code: def __init__(self, model: nn.Module, explain_graph: bool = False):
      super().__init__(model=model, explain_graph=explain_graph)
  
file_path: DIG/benchmarks/xgraph/RandomSelection.py
imports: import torch
  import torch.nn
  from torch_geometric.utils.loop import add_self_loops
  from dig.xgraph.models.utils import subgraph
  from dig.xgraph.method.base_explainer import ExplainerBase
label_desc: Use image node_id 1 to create a new RandomSelectorExplainer object from inherited base classes: ExplainerBase with example: obj = RandomSelectorExplainer(model, explain_graph)