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https://github.com/comfyanonymous/ComfyUI.git
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ae20354b69
Mark widgets as advanced across core, comfy_extras, and comfy_api_nodes to support the new collapsible advanced inputs section in the frontend. Changes: - 267 advanced markers in comfy_extras/ - 162 advanced markers in comfy_api_nodes/ - All files pass python3 -m py_compile verification Widgets marked advanced (hidden by default): - Scheduler internals: sigma_max, sigma_min, rho, mu, beta, alpha - Sampler internals: eta, s_noise, order, rtol, atol, h_init, pcoeff, etc. - Memory optimization: tile_size, overlap, temporal_size, temporal_overlap - Pipeline controls: add_noise, start_at_step, end_at_step - Timing controls: start_percent, end_percent - Layer selection: stop_at_clip_layer, layers, block_number - Video encoding: codec, crf, format - Device/dtype: device, noise_device, dtype, weight_dtype Widgets kept basic (always visible): - Core params: strength, steps, cfg, denoise, seed, width, height - Model selectors: ckpt_name, lora_name, vae_name, sampler_name - Common controls: upscale_method, crop, batch_size, fps, opacity Related: frontend PR #11939 Amp-Thread-ID: https://ampcode.com/threads/T-019c1734-6b61-702e-b333-f02c399963fc
72 lines
3.1 KiB
Python
72 lines
3.1 KiB
Python
from typing_extensions import override
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import nodes
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from comfy_api.latest import ComfyExtension, io
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class CLIPTextEncodeSDXLRefiner(io.ComfyNode):
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@classmethod
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def define_schema(cls):
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return io.Schema(
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node_id="CLIPTextEncodeSDXLRefiner",
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category="advanced/conditioning",
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inputs=[
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io.Float.Input("ascore", default=6.0, min=0.0, max=1000.0, step=0.01),
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io.Int.Input("width", default=1024, min=0, max=nodes.MAX_RESOLUTION),
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io.Int.Input("height", default=1024, min=0, max=nodes.MAX_RESOLUTION),
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io.String.Input("text", multiline=True, dynamic_prompts=True),
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io.Clip.Input("clip"),
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],
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outputs=[io.Conditioning.Output()],
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)
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@classmethod
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def execute(cls, clip, ascore, width, height, text) -> io.NodeOutput:
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tokens = clip.tokenize(text)
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return io.NodeOutput(clip.encode_from_tokens_scheduled(tokens, add_dict={"aesthetic_score": ascore, "width": width, "height": height}))
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class CLIPTextEncodeSDXL(io.ComfyNode):
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@classmethod
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def define_schema(cls):
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return io.Schema(
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node_id="CLIPTextEncodeSDXL",
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category="advanced/conditioning",
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inputs=[
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io.Clip.Input("clip"),
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io.Int.Input("width", default=1024, min=0, max=nodes.MAX_RESOLUTION),
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io.Int.Input("height", default=1024, min=0, max=nodes.MAX_RESOLUTION),
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io.Int.Input("crop_w", default=0, min=0, max=nodes.MAX_RESOLUTION, advanced=True),
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io.Int.Input("crop_h", default=0, min=0, max=nodes.MAX_RESOLUTION, advanced=True),
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io.Int.Input("target_width", default=1024, min=0, max=nodes.MAX_RESOLUTION),
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io.Int.Input("target_height", default=1024, min=0, max=nodes.MAX_RESOLUTION),
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io.String.Input("text_g", multiline=True, dynamic_prompts=True),
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io.String.Input("text_l", multiline=True, dynamic_prompts=True),
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],
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outputs=[io.Conditioning.Output()],
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)
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@classmethod
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def execute(cls, clip, width, height, crop_w, crop_h, target_width, target_height, text_g, text_l) -> io.NodeOutput:
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tokens = clip.tokenize(text_g)
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tokens["l"] = clip.tokenize(text_l)["l"]
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if len(tokens["l"]) != len(tokens["g"]):
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empty = clip.tokenize("")
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while len(tokens["l"]) < len(tokens["g"]):
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tokens["l"] += empty["l"]
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while len(tokens["l"]) > len(tokens["g"]):
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tokens["g"] += empty["g"]
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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}))
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class ClipSdxlExtension(ComfyExtension):
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@override
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async def get_node_list(self) -> list[type[io.ComfyNode]]:
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return [
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CLIPTextEncodeSDXLRefiner,
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CLIPTextEncodeSDXL,
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]
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async def comfy_entrypoint() -> ClipSdxlExtension:
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return ClipSdxlExtension()
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