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convert CLIPTextEncodeSDXL nodes to V3 schema (#9716)

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Alexander Piskun 2025-09-27 00:15:44 +03:00 committed by GitHub
parent 2103e39335
commit cd66d72b46
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1 changed files with 55 additions and 38 deletions
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93
comfy_extras/nodes_clip_sdxl.py
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@ -1,43 +1,52 @@
from nodes import MAX_RESOLUTION
from typing_extensions import override
class CLIPTextEncodeSDXLRefiner:
import nodes
from comfy_api.latest import ComfyExtension, io
class CLIPTextEncodeSDXLRefiner(io.ComfyNode):
@classmethod
def INPUT_TYPES(s):
return {"required": {
"ascore": ("FLOAT", {"default": 6.0, "min": 0.0, "max": 1000.0, "step": 0.01}),
"width": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"height": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"text": ("STRING", {"multiline": True, "dynamicPrompts": True}), "clip": ("CLIP", ),
}}
RETURN_TYPES = ("CONDITIONING",)
FUNCTION = "encode"
def define_schema(cls):
return io.Schema(
node_id="CLIPTextEncodeSDXLRefiner",
category="advanced/conditioning",
inputs=[
io.Float.Input("ascore", default=6.0, min=0.0, max=1000.0, step=0.01),
io.Int.Input("width", default=1024, min=0, max=nodes.MAX_RESOLUTION),
io.Int.Input("height", default=1024, min=0, max=nodes.MAX_RESOLUTION),
io.String.Input("text", multiline=True, dynamic_prompts=True),
io.Clip.Input("clip"),
],
outputs=[io.Conditioning.Output()],
)
CATEGORY = "advanced/conditioning"
def encode(self, clip, ascore, width, height, text):
@classmethod
def execute(cls, clip, ascore, width, height, text) -> io.NodeOutput:
tokens = clip.tokenize(text)
return (clip.encode_from_tokens_scheduled(tokens, add_dict={"aesthetic_score": ascore, "width": width, "height": height}), )
return io.NodeOutput(clip.encode_from_tokens_scheduled(tokens, add_dict={"aesthetic_score": ascore, "width": width, "height": height}))
class CLIPTextEncodeSDXL:
class CLIPTextEncodeSDXL(io.ComfyNode):
@classmethod
def INPUT_TYPES(s):
return {"required": {
"clip": ("CLIP", ),
"width": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"height": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"crop_w": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION}),
"crop_h": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION}),
"target_width": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"target_height": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"text_g": ("STRING", {"multiline": True, "dynamicPrompts": True}),
"text_l": ("STRING", {"multiline": True, "dynamicPrompts": True}),
}}
RETURN_TYPES = ("CONDITIONING",)
FUNCTION = "encode"
def define_schema(cls):
return io.Schema(
node_id="CLIPTextEncodeSDXL",
category="advanced/conditioning",
inputs=[
io.Clip.Input("clip"),
io.Int.Input("width", default=1024, min=0, max=nodes.MAX_RESOLUTION),
io.Int.Input("height", default=1024, min=0, max=nodes.MAX_RESOLUTION),
io.Int.Input("crop_w", default=0, min=0, max=nodes.MAX_RESOLUTION),
io.Int.Input("crop_h", default=0, min=0, max=nodes.MAX_RESOLUTION),
io.Int.Input("target_width", default=1024, min=0, max=nodes.MAX_RESOLUTION),
io.Int.Input("target_height", default=1024, min=0, max=nodes.MAX_RESOLUTION),
io.String.Input("text_g", multiline=True, dynamic_prompts=True),
io.String.Input("text_l", multiline=True, dynamic_prompts=True),
],
outputs=[io.Conditioning.Output()],
)
CATEGORY = "advanced/conditioning"
def encode(self, clip, width, height, crop_w, crop_h, target_width, target_height, text_g, text_l):
@classmethod
def execute(cls, clip, width, height, crop_w, crop_h, target_width, target_height, text_g, text_l) -> io.NodeOutput:
tokens = clip.tokenize(text_g)
tokens["l"] = clip.tokenize(text_l)["l"]
if len(tokens["l"]) != len(tokens["g"]):
@ -46,9 +55,17 @@ class CLIPTextEncodeSDXL:
tokens["l"] += empty["l"]
while len(tokens["l"]) > len(tokens["g"]):
tokens["g"] += empty["g"]
return (clip.encode_from_tokens_scheduled(tokens, add_dict={"width": width, "height": height, "crop_w": crop_w, "crop_h": crop_h, "target_width": target_width, "target_height": target_height}), )
return io.NodeOutput(clip.encode_from_tokens_scheduled(tokens, add_dict={"width": width, "height": height, "crop_w": crop_w, "crop_h": crop_h, "target_width": target_width, "target_height": target_height}))
NODE_CLASS_MAPPINGS = {
"CLIPTextEncodeSDXLRefiner": CLIPTextEncodeSDXLRefiner,
"CLIPTextEncodeSDXL": CLIPTextEncodeSDXL,
}
class ClipSdxlExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[io.ComfyNode]]:
return [
CLIPTextEncodeSDXLRefiner,
CLIPTextEncodeSDXL,
]
async def comfy_entrypoint() -> ClipSdxlExtension:
return ClipSdxlExtension()