input: Write a function to create and print the outcome of a 3-layer artificial neural network using Python. The function should take the input layer, hidden layer, and output layer as parameters. If the input layer is empty, the function should print an error message stating "Input layer cannot be empty."
  assert compute_3_layer_ann(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 compute_3_layer_ann(np.array([]), np.array([[0.1, 0.4], [0.8, 0.6], [0.3, 0.9]]), np.array([0.3, 0.7]))=="Input layer cannot be empty."
  assert compute_3_layer_ann(np.array([2, 4]), np.array([[0.2, 0.5], [0.7, 0.5], [0.4, 0.8]]), np.array([0.2, 0.6]))==None
  assert compute_3_layer_ann(np.array([1, 2]), np.array([[0.3, 0.6], [0.9, 0.7], [0.2, 0.5]]), np.array([0.1, 0.8]))==None
  assert compute_3_layer_ann(np.array([1, 0]), np.array([[0.5, 0.2], [0.4, 0.8], [0.1, 0.3]]), np.array([0.7, 0.4]))==None
output: def compute_3_layer_ann(input_layer, hidden_layer, output_layer):
      if len(input_layer) == 0:
          return "Input layer cannot be empty."
      hidden_output = np.dot(hidden_layer, input_layer)
      final_output = np.dot(output_layer, hidden_output)
      return None