code: def replace_torchsde_browinan():
      import torchsde._brownian.brownian_interval
  
      def torchsde_randn(size, dtype, device, seed):
          return devices.randn_local(seed, size).to(
              device=device, dtype=dtype
          )
  
      torchsde._brownian.brownian_interval._randn = torchsde_randn
  
imports: import inspect
  from collections import namedtuple
  import numpy
  import torch
  from PIL import Image
  from modules import devices, images, sd_vae_approx, sd_samplers, sd_vae_taesd, shared, sd_models
  from modules.shared import opts, state
  import k_diffusion.sampling
label_desc: Use image node_id 10 for calling a global function with example usage: replace_torchsde_browinan() and returns: devices