test_training.py 文件源码

def test_trainable_argument():
    x = np.random.random((5, 3))
    y = np.random.random((5, 2))

    model = Sequential()
    model.add(Dense(2, input_dim=3, trainable=False))
    model.compile('rmsprop', 'mse')
    out = model.predict(x)
    model.train_on_batch(x, y)
    out_2 = model.predict(x)
    assert_allclose(out, out_2)

    # test with nesting
    input = Input(shape=(3,))
    output = model(input)
    model = Model(input, output)
    model.compile('rmsprop', 'mse')
    out = model.predict(x)
    model.train_on_batch(x, y)
    out_2 = model.predict(x)
    assert_allclose(out, out_2)