0b6031eafd5d4312166bba0f3874f4198e95623a,examples/text-pair/glove_mwe_multipool_siamese.py,,main,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,96

Before Change

                                 "+": add}):
        mwe_encode = ExtractWindow(nW=1) >> BN(Maxout(width, drop_factor=0.0, pieces=pieces))

        sent2vec = ( // List[spacy.token.Doc]{B}
            flatten_add_lengths  // : (ids{T}, lengths{B})
            >> with_getitem(0,
                //(StaticVectors("en", width)
                HashEmbed(width, 3000)
                //+ HashEmbed(width, 3000))
                //>> Residual(mwe_encode ** 2)
                ) // : word_ids{T}
            >> Pooling(mean_pool, max_pool)
            //>> Residual(BN(Maxout(width*2, pieces=pieces), nO=width*2)**2)
            >> Maxout(width*2, pieces=pieces, drop_factor=0.0)
            >> logistic
        )
        model = Siamese(sent2vec, CauchySimilarity(width*2))

    print("Read and parse data: %s" % dataset)
    if dataset == "quora":

After Change

            >> LN(Maxout(width, drop_factor=0.0, pieces=pieces))
        )

        sent2vec = (
            flatten_add_lengths
            >> with_getitem(0,
                (HashEmbed(width, 3000) | StaticVectors("en", width))
                >> LN(Maxout(width, width*2))
                >> Residual(mwe_encode) ** depth
            ) // : word_ids{T}
            >> Pooling(mean_pool, max_pool)
            >> Residual(LN(Maxout(width*2, pieces=pieces), nO=width*2)) **2
            >> logistic
        )
        model = Siamese(sent2vec, CauchySimilarity(width*2))

    print("Read and parse data: %s" % dataset)
    if dataset == "quora":

Instances