mirror of
https://github.com/comfyanonymous/ComfyUI.git
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61 lines
1.9 KiB
Python
61 lines
1.9 KiB
Python
from __future__ import annotations
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from comfy_api.v3 import io
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class CLIPTextEncodeControlnet(io.ComfyNodeV3):
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@classmethod
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def define_schema(cls) -> io.SchemaV3:
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return io.SchemaV3(
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node_id="CLIPTextEncodeControlnet_V3",
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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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)
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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.ComfyNodeV3):
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@classmethod
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def define_schema(cls) -> io.SchemaV3:
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return io.SchemaV3(
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node_id="T5TokenizerOptions_V3",
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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),
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io.Int.Input("min_length", default=0, min=0, max=10000, step=1),
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],
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outputs=[io.Clip.Output()],
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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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NODES_LIST = [
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CLIPTextEncodeControlnet,
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T5TokenizerOptions,
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]
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