InputField(default=0, ge=0, description="")
+    crop_left: int = InputField(default=0, ge=0, description="")
+    target_width: int = InputField(ge=8, default=1024, description="")
+    target_height: int = InputField(ge=8, default=1024, description="")
     clip: CLIPField = InputField(description=FieldDescriptions.clip, input=Input.Connection, title="CLIP 1")
     clip2: CLIPField = InputField(description=FieldDescriptions.clip, input=Input.Connection, title="CLIP 2")
     mask: Optional[TensorField] = InputField(
@@ -340,11 +340,11 @@ class SDXLRefinerCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase
         description=FieldDescriptions.compel_prompt,
         ui_component=UIComponent.Textarea,
     )  # TODO: ?
-    original_width: int = InputField(default=1024, description="")
-    original_height: int = InputField(default=1024, description="")
-    crop_top: int = InputField(default=0, description="")
-    crop_left: int = InputField(default=0, description="")
-    aesthetic_score: float = InputField(default=6.0, description=FieldDescriptions.sdxl_aesthetic)
+    original_width: int = InputField(ge=8, default=1024, description="")
+    original_height: int = InputField(ge=8, default=1024, description="")
+    crop_top: int = InputField(ge=0, default=0, description="")
+    crop_left: int = InputField(ge=0, default=0, description="")
+    aesthetic_score: float = InputField(ge=1.0, le=10.0, default=6.0, description=FieldDescriptions.sdxl_aesthetic)
     clip2: CLIPField = InputField(description=FieldDescriptions.clip, input=Input.Connection)
 
     @torch.no_grad()
@@ -379,13 +379,13 @@ class CLIPSkipInvocationOutput(BaseInvocationOutput):
     title="CLIP Skip",
     tags=["clipskip", "clip", "skip"],
     category="conditioning",
-    version="1.1.0",
+    version="1.1.1",
 )
 class CLIPSkipInvocation(BaseInvocation):
     """Skip layers in clip text_encoder model."""
 
     clip: CLIPField = InputField(description=FieldDescriptions.clip, input=Input.Connection, title="CLIP")
-    skipped_layers: int = InputField(default=0, ge=0, description=FieldDescriptions.skipped_layers)
+    skipped_layers: int = InputField(default=0, ge=0, le=24, description=FieldDescriptions.skipped_layers)
 
     def invoke(self, context: InvocationContext) -> CLIPSkipInvocationOutput:
         self.clip.skipped_layers += self.skipped_layers