Why is the tensorflow maxout not calculating the gradient respectively where is the mistake?

Question

I am trying to use the tensorflow maxout implementation (https://www.tensorflow.org/addons/api_docs/python/tfa/layers/Maxout) but struggle with it;

I try to illustrate my problem: If I have the following

d=3


x_in=Input(shape=d)

x_out=Dense(d, activation='relu')(x_in)
model = Model(inputs=x_in, outputs=x_out)


model.compile(optimizer='adam', loss='MeanAbsoluteError')

X=tf.random.normal([200,3])
Y=tf.random.normal([200,3])

model.fit(X, Y, epochs=5, batch_size=32)

Then it is working normally, i.e. the loss is continuously getting smaller and I can get the estimated weights:

model.layers[1].get_weights()
Out[141]: 
[array([[-0.15133516, -0.14892222, -0.64674205],
        [ 0.34437487,  0.7822309 , -0.08931279],
        [-0.8330534 , -0.13827904, -0.23096593]], dtype=float32),
 array([-0.03069788, -0.03311999, -0.02603031], dtype=float32)]

However, when I want to use a maxout activation instead, things do not work out

d=3


x_in=Input(shape=d)

x_out = tfa.layers.Maxout(3)(x_in)
model = Model(inputs=x_in, outputs=x_out)


model.compile(optimizer='adam', loss='MeanAbsoluteError')

X=tf.random.normal([200,3])
Y=tf.random.normal([200,3])

model.fit(X, Y, epochs=5, batch_size=32)

The loss stays constant for all Epochs and

model.layers[1].get_weights()
Out[141]: []

Where is my mistake?