97 lines
3.7 KiB
Markdown
97 lines
3.7 KiB
Markdown
# 🚫AnimateDiff Loader [DEPRECATED] 🎭🅐🅓
|
|
## Documentation
|
|
- Class name: AnimateDiffLoaderV1
|
|
- Category:
|
|
- Output node: False
|
|
- Repo Ref: https://github.com/Kosinkadink/ComfyUI-AnimateDiff-Evolved.git
|
|
|
|
此节点用于初始化和准备AnimateDiff模型，便于其进行动画生成任务。它抽象了加载模型的复杂性，确保其正确设置以供后续使用。
|
|
|
|
## Input types
|
|
### Required
|
|
- model
|
|
- 该参数用于指定要加载的AnimateDiff模型，使节点能够正确初始化和准备模型以进行动画任务。
|
|
- Comfy dtype: MODEL
|
|
- Python dtype: str
|
|
- latents
|
|
- 该参数允许指定初始化模型可能需要的潜在向量，提供一种自定义模型初始状态的方法。
|
|
- Comfy dtype: LATENT
|
|
- Python dtype: str
|
|
- model_name
|
|
- 用于从可用选项中选择特定运动模型，该参数确保根据提供的名称加载正确版本的AnimateDiff模型。
|
|
- Comfy dtype: COMBO[STRING]
|
|
- Python dtype: str
|
|
- unlimited_area_hack
|
|
- 一个布尔参数，启用时应用特定的黑客技术以绕过可动画区域的限制，为动画任务提供更多灵活性。
|
|
- Comfy dtype: BOOLEAN
|
|
- Python dtype: bool
|
|
- beta_schedule
|
|
- 指定在模型操作期间使用的beta计划，影响AnimateDiff模型的行为和性能。
|
|
- Comfy dtype: COMBO[STRING]
|
|
- Python dtype: str
|
|
|
|
## Output types
|
|
- model
|
|
- Comfy dtype: MODEL
|
|
- 表示已加载的AnimateDiff模型，准备进行动画生成任务。
|
|
- Python dtype: str
|
|
- latent
|
|
- Comfy dtype: LATENT
|
|
- 输出与已加载模型相关的潜在向量，可用于进一步的自定义或动画过程。
|
|
- Python dtype: str
|
|
|
|
## Usage tips
|
|
- Infra type: CPU
|
|
- Common nodes: unknown
|
|
|
|
## Source code
|
|
```python
|
|
class AnimateDiffLoader_Deprecated:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"model": ("MODEL",),
|
|
"latents": ("LATENT",),
|
|
"model_name": (get_available_motion_models(),),
|
|
"unlimited_area_hack": ("BOOLEAN", {"default": False},),
|
|
"beta_schedule": (BetaSchedules.get_alias_list_with_first_element(BetaSchedules.SQRT_LINEAR),),
|
|
},
|
|
}
|
|
|
|
RETURN_TYPES = ("MODEL", "LATENT")
|
|
CATEGORY = ""
|
|
FUNCTION = "load_mm_and_inject_params"
|
|
|
|
def load_mm_and_inject_params(
|
|
self,
|
|
model: ModelPatcher,
|
|
latents: Dict[str, torch.Tensor],
|
|
model_name: str, unlimited_area_hack: bool, beta_schedule: str,
|
|
):
|
|
# load motion module
|
|
motion_model = load_motion_module_gen1(model_name, model)
|
|
# get total frames
|
|
init_frames_len = len(latents["samples"]) # deprecated - no longer used for anything lol
|
|
# set injection params
|
|
params = InjectionParams(
|
|
unlimited_area_hack=unlimited_area_hack,
|
|
apply_mm_groupnorm_hack=True,
|
|
model_name=model_name,
|
|
apply_v2_properly=False,
|
|
)
|
|
# inject for use in sampling code
|
|
model = ModelPatcherAndInjector.create_from(model, hooks_only=True)
|
|
model.motion_models = MotionModelGroup(motion_model)
|
|
model.motion_injection_params = params
|
|
|
|
# save model sampling from BetaSchedule as object patch
|
|
# if autoselect, get suggested beta_schedule from motion model
|
|
if beta_schedule == BetaSchedules.AUTOSELECT and not model.motion_models.is_empty():
|
|
beta_schedule = model.motion_models[0].model.get_best_beta_schedule(log=True)
|
|
new_model_sampling = BetaSchedules.to_model_sampling(beta_schedule, model)
|
|
if new_model_sampling is not None:
|
|
model.add_object_patch("model_sampling", new_model_sampling)
|
|
|
|
del motion_model
|
|
return (model, latents) |