code: def __init__(
      self,
      data_list: Union[List[Data], List[Tuple]],
      graph: Data,
      adj: SparseTensor,
      return_edge_index_type: str,
      **kwargs,
  ):
      self.graph = graph
      self.adj = adj
      self.return_edge_index_type = return_edge_index_type
      if "collate_fn" in kwargs:
          del kwargs["collate_fn"]
      super().__init__(data_list, collate_fn=self.collate_fn, **kwargs)
  
imports: import logging
  import math
  from typing import Callable, Iterator, List, NamedTuple, Optional, Tuple, Union
  import numpy
  import scipy.sparse
  import torch
  from torch import Tensor
  from tqdm import tqdm
  from torch_geometric.data import Data
  from torch_geometric.typing import SparseTensor
  from torch_geometric.utils import get_ppr, is_undirected, subgraph
label_desc: Use image node_id 1 to create a new IBMBBaseLoader object from inherited base classes: torch.utils.data with example: obj = IBMBBaseLoader(data_list, graph, adj, return_edge_index_type)