bi_lstm_cnn_crf.py 文件源码

def test():
    energies_var = T.tensor4('energies', dtype=theano.config.floatX)
    targets_var = T.imatrix('targets')
    masks_var = T.matrix('masks', dtype=theano.config.floatX)
    layer_input = lasagne.layers.InputLayer([2, 2, 3, 3], input_var=energies_var)
    out = lasagne.layers.get_output(layer_input)
    loss = crf_loss(out, targets_var, masks_var)
    prediction, acc = crf_accuracy(energies_var, targets_var)

    fn = theano.function([energies_var, targets_var, masks_var], [loss, prediction, acc])

    energies = np.array([[[[10, 15, 20], [5, 10, 15], [3, 2, 0]], [[5, 10, 1], [5, 10, 1], [5, 10, 1]]],
                         [[[5, 6, 7], [2, 3, 4], [2, 1, 0]], [[0, 0, 0], [0, 0, 0], [0, 0, 0]]]], dtype=np.float32)

    targets = np.array([[0, 1], [0, 2]], dtype=np.int32)

    masks = np.array([[1, 1], [1, 0]], dtype=np.float32)

    l, p, a = fn(energies, targets, masks)
    print l
    print p
    print a