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-Basic reference pytorch implementation of GraphSAGE.
-Forgive the messiness; it was coded in a rush.
+# Reference PyTorch GraphSAGE Implementation
+### Author: William L. Hamilton
+
+
+Basic reference PyTorch implementation of GraphSAGE.
+This reference implementation is not as fast as the TensorFlow version for large graphs, but the code is easier to read and it performs better on small-graph benchmarks.
+The code is also intended to be more extensible and easier to work with the the TensorFlow version.
+
+Currently, only supervised versions of GraphSAGE-mean and GraphSAGE-GCN are implemented. 
+
+#### Requirements
+
+pytorch >0.2 is required.
+
+#### Running examples
 
 Execute `python -m graphsage.model` to run the Cora example.
 It assumes that CUDA is not being used, but modifying the run functions in `model.py` in the obvious way can change this.