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tidy(nodes): use canonical capitalizations

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psychedelicious
2024-03-06 19:42:47 +11:00
parent c57f6ee885
commit 132790eebe
8 changed files with 70 additions and 71 deletions
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26
invokeai/app/invocations/compel.py
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@ -20,7 +20,7 @@ from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
from invokeai.backend.util.devices import torch_dtype
from .baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
from .model import ClipField
from .model import CLIPField
# unconditioned: Optional[torch.Tensor]
@ -46,7 +46,7 @@ class CompelInvocation(BaseInvocation):
description=FieldDescriptions.compel_prompt,
ui_component=UIComponent.Textarea,
)
clip: ClipField = InputField(
clip: CLIPField = InputField(
title="CLIP",
description=FieldDescriptions.clip,
input=Input.Connection,
@ -127,7 +127,7 @@ class SDXLPromptInvocationBase:
def run_clip_compel(
self,
context: InvocationContext,
clip_field: ClipField,
clip_field: CLIPField,
prompt: str,
get_pooled: bool,
lora_prefix: str,
@ -253,8 +253,8 @@ class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
crop_left: int = InputField(default=0, description="")
target_width: int = InputField(default=1024, description="")
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")
clip: CLIPField = InputField(description=FieldDescriptions.clip, input=Input.Connection, title="CLIP 1")
clip2: CLIPField = InputField(description=FieldDescriptions.clip, input=Input.Connection, title="CLIP 2")
@torch.no_grad()
def invoke(self, context: InvocationContext) -> ConditioningOutput:
@ -340,7 +340,7 @@ class SDXLRefinerCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase
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)
clip2: ClipField = InputField(description=FieldDescriptions.clip, input=Input.Connection)
clip2: CLIPField = InputField(description=FieldDescriptions.clip, input=Input.Connection)
@torch.no_grad()
def invoke(self, context: InvocationContext) -> ConditioningOutput:
@ -370,10 +370,10 @@ class SDXLRefinerCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase
@invocation_output("clip_skip_output")
class ClipSkipInvocationOutput(BaseInvocationOutput):
"""Clip skip node output"""
class CLIPSkipInvocationOutput(BaseInvocationOutput):
"""CLIP skip node output"""
clip: Optional[ClipField] = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP")
clip: Optional[CLIPField] = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP")
@invocation(
@ -383,15 +383,15 @@ class ClipSkipInvocationOutput(BaseInvocationOutput):
category="conditioning",
version="1.0.0",
)
class ClipSkipInvocation(BaseInvocation):
class CLIPSkipInvocation(BaseInvocation):
"""Skip layers in clip text_encoder model."""
clip: ClipField = InputField(description=FieldDescriptions.clip, input=Input.Connection, title="CLIP")
clip: CLIPField = InputField(description=FieldDescriptions.clip, input=Input.Connection, title="CLIP")
skipped_layers: int = InputField(default=0, ge=0, description=FieldDescriptions.skipped_layers)
def invoke(self, context: InvocationContext) -> ClipSkipInvocationOutput:
def invoke(self, context: InvocationContext) -> CLIPSkipInvocationOutput:
self.clip.skipped_layers += self.skipped_layers
return ClipSkipInvocationOutput(
return CLIPSkipInvocationOutput(
clip=self.clip,
)