code: def forward(self, x: Tensor, edge_index: Tensor, **kwargs):
      self.num_edges = edge_index.shape[1]
      self.num_nodes = x.shape[0]
      self.device = x.device
  
imports: from typing import List, Tuple, Dict
  from math import sqrt
  import torch
  from torch import Tensor
  import torch.nn
  import matplotlib.pyplot
  import networkx
  from torch_geometric.nn import MessagePassing
  from torch_geometric.utils.loop import add_self_loops, remove_self_loops
  from torch_geometric.data import Data, Batch
  from torch_geometric.utils import to_networkx
  from ..models.utils import subgraph
  from rdkit import Chem
  from matplotlib.axes import Axes
  import numpy
  from ..models import GNNPool
label_desc: Use image node_id 7 for calling the ExplainerBase obj's underlying member method code with example usage: obj.forward(x, edge_index) without return types