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MichSchli / RelationPrediction

Implementation of R-GCNs for Relational Link Prediction
MIT License
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Using training triplet index as edge ID? #9

Open treble-maker123 opened 5 years ago

treble-maker123 commented 5 years ago

In the train.py script, copied and pasted below, the first element of the tuple for the adj_list is the index of the train_triplets,

adj_list = [[] for _ in entities]
for i,triplet in enumerate(train_triplets):
    adj_list[triplet[0]].append([i, triplet[2]])
    adj_list[triplet[2]].append([i, triplet[0]])

Later on in the sample_edge_neighborhood method, you have the follow code to sample the edge,

chosen_vertex = np.random.choice(np.arange(degrees.shape[0]), p=probabilities)
chosen_adj_list = adj_list[chosen_vertex]
seen[chosen_vertex] = True

...

chosen_edge = np.random.choice(np.arange(chosen_adj_list.shape[0]))
chosen_edge = chosen_adj_list[chosen_edge]
edge_number = chosen_edge[0]

The chosen_adj_list is an array of shape num_neighbors x 2, the second dimension being the tuple you're appending in the previous code block. But here, chosen_edge[0] would give you the index of the training triplet, which is not in anyway related to the edge type of the triplet, right?