code: def _mean(self, x0, t, y):
      theta = self.theta
      exp_interp = torch.exp(-theta * t)[:, None, None, None]
      return exp_interp * x0 + (1 - exp_interp) * y
  
imports: import abc
  import warnings
  import numpy
  import torch
label_desc: Use image node_id 5 for calling the OUVESDE obj's underlying member method code with example usage: obj._mean(x0, t, y) and returns: unknown