code: def unet_image(shape):
      rng = torch.Generator()
      rng.manual_seed(int(torch.prod(torch.tensor(shape))))
  
      image = torch.randn(size=shape, generator=rng)
  
      return image
  
imports: import pytest
  import torch
  import torch.nn
  from neuralcompression.models import ConditionalUnetDiscriminator, UnetDiscriminator
label_desc: Use image node_id 1 for calling a global function with example usage: unet_image(shape) and returns: image