code: def expand(self, batch_shape, _instance=None):
      # Do basic validation. e.g. we should not "unexpand" distributions even if that is possible.
      new_shape, _, _ = self._broadcast_shape(
          self.batch_shape, batch_shape
      )
      # Record interstitial and expanded dims/sizes w.r.t. the base distribution
      (
          new_shape,
          expanded_sizes,
          interstitial_sizes,
      ) = self._broadcast_shape(self.base_dist.batch_shape, new_shape)
      self._batch_shape = new_shape
      self._expanded_sizes = expanded_sizes
      self._interstitial_sizes = interstitial_sizes
      return self
  
imports: import warnings
  from collections import OrderedDict
  from typing import Callable
  import torch
  from torch.distributions.kl import kl_divergence, register_kl
  import pyro.distributions.torch
  from .None import constraints
  from .distribution import Distribution
  from .score_parts import ScoreParts
  from .util import broadcast_shape, scale_and_mask
label_desc: Use image node_id 2 for calling the ExpandedDistribution obj's underlying member method code with example usage: obj.expand(batch_shape, _instance) and returns: self