import torch

class RandomLatentImage:
    def __init__(self, device="cpu"):
        self.device = device

    @classmethod
    def INPUT_TYPES(s):
        return {"required": { "width": ("INT", {"default": 512, "min": 64, "max": 4096, "step": 64}),
                              "height": ("INT", {"default": 512, "min": 64, "max": 4096, "step": 64}),
                              "batch_size": ("INT", {"default": 1, "min": 1, "max": 64})}}
    RETURN_TYPES = ("LATENT",)
    FUNCTION = "generate"

    CATEGORY = "latent"

    def generate(self, width, height, batch_size=1):
        latent = torch.randn(batch_size, 4, height // 8, width // 8)
        return ({"samples":latent}, )