70 lines
1.9 KiB
Markdown
70 lines
1.9 KiB
Markdown
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# Documentation
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- Class name: RandomGeneratorForList __Inspire
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- Category: InspirePack/Util
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- Output node: False
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RandomGeneratorForList节点旨在基于给定的种子和唯一标识符生成随机值序列。它确保每个序列对其标识符是唯一的，从而在不同的执行过程中实现可重现的随机性。
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# Input types
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## Required
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- signal
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- signal输入充当随机生成过程的触发器，确保节点的操作被启动。
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- Comfy dtype: *
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- Python dtype: utils.any_typ
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- seed
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- seed输入决定了随机数生成的起点，确保序列的可重现性。
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- Comfy dtype: INT
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- Python dtype: int
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# Output types
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- signal
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- signal输出保持不变地传递，作为节点操作中的连续性元素。
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- Comfy dtype: *
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- Python dtype: utils.any_typ
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- random_value
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- random_value输出是一个新生成的随机数，为进一步处理提供了一个独特的元素。
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- Comfy dtype: INT
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- Python dtype: int
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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 RandomGeneratorForList:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {
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"signal": (utils.any_typ,),
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"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
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},
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"hidden": {"unique_id": "UNIQUE_ID"},
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}
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RETURN_TYPES = (utils.any_typ, "INT",)
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RETURN_NAMES = ("signal", "random_value",)
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FUNCTION = "doit"
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CATEGORY = "InspirePack/Util"
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def doit(self, signal, seed, unique_id):
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if unique_id not in list_counter_map:
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count = 0
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else:
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count = list_counter_map[unique_id]
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list_counter_map[unique_id] = count + 1
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rn = random.Random()
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rn.seed(seed + count)
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new_seed = random.randint(0, 1125899906842624)
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return (signal, new_seed)
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```
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