e8065b7e890390dbd9398507d909aa2e955fd9f6,onmt/encoders/ggnn_encoder.py,GGNNEncoder,forward,#GGNNEncoder#Any#Any#,154

Before Change

                elif token == self.DELIMITER:
                    flags += 1
                    flags_done = True
                    assert flags <= nodes
                elif not flags_done:
                    // The total number of integers in the vocab should allow
                    // for all features and edges to be defined.
                    if token == self.COMMA:

After Change

        token_onehot = torch.from_numpy(token_onehot).float().to(src.device)
        if self.src_ggnn_size > 0:
            token_embed = self.embed(token_onehot)
            prop_state = torch.cat((token_embed, torch.zeros(
                (batch_size, nodes, self.state_dim - self.src_word_vec_size)
                 ).float().to(src.device)), 2)
        else:
            prop_state = token_onehot
        edges = torch.from_numpy(edges).float().to(src.device)

Instances