implement
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import torch
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class RandomLatentImage:
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def __init__(self, device="cpu"):
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self.device = device
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "width": ("INT", {"default": 512, "min": 64, "max": 4096, "step": 64}),
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"height": ("INT", {"default": 512, "min": 64, "max": 4096, "step": 64}),
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"batch_size": ("INT", {"default": 1, "min": 1, "max": 64})}}
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RETURN_TYPES = ("LATENT",)
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FUNCTION = "generate"
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CATEGORY = "latent"
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def generate(self, width, height, batch_size=1):
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latent = torch.randn(batch_size, 4, height // 8, width // 8)
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return ({"samples":latent}, )
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