code: def round_stoachastic(x):
      sign = torch.sign(x)
      absx = torch.abs(x)
      decimal = absx - torch.floor(absx)
      rdm = torch.rand_like(decimal)
      return sign * (torch.floor(absx) + (rdm < decimal).to(x.dtype))
  
imports: from itertools import product
  import pytest
  import torch
  from torch import nn
  import bitsandbytes
label_desc: Use image node_id 7 for calling the LinearFunction obj's underlying member method code with example usage: obj.round_stoachastic(x) and returns: unknown