175 lines
6.2 KiB
Markdown
175 lines
6.2 KiB
Markdown
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# Documentation
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- Class name: ttN pipeLoraStack
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- Category: ttN/pipe
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- Output node: False
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- Repo Ref: https://github.com/comfyanonymous/ComfyUI
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ttN pipeLoraStack节点旨在通过堆叠LoRA调整来动态增强和修改模型和剪辑的功能，这些调整基于指定的配置。它允许用户通过应用学习到的仿射变换来自定义模型和剪辑的行为，使用户能够精确地微调他们的生成过程。
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# Input types
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## Required
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- toggle
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- 决定是否应用LoRA堆栈，作为启用或禁用堆叠过程的开关。
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- Comfy dtype: COMBO[BOOLEAN]
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- Python dtype: bool
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- mode
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- 指定LoRA调整的操作模式，区分简单和高级配置，用于应用模型和剪辑强度修改。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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- num_loras
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- 表示要应用的LoRA调整数量，允许堆叠多层修改。
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- Comfy dtype: INT
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- Python dtype: int
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## Optional
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- optional_pipe
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- 一个可选的管道配置，如果提供，可以用LoRA调整来增强；否则，将生成一个新的配置。
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- Comfy dtype: PIPE_LINE
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- Python dtype: dict or None
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- model_override
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- 允许在可选管道中覆盖模型组件，便于自定义模型调整。
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- Comfy dtype: MODEL
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- Python dtype: object or None
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- clip_override
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- 允许在可选管道中覆盖剪辑组件，便于自定义剪辑调整。
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- Comfy dtype: CLIP
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- Python dtype: object or None
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- optional_lora_stack
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- 一个预定义的LoRA调整列表，可以选择性地包含用于堆叠，提供了导入现有配置或添加到现有配置的方法。
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- Comfy dtype: LORA_STACK
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- Python dtype: list of tuples or None
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- lora_i_name
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- 指定要应用的第i个LoRA调整的名称，使能够识别和应用特定的LoRA变换。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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- lora_i_strength
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- 在简单模式下定义第i个LoRA调整对模型和剪辑的强度，允许统一的修改强度。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- lora_i_model_strength
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- 在高级模式下指定应用于模型的第i个LoRA调整的强度，使模型变换能够有差异化的强度。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- lora_i_clip_strength
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- 在高级模式下指定应用于剪辑的第i个LoRA调整的强度，使剪辑变换能够有差异化的强度。
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- Comfy dtype: FLOAT
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- Python dtype: float
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# Output types
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- optional_pipe
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- 返回应用LoRA堆栈后增强或新创建的管道配置。
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- Comfy dtype: PIPE_LINE
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- Python dtype: dict
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- lora_stack
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- 提供应用的LoRA调整列表，详细说明对模型和剪辑所做的修改。
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- Comfy dtype: LORA_STACK
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- Python dtype: list of tuples or None
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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 ttN_pipeLoraStack:
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version = '1.1.1'
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(s):
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inputs = {
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"required": {
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"toggle": ([True, False],),
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"mode": (["simple", "advanced"],),
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"num_loras": ("INT", {"default": 1, "min": 0, "max": 20}),
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},
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"optional": {
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"optional_pipe": ("PIPE_LINE", {"default": None}),
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"model_override": ("MODEL",),
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"clip_override": ("CLIP",),
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"optional_lora_stack": ("LORA_STACK",),
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},
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"hidden": {
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"ttNnodeVersion": (ttN_pipeLoraStack.version),
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},
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}
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for i in range(1, 21):
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inputs["optional"][f"lora_{i}_name"] = (["None"] + folder_paths.get_filename_list("loras"),{"default": "None"})
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inputs["optional"][f"lora_{i}_strength"] = ("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.01})
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inputs["optional"][f"lora_{i}_model_strength"] = ("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.01})
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inputs["optional"][f"lora_{i}_clip_strength"] = ("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.01})
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return inputs
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RETURN_TYPES = ("PIPE_LINE", "LORA_STACK",)
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RETURN_NAMES = ("optional_pipe","lora_stack",)
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FUNCTION = "stack"
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CATEGORY = "ttN/pipe"
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def stack(self, toggle, mode, num_loras, optional_pipe=None, lora_stack=None, model_override=None, clip_override=None, **kwargs):
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if (toggle in [False, None, "False"]) or not kwargs:
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return optional_pipe, None
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loras = []
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# Import Stack values
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if lora_stack is not None:
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loras.extend([l for l in lora_stack if l[0] != "None"])
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# Import Lora values
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for i in range(1, num_loras + 1):
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lora_name = kwargs.get(f"lora_{i}_name")
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if not lora_name or lora_name == "None":
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continue
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if mode == "simple":
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lora_strength = float(kwargs.get(f"lora_{i}_strength"))
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loras.append((lora_name, lora_strength, lora_strength))
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elif mode == "advanced":
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model_strength = float(kwargs.get(f"lora_{i}_model_strength"))
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clip_strength = float(kwargs.get(f"lora_{i}_clip_strength"))
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loras.append((lora_name, model_strength, clip_strength))
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if not loras:
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return optional_pipe, None
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if loras and not optional_pipe:
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return optional_pipe, loras
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# Load Loras
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model = model_override or optional_pipe.get("model")
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clip = clip_override or optional_pipe.get("clip")
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if not model or not clip:
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return optional_pipe, loras
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for lora in loras:
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model, clip = loader.load_lora(lora[0], model, clip, lora[1], lora[2])
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new_pipe = {
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"model": model,
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"positive": optional_pipe["positive"],
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"negative": optional_pipe["negative"],
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"vae": optional_pipe["vae"],
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"clip": clip,
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"samples": optional_pipe["samples"],
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"images": optional_pipe["images"],
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"seed": optional_pipe["seed"],
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"loader_settings": optional_pipe["loader_settings"],
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}
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del optional_pipe
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return new_pipe, loras
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```
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