code: def seeded_randn(shape, seed):
      randn = np.random.RandomState(seed).randn(*shape)
      randn = torch.from_numpy(randn).to(
          device="cuda", dtype=torch.float32
      )
      return randn
  
file_path: generative-models/scripts/demo/turbo.py
imports: from streamlit_helpers import *
  from st_keyup import st_keyup
  from sgm.modules.diffusionmodules.sampling import EulerAncestralSampler
label_desc: Use image node_id 1 for calling a global function with example usage: seeded_randn(shape, seed) and returns: randn