test_loss_masking.py 文件源码

def test_loss_masking(self):
        X = np.array(
            [[[1, 1], [2, 1], [3, 1], [5, 5]],
             [[1, 5], [5, 0], [0, 0], [0, 0]]], dtype=np.int32)
        model = Sequential()
        model.add(Masking(mask_value=0, input_shape=(None, 2)))
        model.add(TimeDistributedDense(1, init='one'))
        model.compile(loss='mse', optimizer='sgd')
        y = model.predict(X)
        loss = model.fit(X, 4*y, nb_epoch=1, batch_size=2, verbose=1).history['loss'][0]
        assert loss == 285.