test_temporal_data_tasks.py 文件源码

def test_temporal_regression():
    '''
    Predict float numbers (regression) based on sequences
    of float numbers of length 3 using a single layer of GRU units
    '''
    (X_train, y_train), (X_test, y_test) = get_test_data(nb_train=500,
                                                         nb_test=400,
                                                         input_shape=(3, 5),
                                                         output_shape=(2,),
                                                         classification=False)
    model = Sequential()
    model.add(GRU(y_train.shape[-1],
                  input_shape=(X_train.shape[1], X_train.shape[2])))
    model.compile(loss='hinge', optimizer='adam')
    history = model.fit(X_train, y_train, nb_epoch=5, batch_size=16,
                        validation_data=(X_test, y_test), verbose=0)
    assert(history.history['val_loss'][-1] < 1.)