736ba6c6873290fdae110395040f76ba7ab0ff19,tests/test_net_transformer.py,,test_net_transformer,#,3

Before Change

def test_net_transformer():
    model_a = Sequential()
    model_a.add(Conv2D(32, (3, 3), activation="relu", input_shape=(28, 28, 1)))
    model_a.add(Conv2D(32, (3, 3), activation="relu"))
    model_a.add(MaxPooling2D(pool_size=(2, 2)))
    model_a.add(Dropout(0.25))

After Change

    model.compile(loss=categorical_crossentropy,
                  optimizer=Adadelta(),
                  metrics=["accuracy"])
    random_input = np.random.rand(1,28,28,1)//one picture, 28,28, 1 chanel
    output1 = model.predict_on_batch(random_input)
    //print(model.summary())
    models = net_transfromer(model)

Instances