0a80b9769115d291f15c244429793eda4cb8ecad,tests/test_layer_transformer.py,,test_conv_to_wider_layer,#,60

Before Change

    model2.compile(loss=categorical_crossentropy,
                   optimizer=Adadelta(),
                   metrics=["accuracy"])
    random_input = np.random.rand(1, 28, 28, 1)
    output1 = model.predict_on_batch(random_input)
    output2 = model2.predict_on_batch(random_input)
    assert np.sum(output1.flatten() - output2.flatten()) < 1e-4

After Change

def test_conv_to_wider_layer():
    model = get_conv_model()
    conv1 = model.layers[1]
    conv2 = model.layers[4]
    bn1 = model.layers[2]
    new_conv1, [new_conv2], [new_bn1] = conv_to_wider_layer(conv1, [conv2], [bn1], 3)

    new_input = Input(shape=get_int_tuple(model.inputs[0].shape[1:]))
    temp_tensor = new_conv1(new_input)
    temp_tensor = new_bn1(temp_tensor)
    temp_tensor = Activation("relu")(temp_tensor)
    temp_tensor = new_conv2(temp_tensor)

Instances