class_docstr: A wrapper around torchsde.BrownianTree that enables batches of entropy.
class_docstr_tok: ["A","wrapper","around","torchsde.BrownianTree","that","enables","batches","of","entropy","."]
code: def __call__(self, t0, t1):
      t0, t1, sign = self.sort(t0, t1)
      w = torch.stack([tree(t0, t1) for tree in self.trees]) * (
          self.sign * sign
      )
      return w if self.batched else w[0]
  
imports: import math
  from collections import defaultdict
  from typing import List, Optional, Tuple, Union
  import numpy
  import torch
  import torchsde
  from ..configuration_utils import ConfigMixin, register_to_config
  from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
label_desc: Use image node_id 3 for calling the BatchedBrownianTree obj's underlying member method code with example usage: obj.__call__(t0, t1) and returns: unknown