65 lines
3.2 KiB
Markdown
65 lines
3.2 KiB
Markdown
# Documentation
|
|
- Class name: LoadResAdapterNormalization
|
|
- Category: KJNodes/experimental
|
|
- Output node: False
|
|
- Repo Ref: https://github.com/kijai/ComfyUI-KJNodes.git
|
|
|
|
方法 `load_res_adapter` 旨在将 ResAdapter 标准化权重集成到给定模型中。它确保从指定路径正确加载权重并将其应用于模型的标准化层，增强了模型处理具有标准化特征的输入数据的能力。
|
|
|
|
# Input types
|
|
## Required
|
|
- model
|
|
- 参数 'model' 是必需的，因为它代表了将要应用 ResAdapter 标准化权重的机器学习模型。它是一个关键组件，决定了节点的功能和标准化过程的结果。
|
|
- Comfy dtype: MODEL
|
|
- Python dtype: torch.nn.Module
|
|
- resadapter_path
|
|
- 参数 'resadapter_path' 指定了存储 ResAdapter 标准化权重的目录路径。对于节点来说，找到并加载正确的权重至关重要，以确保成功地将标准化应用于模型。
|
|
- Comfy dtype: folder_paths.get_filename_list('checkpoints')
|
|
- Python dtype: List[str]
|
|
|
|
# Output types
|
|
- model_clone
|
|
- 输出 'model_clone' 是应用了 ResAdapter 标准化权重的原始模型。它标志权重成功集成，允许模型使用标准化特性以改进数据处理。
|
|
- Comfy dtype: MODEL
|
|
- Python dtype: torch.nn.Module
|
|
|
|
# Usage tips
|
|
- Infra type: CPU
|
|
|
|
# Source code
|
|
```
|
|
class LoadResAdapterNormalization:
|
|
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {'required': {'model': ('MODEL',), 'resadapter_path': (folder_paths.get_filename_list('checkpoints'),)}}
|
|
RETURN_TYPES = ('MODEL',)
|
|
FUNCTION = 'load_res_adapter'
|
|
CATEGORY = 'KJNodes/experimental'
|
|
|
|
def load_res_adapter(self, model, resadapter_path):
|
|
print('ResAdapter: Checking ResAdapter path')
|
|
resadapter_full_path = folder_paths.get_full_path('checkpoints', resadapter_path)
|
|
if not os.path.exists(resadapter_full_path):
|
|
raise Exception('Invalid model path')
|
|
else:
|
|
print('ResAdapter: Loading ResAdapter normalization weights')
|
|
prefix_to_remove = 'diffusion_model.'
|
|
model_clone = model.clone()
|
|
norm_state_dict = comfy.utils.load_torch_file(resadapter_full_path)
|
|
new_values = {key[len(prefix_to_remove):]: value for (key, value) in norm_state_dict.items() if key.startswith(prefix_to_remove)}
|
|
print('ResAdapter: Attempting to add patches with ResAdapter weights')
|
|
try:
|
|
for key in model.model.diffusion_model.state_dict().keys():
|
|
if key in new_values:
|
|
original_tensor = model.model.diffusion_model.state_dict()[key]
|
|
new_tensor = new_values[key].to(model.model.diffusion_model.dtype)
|
|
if original_tensor.shape == new_tensor.shape:
|
|
model_clone.add_object_patch(f'diffusion_model.{key}.data', new_tensor)
|
|
else:
|
|
print('ResAdapter: No match for key: ', key)
|
|
except:
|
|
raise Exception('Could not patch model, this way of patching was added to ComfyUI on March 3rd 2024, is your ComfyUI up to date?')
|
|
print('ResAdapter: Added resnet normalization patches')
|
|
return (model_clone,)
|
|
``` |