code: def _setup(device, levy_area_approximation, shape):
      t0, t1 = torch.tensor([0.0, 1.0], device=device)
      ta = torch.rand([], device=device)
      tb = torch.rand([], device=device)
      ta, tb = min(ta, tb), max(ta, tb)
      bm = torchsde.BrownianInterval(
          t0=t0,
          t1=t1,
          size=shape,
          device=device,
          levy_area_approximation=levy_area_approximation,
      )
      return ta, tb, bm
  
file_path: torchsde/tests/test_brownian_interval.py
imports: import sys
  import math
  import numpy.random
  import torch
  from scipy.stats import kstest
  import pytest
  import torchsde
label_desc: Use image node_id 2 for calling a global function with example usage: _setup(device, levy_area_approximation, shape) and returns: ta,  tb,  bm