class_docstr: An abstract base class for implementing explainer algorithms.
docstr: Checks if the explainer supports the user-defined settings provided
  in :obj:`self.explainer_config`, :obj:`self.model_config`.
docstr_tok: ["Checks","if","the","explainer","supports","the","user-defined","settings","provided","in",":","obj",":","`","self.explainer_config","`",",",":","obj",":","`","self.model_config","`","."]
code: def supports(self) -> bool:
      r"""Checks if the explainer supports the user-defined settings provided
      in :obj:`self.explainer_config`, :obj:`self.model_config`.
      """
      pass
  
imports: from abc import abstractmethod
  from typing import Dict, Optional, Tuple, Union
  import torch
  import torch.nn.functional
  from torch import Tensor
  from torch_geometric.explain import Explanation, HeteroExplanation
  from torch_geometric.explain.config import ExplainerConfig, ModelConfig, ModelReturnType
  from torch_geometric.nn import MessagePassing
  from torch_geometric.typing import EdgeType, NodeType
  from torch_geometric.utils import k_hop_subgraph
label_desc: Use image node_id 2 for calling the ExplainerAlgorithm obj's underlying member method code with example usage: obj.supports() without return types