be59363ec171475fe839cd8d903b9eb8d92856ae,thumt/models/seq2seq.py,,model_graph,#,15

Before Change

        logits = layers.nn.linear(outputs[:, -1, :], tgt_vocab_size, True,
                                  scope="softmax")

        return logits

    // Prediction
    logits = layers.nn.linear(outputs, tgt_vocab_size, True, scope="softmax")
    logits = tf.reshape(logits, [-1, tgt_vocab_size])

After Change

        logits = layers.nn.linear(outputs[:, -1, :], tgt_vocab_size, True,
                                  scope="softmax")

        return tf.nn.log_softmax(logits)

    // Prediction
    logits = layers.nn.linear(outputs, tgt_vocab_size, True, scope="softmax")
    logits = tf.reshape(logits, [-1, tgt_vocab_size])

Instances