I was studying the case of BNN in documentation (https://docs.pymc.io/notebooks/bayesian_neural_network_advi.html?highlight=tanh).

I am not sure if I missed something… input data is suggested to use *skl.scalar* for normalization, but before the data enter *act_1* , the values of *pm.math.dot(ann_input, weights_in_1)* are also possible outside the functional range of x. Is it not suggested to transform again before the data entering *tanh(x)* ?