text: import numpy as np
  
  
  def rand_initialization(l_in, l_out):
      # You need to return the following variable correctly
      epsilon_init = 0.12
      w = np.random.rand(l_in + 1, l_out) * 2 * epsilon_init - epsilon_init
  
      # ===================== Your Code Here =====================
      # Instructions : Initialize w randomly so that we break the symmetry while
      #                training the neural network
      #
      # Note : The first column of w corresponds to the parameters for the bias unit
      #
  
  
      # ===========================================================
  
      return w
  