51 lines
2.0 KiB
Markdown
51 lines
2.0 KiB
Markdown
# Documentation
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- Class name: KfConditioningAdd
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- Category: CATEGORY
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- Output node: False
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- Repo Ref: https://github.com/dmarx/ComfyUI-Keyframed
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该节点用于将两个调节输入相加以产生一个综合的调节输出。它强调数据的整合以增强整体调节影响，同时不改变各自的数据结构。
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# Input types
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## Required
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- conditioning_1
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- 第一个调节输入对于节点的操作至关重要，提供了将与第二个输入结合的初始数据集。它为整合过程奠定了基础。
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- Comfy dtype: CONDITIONING
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- Python dtype: Tuple[torch.Tensor, Dict[str, Any]]
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- conditioning_2
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- 第二个调节输入补充了第一个输入，允许将另一个数据集添加到混合中。这对于实现全面的调节结果至关重要。
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- Comfy dtype: CONDITIONING
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- Python dtype: Tuple[torch.Tensor, Dict[str, Any]]
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# Output types
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- CONDITIONING
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- 输出是两个输入相加后的综合调节集。它代表了可以进一步在过程中利用的增强调节影响。
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- Comfy dtype: CONDITIONING
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- Python dtype: List[Tuple[torch.Tensor, Dict[str, Any]]]
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# Usage tips
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- Infra type: CPU
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# Source code
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```
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class KfConditioningAdd:
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CATEGORY = CATEGORY
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FUNCTION = 'main'
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RETURN_TYPES = ('CONDITIONING',)
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@classmethod
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def INPUT_TYPES(s):
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return {'required': {'conditioning_1': ('CONDITIONING',), 'conditioning_2': ('CONDITIONING',)}}
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def main(self, conditioning_1, conditioning_2):
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conditioning_1 = deepcopy(conditioning_1)
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conditioning_2 = deepcopy(conditioning_2)
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assert len(conditioning_1) == len(conditioning_2)
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outv = []
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for (i, ((c1_tensor, c1_dict), (c2_tensor, c2_dict))) in enumerate(zip(conditioning_1, conditioning_2)):
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c1_tensor += c2_tensor
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if 'pooled_output' in c1_dict and 'pooled_output' in c2_dict:
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c1_dict['pooled_output'] += c2_dict['pooled_output']
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outv.append((c1_tensor, c1_dict))
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return (outv,)
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``` |