Evolving Neural Networks

In the __init__ function, we set up the network. The parameter dimensions is a list of layer dimensions, where the first is the width of the input, the last is the width of the output, and all others are hidden dimensions. The __init__ function iterates through these n dimensions to create n-1 weight matrices using Glorot Normal initialization, which are stored as layers. If bias is enabled, a non-zero bias vector is also stored for each layer. The model uses ReLU activation for all internal layers.