torch_geometric.explain.algorithm.AttentionExplainer

class AttentionExplainer(reduce: str = 'max')

Bases: ExplainerAlgorithm

一个解释器，使用基于注意力的GNN（例如， GATConv， GATv2Conv，或 TransformerConv）生成的注意力系数作为边的解释。 跨层和头的注意力分数将根据reduce参数进行聚合。

Parameters:

reduce (str, optional) – 用于减少跨层和跨头的注意力分数的方法。（默认值："max"）

forward(model: Module, x: Tensor, edge_index: Tensor, *, target: Tensor, index: Optional[Union[int, Tensor]] = None, **kwargs) → Explanation

计算解释。

Parameters:

• model (torch.nn.Module) – The model to explain.

• x (Union[torch.Tensor, Dict[NodeType, torch.Tensor]]) – The input node features of a homogeneous or heterogeneous graph.

• edge_index (Union[torch.Tensor, Dict[NodeType, torch.Tensor]]) – The input edge indices of a homogeneous or heterogeneous graph.

• target (torch.Tensor) – The target of the model.

• index (Union[int, Tensor], optional) – The index of the model output to explain. Can be a single index or a tensor of indices. (default: None)

• **kwargs (optional) – Additional keyword arguments passed to model.

Return type:

Explanation

supports() → bool

Checks if the explainer supports the user-defined settings provided in self.explainer_config, self.model_config.

Return type:

bool 翻译后的内容： bool 在这个例子中，`bool` 是一个Python函数名称，根据翻译规则1，不需要翻译。因此，翻译后的内容保持不变。