input: Write a function to create a 3-layer artificial neural network using Python and print the outcome of the network's computation. The function should accept the input layer, hidden layer, and output layer as arguments. If the layers are not provided, the function should use default values.
  
  
  def neural_network(input_layer=np.array([2, 3]), hidden_layer=np.array([[0.1, 0.4], [0.8, 0.6], [0.3, 0.9]]), output_layer=np.array([0.3, 0.7])):
      import numpy as np
      
      hidden_layer_output = np.dot(input_layer, hidden_layer)
      output = np.dot(hidden_layer_output, output_layer)
      
      print(output)
  
  assert neural_network() == None  # The function should print the output and return None
  assert neural_network(input_layer=np.array([1, 2]), hidden_layer=np.array([[0.2, 0.3], [0.7, 0.5], [0.4, 0.8]]), output_layer=np.array([0.4, 0.6])) == None  # The function should print the output and return None
  
output: 
  def neural_network(input_layer=np.array([2, 3]), hidden_layer=np.array([[0.1, 0.4], [0.8, 0.6], [0.3, 0.9]]), output_layer=np.array([0.3, 0.7])):
      import numpy as np
      
      hidden_layer_output = np.dot(input_layer, hidden_layer)
      output = np.dot(hidden_layer_output, output_layer)
      
      print(output)
  