code: def WeightedClassSplitter(task=None, *args, **kwargs):
      return apply_wrapper(
          WeightedClassSplitter_(*args, **kwargs), task
      )
  
imports: import torch
  import numpy
  from collections import OrderedDict, defaultdict
  from torchmeta.utils.data.task import Task, ConcatTask, SubsetTask
  from torchmeta.transforms.utils import apply_wrapper
label_desc: Use image node_id 2 for calling a global function with example usage: WeightedClassSplitter(task) and returns: apply_wrapper