Add READMEs to some examples

examples/contrib/README.md

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+# Examples for External Contributions
+
+This directory contains examples demonstrating functionality included in the `torch_geometric.contrib` package.
+The `contrib` package of PyG is a staging area for early-stage, experimental code.
+Modules included here might be moved to the main library in the future.
+
+| Example                                                                            | Description                                                                                 |
+| ---------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------- |
+| [`rbcd_attack.py`](./rbcd_attack.py)                                               | An example of the RBCD (Resource-based Critical Data) attack                                |
+| [`rbcd_attack_poisoning.py`](./rbcd_attack_poisoning.py)                           | An example of the RBCD (Resource-Based Critical Data) attack with data poisoning strategies |
+| [`pgm_explainer_node_classification.py`](./pgm_explainer_node_classification.py)   | An example of the PGM (Probabilistic Graphical Model) explainer for node classification     |
+| [`pgm_explainer_graph_classification.py`](./pgm_explainer_graph_classification.py) | An example of the PGM (Probabilistic Graphical Model) explainer for graph classification    |

examples/distributed/README.md

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+# Examples for Distributed Graph Learning
+
+This directory contains examples for distributed graph learning.
+The examples are organized into two subdirectories:
+
+1. `pyg`: Distributed training via PyG's own `torch_geometric.distributed` package.
+1. `graphlearn_for_pytorch`: Distributed training via the external GraphLearn-for-PyTorch (GLT) package.

examples/explain/README.md

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+# Examples for Generating Explanations of Graph Neural Networks
+
+This directory contains examples demonstrating the use of the `torch_geometric.explain` package.
+The `explain` package of PyG provides a set of tools to explain the predictions of a GNN model or to explain the underlying phenomenon of a dataset.
+
+| Example                                                                | Description                                             |
+| ---------------------------------------------------------------------- | ------------------------------------------------------- |
+| [`gnn_explainer.py`](./gnn_explainer.py)                               | `GNNExplainer` for node classification                  |
+| [`gnn_explainer_link_pred.py`](./gnn_explainer_link_pred.py)           | `GNNExplainer` for link prediction                      |
+| [`gnn_explainer_ba_shapes.py`](./gnn_explainer_ba_shapes.py)           | `GNNExplainer` applied on the `BAShapes` dataset        |
+| [`captum_explainer.py`](./captum_explainer.py)                         | Captum-based explainer for node classification          |
+| [`captum_explainer_hetero_link.py`](./captum_explainer_hetero_link.py) | Captum-based explainer for heterogenous link prediction |
+| [`graphmask_explainer.py`](./graphmask_explainer.py)                   | `GraphMaskExplainer` for node classification            |

examples/jit/README.md

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+# JIT Examples
+
+This directory contains examples demonstrating the use of Just-In-Time (JIT) compilation in different GNN models.
+
+| Example                | Description                                                       |
+| ---------------------- | ----------------------------------------------------------------- |
+| [`gcn.py`](./gcn.py)   | JIT compilation in `GCN`                                          |
+| [`gat.py`](./gat.py)   | JIT compilation in `GAT`                                          |
+| [`gin.py`](./gin.py)   | JIT compilation in `GIN`                                          |
+| [`film.py`](./film.py) | JIT compilation in [`GNN-FiLM`](https://arxiv.org/abs/1906.12192) |

examples/pytorch_ignite/README.md

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+# Examples for PyTorch Ignite
+
+This directory provides examples showcasing the integration of PyG with [PyTorch Ingite](https://pytorch.org/ignite/index.html).
+
+| Example              | Description                                                      |
+| -------------------- | ---------------------------------------------------------------- |
+| [`gin.py`](./gin.py) | Demonstrates how to implement the GIN model using PyTorch Ignite |

examples/pytorch_lightning/README.md

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+# Examples for PyTorch Lightning
+
+This directory provides examples showcasing the integration of PyG with [PyTorch Lightning](https://github.com/Lightning-AI/pytorch-lightning).
+
+| Example                                    | Description                                                                          |
+| ------------------------------------------ | ------------------------------------------------------------------------------------ |
+| [`graph_sage.py`](./graph_sage.py)         | Combines PyG and PyTorch Lightning for node classification via the `GraphSAGE` model |
+| [`gin.py`](./gin.py)                       | Combines PyG and PyTorch Lightning for graph classification via the `GIN` model      |
+| [`relational_gnn.py`](./relational_gnn.py) | Combines PyG and PyTorch Lightning for heterogeneous node classification             |