input: Write a function to create a 3-layer artificial neural network using Python and print the outcome. The function should take three numpy arrays as inputs: the input layer, hidden layer, and output layer. It should compute the output of the network and print the result.
  
  def create_nn(input_layer, hidden_layer, output_layer):
      hidden_layer_output = np.dot(input_layer, hidden_layer)
      output = np.dot(hidden_layer_output, output_layer)
      print(output)
  
  import numpy as np
  
  assert create_nn(np.array([2, 3]), np.array([[0.1, 0.4], [0.8, 0.6], [0.3, 0.9]]), np.array([0.3, 0.7])) == print(np.array([0.6099999999999999]))
  assert create_nn(np.array([1, 2]), np.array([[0.2, 0.5], [0.7, 0.3], [0.4, 0.8]]), np.array([0.4, 0.6])) == print(np.array([0.5999999999999999]))
  assert create_nn(np.array([4, 5]), np.array([[0.9, 0.1], [0.5, 0.2], [0.7, 0.3]]), np.array([0.5, 0.8])) == print(np.array([0.88]))
  assert create_nn(np.array([0, 0]), np.array([[0.1, 0.4], [0.8, 0.6], [0.3, 0.9]]), np.array([0.3, 0.7])) == print(np.array([0.0]))
  assert create_nn(np.array([3, 4]), np.array([[0.1, 0.4], [0.8, 0.6], [0.3, 0.9]]), np.array([0.3, 0.7])) == print(np.array([0.6399999999999999]))
output: def create_nn(input_layer, hidden_layer, output_layer):
      hidden_layer_output = np.dot(input_layer, hidden_layer)
      output = np.dot(hidden_layer_output, output_layer)
      print(output)