59 lines
2.4 KiB
Markdown
59 lines
2.4 KiB
Markdown
# Sigma Schedule Split Combine 🎭🅐🅓
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## Documentation
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- Class name: ADE_SigmaScheduleSplitAndCombine
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- Category: Animate Diff 🎭🅐🅓/sample settings/sigma schedule
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- Output node: False
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- Repo Ref: https://github.com/Kosinkadink/ComfyUI-AnimateDiff-Evolved.git
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此节点旨在通过基于指定的权重和插值方法拆分和组合sigma计划来操作它们。它允许创建两个输入计划的混合新sigma计划，从而实现sigma值随时间的自定义进程。
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## Input types
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### Required
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- schedule_Start
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- 用于拆分和组合过程的起始sigma计划，决定新sigma计划的初始部分。
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- Comfy dtype: SIGMA_SCHEDULE
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- Python dtype: SigmaSchedule
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- schedule_End
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- 用于拆分和组合过程的结束sigma计划，影响新sigma计划的后段。
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- Comfy dtype: SIGMA_SCHEDULE
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- Python dtype: SigmaSchedule
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- idx_split_percent
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- 初始sigma计划拆分的百分比，决定两个计划之间的过渡点。
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- Comfy dtype: FLOAT
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- Python dtype: float
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## Output types
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- sigma_schedule
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- Comfy dtype: SIGMA_SCHEDULE
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- 结果sigma计划，是根据指定的拆分百分比修改的起始和结束输入计划的混合体。
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- Python dtype: SigmaSchedule
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## Usage tips
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- Infra type: CPU
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- Common nodes: unknown
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## Source code
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```python
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class SplitAndCombineSigmaScheduleNode:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"schedule_Start": ("SIGMA_SCHEDULE",),
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"schedule_End": ("SIGMA_SCHEDULE",),
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"idx_split_percent": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.001})
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}
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}
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RETURN_TYPES = ("SIGMA_SCHEDULE",)
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CATEGORY = "Animate Diff 🎭🅐🅓/sample settings/sigma schedule"
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FUNCTION = "get_sigma_schedule"
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def get_sigma_schedule(self, schedule_Start: SigmaSchedule, schedule_End: SigmaSchedule, idx_split_percent: float):
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validate_sigma_schedule_compatibility(schedule_Start, schedule_End)
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# first, calculate index to act as split; get diff from 1.0 since sigmas are flipped at this stage
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idx = int((1.0-idx_split_percent) * schedule_Start.total_sigmas())
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new_sigmas = torch.cat([schedule_End.model_sampling.sigmas[:idx], schedule_Start.model_sampling.sigmas[idx:]], dim=0)
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new_schedule = schedule_Start.clone()
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new_schedule.model_sampling.set_sigmas(new_sigmas)
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return (new_schedule,) |