a83fb851fa1829967304f18be76903b56a03bc89,examples/cnn_tagger.py,,main,#Any#Any#,24

Before Change

    with Model.define_operators({"**": clone, ">>": chain}):
        model = FeedForward((
            layerize(flatten_sequences),
            Embed(width, vector_length),
            (ExtractWindow(nW=1) >> ReLu(width)),
            (ExtractWindow(nW=2) >> ReLu(width)),

After Change

    train_data, check_data, nr_tag = ancora_pos_tags()

    with Model.define_operators({"**": clone, ">>": chain}):
        model = (
            layerize(flatten_sequences)
            >> layerize(get_positions)
            >> MaxoutWindowEncode(Embed(width, vector_length), 128,
                  pieces=2, window=2)
            >> ExtractWindow(nW=2)
            >> ReLu(128)
            >> Softmax(nr_tag))

    train_X, train_y = zip(*train_data)
    print("NR vector", max(max(seq) for seq in train_X))
    dev_X, dev_y = zip(*check_data)

Instances