87 lines
3.0 KiB
Markdown
87 lines
3.0 KiB
Markdown
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# Documentation
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- Class name: AV_LoraListLoader
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- Category: Art Venture/Loaders
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- Output node: False
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- Repo Ref: https://github.com/comfyanonymous/ComfyUI
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AV_LoraListLoader节点旨在根据提供的数据和配置加载和堆叠LoRA模型列表。它通过按顺序应用多个LoRA调整来促进模型和剪辑的动态增强，从而通过LoRA参数实现复杂的模型行为修改。
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# Input types
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## Required
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- model
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- 'model'参数代表将应用LoRA调整的初始模型。它对于定义LoRA堆叠过程的起点至关重要。
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- Comfy dtype: MODEL
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- Python dtype: str
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- clip
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- 'clip'参数表示将与主模型一起通过LoRA调整进行修改的初始剪辑模型。它在堆叠过程中扮演关键角色，因为它会受到修改。
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- Comfy dtype: CLIP
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- Python dtype: str
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- data
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- 'data'参数包含要加载和应用的LoRA模型列表，以JSON格式呈现。它对于指定哪些LoRA模型及其相应的强度将影响模型和剪辑至关重要。
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- Comfy dtype: STRING
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- Python dtype: str
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## Optional
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- base_url
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- 'base_url'参数提供获取本地未找到的LoRA模型的基础URL。它有助于从外部源动态加载LoRA模型。
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- Comfy dtype: STRING
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- Python dtype: str
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# Output types
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- model
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- 返回应用指定LoRA调整后的修改模型。
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- Comfy dtype: MODEL
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- Python dtype: str
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- clip
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- 返回应用LoRA调整后的修改剪辑模型。
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- Comfy dtype: CLIP
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- Python dtype: str
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## Usage tips
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- Infra type: `CPU`
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- Common nodes: unknown
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## Source code
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```python
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class AVLoraListLoader(AVLoraListStacker):
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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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"model": ("MODEL",),
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"clip": ("CLIP",),
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"data": ("STRING", {"default": "", "multiline": True, "dynamicPrompts": False}),
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},
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"optional": {"base_url": ("STRING", {"default": lora_cloud_front_url})},
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}
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RETURN_TYPES = ("MODEL", "CLIP")
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def load_list_lora(self, model, clip, data, base_url=lora_cloud_front_url):
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lora_params = self.parse_lora_list(data, base_url=base_url)
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if len(lora_params) == 0:
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return (model, clip)
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def recursive_load_lora(lora_params, model, clip, id, folder_paths):
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if len(lora_params) == 0:
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return model, clip
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lora_name, strength_model, strength_clip = lora_params[0]
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lora_path = folder_paths.get_full_path("loras", lora_name)
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lora_model, lora_clip = comfy.sd.load_lora_for_models(
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model, clip, comfy.utils.load_torch_file(lora_path), strength_model, strength_clip
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)
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# Call the function again with the new lora_model and lora_clip and the remaining tuples
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return recursive_load_lora(lora_params[1:], lora_model, lora_clip, id, folder_paths)
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lora_model, lora_clip = recursive_load_lora(lora_params, model, clip, id, folder_paths)
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return (lora_model, lora_clip)
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```
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