code: def init_net_params(scale, layer_sizes, rs=npr.RandomState(0)):
      
      return [(scale * rs.randn(m, n),   # weight matrix
               scale * rs.randn(n))      # bias vector
              for m, n in zip(layer_sizes[:-1], layer_sizes[1:])]
docs: Build a (weights, biases) tuples for all layers.