70 lines
2.3 KiB
Markdown
70 lines
2.3 KiB
Markdown
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# Documentation
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- Class name: CLIPTextEncodeWithWeight __Inspire
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- Category: InspirePack/Util
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- Output node: False
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CLIPTextEncodeWithWeight节点旨在使用CLIP模型对文本输入进行编码，同时在编码过程中应用指定的强度和额外的权重调整。该节点允许自定义文本编码，通过调整编码的强度和偏差，实现对生成的嵌入向量更细致的控制。
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# Input types
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## Required
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- text
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- 待编码的文本输入。作为编码过程的主要内容，直接影响生成的嵌入向量。
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- Comfy dtype: STRING
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- Python dtype: str
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- clip
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- 用于编码文本的CLIP模型。决定了编码的方法和质量，影响最终的嵌入向量。
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- Comfy dtype: CLIP
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- Python dtype: object
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- strength
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- 编码强度的乘数。用于调整文本在嵌入空间中表示的强度。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- add_weight
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- 应用于编码的额外权重。允许对嵌入向量的偏差进行微调，提供了一种微妙改变其特征的方法。
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- Comfy dtype: FLOAT
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- Python dtype: float
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# Output types
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- conditioning
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- 输出是一个包含编码后文本及任何指定调整的条件对象。可直接用于后续的处理或生成任务。
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- Comfy dtype: CONDITIONING
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- Python dtype: list
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## Usage tips
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- Infra type: `GPU`
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- Common nodes: unknown
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## Source code
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```python
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class CLIPTextEncodeWithWeight:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"text": ("STRING", {"multiline": True}), "clip": ("CLIP", ),
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"strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
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"add_weight": ("FLOAT", {"default": 0.0, "min": -10.0, "max": 10.0, "step": 0.01}),
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}
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}
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RETURN_TYPES = ("CONDITIONING",)
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FUNCTION = "encode"
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CATEGORY = "InspirePack/Util"
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def encode(self, clip, text, strength, add_weight):
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tokens = clip.tokenize(text)
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if add_weight != 0 or strength != 1:
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for v in tokens.values():
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for vv in v:
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for i in range(0, len(vv)):
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vv[i] = (vv[i][0], vv[i][1] * strength + add_weight)
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cond, pooled = clip.encode_from_tokens(tokens, return_pooled=True)
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return ([[cond, {"pooled_output": pooled}]], )
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```
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