feat: 增加节点文档

2024-05-26 20:35:16 +08:00
parent 214e62dba4
commit 79bb3e381d
1686 changed files with 114318 additions and 23 deletions
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+# Documentation
+- Class name: AnimateDiffModuleLoader
+- Category: Animate Diff
+- Output node: False
+- Repo Ref: https://github.com/ArtVentureX/comfyui-animatediff.git
+
+该节点旨在动画框架内管理和操作运动模块，专注于集成和应用高级运动技术，以增强动画的动态性和流畅性。
+
+# Input types
+## Required
+- model_name
+    - 模型名称对于识别要加载和操作的特定运动模块至关重要。它决定了动画资产的来源，并为后续操作奠定了基础。
+    - Comfy dtype: string
+    - Python dtype: str
+## Optional
+- lora_stack
+    - LoRa堆栈是一个可选参数，提供后允许通过逐层调整来微调运动模块。它增强了动画适应性和定制性，以满足特定要求。
+    - Comfy dtype: list
+    - Python dtype: List[Tuple[Dict[str, torch.Tensor], float]]
+
+# Output types
+- motion_module
+    - 输出的运动模块是节点处理的结果，代表最终确定和优化的动画模块，准备在动画流程中使用。
+    - Comfy dtype: object
+    - Python dtype: MotionWrapper
+
+# Usage tips
+- Infra type: CPU
+
+# Source code
+```
+class AnimateDiffModuleLoader:
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {'required': {'model_name': (get_available_models(),)}, 'optional': {'lora_stack': ('MOTION_LORA_STACK',)}}
+    RETURN_TYPES = ('MOTION_MODULE',)
+    CATEGORY = 'Animate Diff'
+    FUNCTION = 'load_motion_module'
+
+    def inject_loras(self, motion_module: MotionWrapper, lora_stack: List[Tuple[Dict[str, Tensor], float]]):
+        for lora in lora_stack:
+            (state_dict, alpha) = lora
+            for key in state_dict:
+                layer_infos = key.split('.')
+                curr_layer = motion_module
+                while len(layer_infos) > 0:
+                    temp_name = layer_infos.pop(0)
+                    curr_layer = curr_layer.__getattr__(temp_name)
+                curr_layer.weight.data += alpha * state_dict[key].to(curr_layer.weight.data.device)
+
+    def eject_loras(self, motion_module: MotionWrapper, lora_stack: List[Tuple[float, Dict[str, Tensor]]]):
+        lora_stack.reverse()
+        for lora in lora_stack:
+            (state_dict, alpha) = lora
+            for key in state_dict:
+                layer_infos = key.split('.')
+                curr_layer = motion_module
+                while len(layer_infos) > 0:
+                    temp_name = layer_infos.pop(0)
+                    curr_layer = curr_layer.__getattr__(temp_name)
+                curr_layer.weight.data -= alpha * state_dict[key].to(curr_layer.weight.data.device)
+
+    def load_motion_module(self, model_name: str, lora_stack: List=None):
+        motion_module = load_motion_module(model_name)
+        if motion_module.is_v2:
+            if hasattr(motion_module, 'lora_stack') and isinstance(motion_module.lora_stack, list):
+                self.eject_loras(motion_module, motion_module.lora_stack)
+                delattr(motion_module, 'lora_stack')
+            if isinstance(lora_stack, list):
+                self.inject_loras(motion_module, lora_stack)
+                setattr(motion_module, 'lora_stack', lora_stack)
+        elif isinstance(lora_stack, list):
+            logger.warning('LoRA is provided but only motion module v2 is supported.')
+        return (motion_module,)
+```