Optimize hyperparameters hidden_layer_size MLPClassifier with skopt

Question

How can I optimize the number of layers and hidden layer size in a neural network using MLPClassifier from sklearn and skopt?

Usually I'd specify my space something like:

Space([Integer(name = 'alpha_2', low = 1, high = 2),
       Real(10**-5, 10**0, "log-uniform", name='alpha_2')])

( let's say hyperparameters alpha_1 and alpha_2).

With the neural network implementation in sklearn I need to tune hidden_layer_sizes which is a tuple:

hidden_layer_sizes : tuple, length = n_layers - 2, default=(100,)
    The ith element represents the number of neurons in the ith
    hidden layer.

How can i represent this in Space?