This repository holds a graph explainability solution, which extends the work (GraphMask Explainer) to heterogeneous as well as homogeneous Graphs, making this functionality model-agnostic. Moreover, this implementation provides both node feature-level and edge-level attributes mask (explanation subgraph), which is a binary-valued vector. All 0 values of this mask vector represent those features (and edges) of the graph that do not affect their corresponding predictions, whereas features (and edges) associated with 1 values consider to be a lot effective in influencing their associated predictions outputted by the original Graph Neural Network (GNN) model.
PyTorch GeometricPyTorchnumpyscikit-learntqdm
This implementation of GraphMask Explainer demonstrates explainability examples for GCN, GAT, and RGCN layer-types on Node Classification (NC), Graph Classification (GC), and Link Prediction (LP) tasks.
| Layer Type | Task | Dataset |
|---|---|---|
| GCN | NC | Cora |
| GCN | GC | Enzymes |
| GAT | NC | Cora |
| GAT | GC | Enzymes |
| GAT | LP | Cora |
| RGCN | NC | AIFB |
| RGCN | GC | Enzymes |
- To see the model-agnostic explainability layer’s implementation, check
graphmask_explainer.py. - To train the GraphMask Explainer and generate explanations for any of the aforementioned tasks, run
graphmask_explainer_example.py. - All hyperparameters’ settings can be tweaked (based on requirements) by altering their corresponding values provided in both
graphmask_explainer.pyandgraphmask_explainer_example.pyfiles.
| NC Task Explanation Subgraph (AIFB Dataset) | GC Task Explanation Subgraph (Enzymes Dataset) |
|---|---|
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These figures show output subgraph in which all irrelevant edges (having 0 values in the binary-valued mask) have been colored grey, whereas all relevant edges (having 1 values in the generated binary-valued mask) have been illustrated in black color. Note that, for NC task, the output subgraph contains only those nodes that lie within the 3-hop neighborhood of the parent node with index 20 and have the same relation type as the parent node has, on the other hand, for GC task, the output subgraph demonstrates explanations of the graph with index 10 present in Enzymes dataset.