INNER CODE UNIT · Python

label_idx

IBM/transition-amr-parser · src/ibm_neural_aligner/main.py:500

            label_idx = len(node_ids) + label_idx
            src_idx = d_node_idx[src]
            tgt_idx = d_node_idx[tgt]

            edge_index.append([src_idx, label_idx])
            edge_index.append([label_idx, tgt_idx])

            edge_index.append([tgt_idx, label_idx])
            edge_index.append([label_idx, src_idx])

        node_labels = [amr.nodes[k] for k in node_ids]
        edge_labels = [label for src, label, tgt in amr.edges]
        tokens = torch.tensor([vocab[tok] for tok in node_labels + edge_labels], dtype=torch.long)
        edge_index = torch.tensor(edge_index, dtype=torch.long)
        data = Data(edge_index=edge_index.t().contiguous(), y=tokens, num_nodes=len(tokens))
        return data

    def get_geometric_data_standard(self, amr):

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