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

Before Change

    // Set inputs back to the unexpanded inputs to not to confuse the Estimator
    features["source"] = inputs_old
    features["source_length"] = inputs_length_old

    // Return `top_beams` decoding
    // (also remove initial id from the beam search)

After Change

                              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

    if params.decode_normalize:
        scores, indices = tf.nn.top_k(normalized_scores, k=top_beams)
        // shape of ids: [batch, beam_size, max_length]

Instances