Rename MaskField to be a generice TensorField.

invokeai/app/invocations/compel.py

@@ -10,8 +10,8 @@ from invokeai.app.invocations.fields import (
     FieldDescriptions,
     Input,
     InputField,
-    MaskField,
     OutputField,
+    TensorField,
     UIComponent,
 )
 from invokeai.app.invocations.primitives import ConditioningOutput
@@ -59,7 +59,7 @@ class CompelInvocation(BaseInvocation):
         description=FieldDescriptions.clip,
         input=Input.Connection,
     )
-    mask: Optional[MaskField] = InputField(
+    mask: Optional[TensorField] = InputField(
         default=None, description="A mask defining the region that this conditioning prompt applies to."
     )
 
@@ -270,7 +270,7 @@ class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
     target_height: int = InputField(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[MaskField] = InputField(
+    mask: Optional[TensorField] = InputField(
         default=None, description="A mask defining the region that this conditioning prompt applies to."
     )
 

invokeai/app/invocations/fields.py

@@ -203,10 +203,10 @@ class DenoiseMaskField(BaseModel):
     gradient: bool = Field(default=False, description="Used for gradient inpainting")
 
 
-class MaskField(BaseModel):
+class TensorField(BaseModel):
-    """A mask primitive field."""
+    """A tensor primitive field."""
 
-    mask_name: str = Field(description="The name of a spatial mask. dtype: bool, shape: (1, h, w).")
+    tensor_name: str = Field(description="The name of a tensor.")
 
 
 class LatentsField(BaseModel):
@@ -232,9 +232,9 @@ class ConditioningField(BaseModel):
     """A conditioning tensor primitive value"""
 
     conditioning_name: str = Field(description="The name of conditioning tensor")
-    mask: Optional[MaskField] = Field(
+    mask: Optional[TensorField] = Field(
         default=None,
-        description="The bool mask associated with this conditioning tensor. Excluded regions should be set to False, "
+        description="The mask associated with this conditioning tensor. Excluded regions should be set to False, "
         "included regions should be set to True.",
     )
 

invokeai/app/invocations/latent.py

@@ -380,7 +380,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
             mask = cond.mask
             if mask is not None:
-                mask = context.tensors.load(mask.mask_name)
+                mask = context.tensors.load(mask.tensor_name)
             text_embeddings_masks.append(mask)
 
         return text_embeddings, text_embeddings_masks

invokeai/app/invocations/mask.py

@@ -9,7 +9,7 @@ from invokeai.app.invocations.baseinvocation import (
     invocation,
     invocation_output,
 )
-from invokeai.app.invocations.fields import ColorField, ImageField, InputField, MaskField, OutputField, WithMetadata
+from invokeai.app.invocations.fields import ColorField, ImageField, InputField, OutputField, TensorField, WithMetadata
 from invokeai.app.invocations.primitives import MaskOutput
 
 
@@ -36,9 +36,9 @@ class RectangleMaskInvocation(BaseInvocation, WithMetadata):
             True
         )
 
-        mask_name = context.tensors.save(mask)
+        mask_tensor_name = context.tensors.save(mask)
         return MaskOutput(
-            mask=MaskField(mask_name=mask_name),
+            mask=TensorField(tensor_name=mask_tensor_name),
             width=self.width,
             height=self.height,
         )
@@ -51,7 +51,7 @@ class PromptColorPair(BaseModel):
 
 class PromptMaskPair(BaseModel):
     prompt: str
-    mask: MaskField
+    mask: TensorField
 
 
 default_prompt_color_pairs = [
@@ -92,15 +92,15 @@ class ExtractMasksAndPromptsInvocation(BaseInvocation):
             mask = torch.all(image_as_tensor == torch.tensor(pair.color.tuple()), dim=-1)
             # Add explicit channel dimension.
             mask = mask.unsqueeze(0)
-            mask_name = context.tensors.save(mask)
+            mask_tensor_name = context.tensors.save(mask)
-            prompt_mask_pairs.append(PromptMaskPair(prompt=pair.prompt, mask=MaskField(mask_name=mask_name)))
+            prompt_mask_pairs.append(PromptMaskPair(prompt=pair.prompt, mask=TensorField(tensor_name=mask_tensor_name)))
         return ExtractMasksAndPromptsOutput(prompt_mask_pairs=prompt_mask_pairs)
 
 
 @invocation_output("split_mask_prompt_pair_output")
 class SplitMaskPromptPairOutput(BaseInvocationOutput):
     prompt: str = OutputField()
-    mask: MaskField = OutputField()
+    mask: TensorField = OutputField()
 
 
 @invocation(

invokeai/app/invocations/primitives.py

@@ -14,8 +14,8 @@ from invokeai.app.invocations.fields import (
     Input,
     InputField,
     LatentsField,
-    MaskField,
     OutputField,
+    TensorField,
     UIComponent,
 )
 from invokeai.app.services.images.images_common import ImageDTO
@@ -414,7 +414,7 @@ class ColorInvocation(BaseInvocation):
 class MaskOutput(BaseInvocationOutput):
     """A torch mask tensor."""
 
-    mask: MaskField = OutputField(description="The mask.")
+    mask: TensorField = OutputField(description="The mask.")
     width: int = OutputField(description="The width of the mask in pixels.")
     height: int = OutputField(description="The height of the mask in pixels.")