Building a neural network in PyTorch is like assembling LEGO. In _init_ you declare the pieces (layers), and in forward you specify how the input tensor should flow through them to become a prediction. The main advantage of nn.Module is that it automatically tracks all parameters (weights) inside its layers.
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