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| # finished i-th walk from node so add it to the list of walks as a list | ||
| walks.append(walk) | ||
| if include_edges: | ||
| assert len(walk_edges) == len(walk) - 1 |
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| if generator.use_edge_features: | ||
| edge_feature_sizes = generator.graph.edge_feature_sizes() | ||
| # the generator validates there's only one edge type | ||
| assert len(edge_feature_sizes) == 1 |
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| ] | ||
| ) | ||
| # there's never an edge for the head node (i.e. first element), so don't include it | ||
| assert np.size(edge_features[0]) == 0 |
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| for layer_nodes in nodes_per_hop | ||
| ] | ||
| # there's never an edge for the head node (i.e. first element), so don't include it | ||
| assert np.size(edge_features[0]) == 0 |
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|
Code Climate has analyzed commit 3df8da4 and detected 10 issues on this pull request. Here's the issue category breakdown:
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Any updates if this is going to be merged? |
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This allows a GraphSAGE generator to optionally include the features of edges that were traversed, and thus the model to factor these features into its predictions.
See: #1328