chore: import upstream snapshot with attribution

docs/source/notebooks/sparse/gcn.nblink

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+{
+    "path": "../../../../notebooks/sparse/gcn.ipynb"
+}

docs/source/notebooks/sparse/graph_diffusion.nblink

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+{
+    "path": "../../../../notebooks/sparse/graph_diffusion.ipynb"
+}

docs/source/notebooks/sparse/graph_transformer.nblink

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+{
+    "path": "../../../../notebooks/sparse/graph_transformer.ipynb"
+}

docs/source/notebooks/sparse/hgnn.nblink

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+{
+    "path": "../../../../notebooks/sparse/hgnn.ipynb"
+}

docs/source/notebooks/sparse/index.rst

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+Tutorials: dgl.sparse
+=========================
+
+The tutorial set cover the basic usage of DGL's sparse matrix class and operators. You can begin with "Quickstart" and "Building a Graph Convolutional Network Using Sparse Matrices". The rest of the tutorials demonstrate the usage by end-to-end examples. All the tutorials are written in Jupyter Notebook and can be played on Google Colab.
+
+.. toctree::
+  :maxdepth: 3
+  :titlesonly:
+
+  quickstart.nblink
+  gcn.nblink
+  graph_diffusion.nblink
+  hgnn.nblink
+  graph_transformer.nblink

docs/source/notebooks/sparse/quickstart.nblink

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+{
+    "path": "../../../../notebooks/sparse/quickstart.ipynb"
+}