code: def init_nn_params(scale, layer_sizes, rs=npr.RandomState(0)):
      
      return [(rs.randn(insize, outsize) * scale,   # weight matrix
               rs.randn(outsize) * scale)           # bias vector
              for insize, outsize in zip(layer_sizes[:-1], layer_sizes[1:])]
docs: Build a list of (weights, biases) tuples, one for each layer.