code: def __init__(self, cls, *args, **kwargs):
      super(TransformWrapper, self).__init__(
          data_t="tensor", *args, **kwargs
      )
      self._cls = cls
      self._func = None
      self._args = args
      self._kwargs = kwargs
  
imports: from operator import xor
  from .utils import data_is_tensor, data_tensor2np, data_np2tensor
  import numpy
  import copy
  from torch_geometric.utils.convert import to_networkx
  from torch.utils.data import Dataset
  import torch
  from ...utils import get_logger
label_desc: Use image node_id 1 to create a new TransformWrapper object from inherited base classes: BaseFeature with example: obj = TransformWrapper(cls)