text: Title: [Roadmap] Heterogeneous Graphs Explainability Support
  Body: ### 🚀 The feature, motivation and pitch
  
  Explainability is a key feature of GNNs, which is already implemented in PyG. However, of all the features introduced, only a few have been adapted to heterogeneous graphs.
  
  **Algorithms**: Of all the algorithms implemented for explainability, only the Captum algorithm is compatible with heterogeneous graphs. It would be interesting to adapt other specific algorithms for graphs such as ``GNNExplainer`` or ``PGExplainer``, and other algorithms such as ``AttentionExplainer``.
  
  Moreover, the algorithms adapted by PyG could be extended with new algorithms that have been published over the years (for example, see this [survey](https://arxiv.org/abs/2306.01958)), but this isn't just for heterogeneous graphs. Maybe in the future, we could work on creating new algorithms simultaneously for heterogeneous graphs, without this gap.
  
  - [ ] Adaptation of ``GNNExplainer`` for heterogeneous graphs.
  - [ ] Adaptation of ``PGExplainer`` for heterogeneous graphs. 
  - [ ] Adaptation of ``AttentionExplainer`` for heterogeneous graphs. 
  - [ ] Implementation of new explainability algorithms. System to allow adaptation to heterogeneous graphs without additional work.
  
  **Features**: Some features available in the explanations of homogeneous GNNs are missing in heterogeneous GNNs. For example, the ``visualize_graph`` method of ``Explanation`` is not available for ``HeteroExplanation``. This right now can be done with the ``get_explanation_subgraph`` method, and generating the plot by hand with NetworkX, but it would be nice to implement it to do it automatically.
  
  - [ ] Implementation of missing features for HeteroExplanation, such as ``visualize_graph``.
  
  **Metrics**: Currently, the available metrics such as Fidelity or Faithfulness are only available for homogeneous graphs, but those metrics could be adapted for heterogeneous graphs. To continue the work of #5628, we could think implementing new metrics for all kind of graphs, such as sparsity or stability (e.g. see https://arxiv.org/pdf/2012.15445.pdf)
  
  
  - [ ] Adaptation of fidelity, faithfulness and characterization score for heterogeneous graphs.
  - [ ] Sparsity metric for all graphs.
  - [ ] Stability metric for all graphs.
  
  ### Alternatives
  
  _No response_
  
  ### Additional context
  
  _No response_