52 lines
1.4 KiB
Markdown
52 lines
1.4 KiB
Markdown
|
|
# Documentation
|
|
- Class name: LoadInstanceScaleUNode
|
|
- Category: instance/loaders
|
|
- Output node: False
|
|
|
|
该节点旨在从指定文件名加载ScaleU模型的特定实例。它利用检查点检索机制来加载模型的状态，并为实例扩散过程中的后续使用准备ScaleU网络。
|
|
|
|
# Input types
|
|
## Required
|
|
- model_filename
|
|
- 指定要加载的模型文件名。这个参数至关重要，因为它决定了要检索和加载哪个特定的ScaleU模型实例以供使用。
|
|
- Comfy dtype: COMBO[STRING]
|
|
- Python dtype: str
|
|
|
|
# Output types
|
|
- scaleu
|
|
- 返回一个字典，其中包含ScaleU模型实例的列表，可随时集成到实例扩散框架中。
|
|
- Comfy dtype: SCALEU
|
|
- Python dtype: Dict[str, List[torch.nn.Module]]
|
|
|
|
|
|
## Usage tips
|
|
- Infra type: `CPU`
|
|
- Common nodes: unknown
|
|
|
|
|
|
## Source code
|
|
```python
|
|
class LoadInstanceScaleUNode:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {"required": {
|
|
"model_filename": (get_model_list(constants.INSTANCE_SCALEU_DIR),),
|
|
}}
|
|
|
|
RETURN_TYPES = ("SCALEU",)
|
|
FUNCTION = "load_model"
|
|
|
|
CATEGORY = "instance/loaders"
|
|
|
|
def load_model(self, model_filename: str):
|
|
checkpoint = load_checkpoint(
|
|
constants.INSTANCE_SCALEU_DIR, model_filename)
|
|
scaleu_list = prepare_scaleu_nets(checkpoint)
|
|
scaleu = {
|
|
'model_list': scaleu_list
|
|
}
|
|
return (scaleu,)
|
|
|
|
```
|