55 lines
1.6 KiB
Markdown
55 lines
1.6 KiB
Markdown
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# Documentation
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- Class name: CLIPEncodeMultiple
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- Category: Bmad/conditioning
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- Output node: False
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CLIPEncodeMultiple节点旨在使用CLIP模型对多个输入进行编码，从而基于这些输入生成一系列条件。该节点抽象了处理多个输入的复杂性，并利用CLIP模型的能力为每个输入生成相关的条件。
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# Input types
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## Required
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- clip
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- 用于编码输入的CLIP模型。它对于确定输入如何被处理和编码成条件至关重要。
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- Comfy dtype: CLIP
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- Python dtype: torch.nn.Module
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- inputs_len
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- 指定要编码的输入数量。它影响迭代次数，从而影响输出条件列表的大小。
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- Comfy dtype: INT
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- Python dtype: int
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# Output types
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- conditioning
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- 从输入生成的条件列表。列表中的每个元素对应一个单独输入的条件。
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- Comfy dtype: CONDITIONING
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- Python dtype: List[torch.Tensor]
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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 CLIPEncodeMultiple(nodes.CLIPTextEncode):
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {
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"clip": ("CLIP",),
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"inputs_len": ("INT", {"default": 9, "min": 0, "max": 32}),
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}}
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RETURN_TYPES = ("CONDITIONING",)
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FUNCTION = "gen2"
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CATEGORY = "Bmad/conditioning"
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OUTPUT_IS_LIST = (True,)
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def gen2(self, clip, inputs_len, **kwargs):
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conds = []
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for i in range(inputs_len):
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arg_name = get_arg_name_from_multiple_inputs("string", i)
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conds.append(super().encode(clip, kwargs[arg_name])[0])
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return (conds,)
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```
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