input: Write a function to create a 3-layer artificial neural network using Python and print the outcome. The function should take the input vector, the weights of the hidden layer, and the weights of the output layer as parameters. 
  
  import numpy as np
  
  def neural_network(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)
  
  assert neural_network(np.array([2, 3]), np.array([[0.1, 0.4], [0.8, 0.6], [0.3, 0.9]]), np.array([0.3, 0.7]))==None
  assert neural_network(np.array([1, 4]), np.array([[0.2, 0.5], [0.7, 0.3], [0.4, 0.8]]), np.array([0.6, 0.2]))==None
  assert neural_network(np.array([0, 5]), np.array([[0.3, 0.6], [0.9, 0.1], [0.5, 0.7]]), np.array([0.4, 0.5]))==None
  assert neural_network(np.array([3, 2]), np.array([[0.4, 0.7], [0.6, 0.2], [0.8, 0.3]]), np.array([0.1, 0.8]))==None
  assert neural_network(np.array([5, 1]), np.array([[0.5, 0.8], [0.2, 0.1], [0.7, 0.4]]), np.array([0.2, 0.6]))==None
output: def neural_network(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)