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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
69 lines
2.3 KiB
Python
69 lines
2.3 KiB
Python
from typing_extensions import override
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from comfy_api.latest import ComfyExtension, io
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class CLIPTextEncodeControlnet(io.ComfyNode):
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@classmethod
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def define_schema(cls) -> io.Schema:
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return io.Schema(
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node_id="CLIPTextEncodeControlnet",
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category="_for_testing/conditioning",
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inputs=[
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io.Clip.Input("clip"),
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io.Conditioning.Input("conditioning"),
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io.String.Input("text", multiline=True, dynamic_prompts=True),
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],
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outputs=[io.Conditioning.Output()],
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is_experimental=True,
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)
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@classmethod
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def execute(cls, clip, conditioning, text) -> io.NodeOutput:
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tokens = clip.tokenize(text)
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cond, pooled = clip.encode_from_tokens(tokens, return_pooled=True)
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c = []
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for t in conditioning:
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n = [t[0], t[1].copy()]
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n[1]['cross_attn_controlnet'] = cond
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n[1]['pooled_output_controlnet'] = pooled
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c.append(n)
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return io.NodeOutput(c)
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class T5TokenizerOptions(io.ComfyNode):
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@classmethod
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def define_schema(cls) -> io.Schema:
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return io.Schema(
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node_id="T5TokenizerOptions",
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category="_for_testing/conditioning",
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inputs=[
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io.Clip.Input("clip"),
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io.Int.Input("min_padding", default=0, min=0, max=10000, step=1, advanced=True),
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io.Int.Input("min_length", default=0, min=0, max=10000, step=1, advanced=True),
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],
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outputs=[io.Clip.Output()],
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is_experimental=True,
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)
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@classmethod
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def execute(cls, clip, min_padding, min_length) -> io.NodeOutput:
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clip = clip.clone()
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for t5_type in ["t5xxl", "pile_t5xl", "t5base", "mt5xl", "umt5xxl"]:
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clip.set_tokenizer_option("{}_min_padding".format(t5_type), min_padding)
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clip.set_tokenizer_option("{}_min_length".format(t5_type), min_length)
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return io.NodeOutput(clip)
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class CondExtension(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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CLIPTextEncodeControlnet,
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T5TokenizerOptions,
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]
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async def comfy_entrypoint() -> CondExtension:
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return CondExtension()
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