Set Model LoRA Hook 🎭🅐🅓

Documentation

• Class name: ADE_AttachLoraHookToConditioning
• Category: Animate Diff 🎭🅐🅓/conditioning/single cond ops
• Output node: False

This node is designed to attach LoRA hooks to conditioning data, enabling the dynamic modification of model behavior based on specified LoRA hooks. It plays a crucial role in customizing and controlling the conditioning process in generative models, particularly in the context of animation and differential rendering.

Input types

Required

• conditioning
  • The conditioning data to which the LoRA hook will be attached. This data dictates the model's behavior and output, and attaching a LoRA hook allows for dynamic adjustments.
  • Comfy dtype: CONDITIONING
  • Python dtype: List[Tuple[Any, Dict[str, Any]]]
• lora_hook
  • The LoRA hook to be attached to the conditioning data. This hook enables the modification of model parameters at runtime, allowing for enhanced control and customization of the generative process.
  • Comfy dtype: LORA_HOOK
  • Python dtype: LoraHookGroup

Output types

• conditioning
  • Comfy dtype: CONDITIONING
  • The modified conditioning data with the LoRA hook attached, enabling dynamic adjustments to the model's behavior.
  • Python dtype: List[Tuple[Any, Dict[str, Any]]]

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class SetModelLoraHook:
    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "conditioning": ("CONDITIONING",),
                "lora_hook": ("LORA_HOOK",),
            }
        }

    RETURN_TYPES = ("CONDITIONING",)
    CATEGORY = "Animate Diff 🎭🅐🅓/conditioning/single cond ops"
    FUNCTION = "attach_lora_hook"

    def attach_lora_hook(self, conditioning, lora_hook: LoraHookGroup):
        c = []
        for t in conditioning:
            n = [t[0], t[1].copy()]
            n[1]["lora_hook"] = lora_hook
            c.append(n)
        return (c, )