[Bug fix] No backpropagation in sparse GAT #13
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Also, there are some possible performance improvement in the backward process, but I create pull request for fixing the incorrect part. |
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#8 isn't work correctly because copying tensor cannot backward propagation.
Therefore, I create a custom autograd function to manually calcuate the gradient and sent them.
You can get the overall graph using
visualize_graph.pyand the output for sparse version GAT isoutput/graph_visualize.pdfoutput.pdf