62d2ea56ae4a090aa68baf133137982a836700bd,thumt/utils/search.py,,create_inference_graph,#Any#Any#Any#,430

Before Change

            return ids[:, :top_beams, 1:]
    else:
        if top_beams == 1:
            return ids[:, 0, 1:], scores[:, 0]
        else:
            return ids[:, :top_beams, 1:], scores[:, :top_beams]

After Change

                              eos_id=params.mapping["target"][params.eos],
                              lp_constant=params.decode_constant)

    mask = tf.not_equal(ids, 0)
    output_length = tf.reduce_sum(tf.to_float(mask), axis=-1)

    // shape: [batch, beam_size]
    normalized_scores = scores / output_length

Instances