input: Write a python function to compute the output of a 3-layer neural network given the input layer, hidden layer, and output layer weights using NumPy. 
  ```python
  import numpy as np
  
  def compute_output(input_layer, hidden_layer, output_layer):
      hidden_layer_output = np.dot(input_layer, hidden_layer)
      output = np.dot(hidden_layer_output, output_layer)
      return output
  
  assert np.isclose(compute_output(np.array([2, 3]), np.array([[0.1, 0.4],
                                                              [0.8, 0.6],
                                                              [0.3, 0.9]]),
                                   np.array([0.3, 0.7])), 1.35)
  assert np.isclose(compute_output(np.array([1, 2]), np.array([[0.2, 0.5],
                                                              [0.4, 0.3],
                                                              [0.6, 0.8]]),
                                   np.array([0.5, 0.2])), 0.83)
  assert np.isclose(compute_output(np.array([3, 4]), np.array([[0.1, 0.2],
                                                              [0.3, 0.4],
                                                              [0.5, 0.6]]),
                                   np.array([0.4, 0.6])), 1.52)
output: import numpy as np
  
  def compute_output(input_layer, hidden_layer, output_layer):
      hidden_layer_output = np.dot(input_layer, hidden_layer)
      output = np.dot(hidden_layer_output, output_layer)
      return output
  
  assert np.isclose(compute_output(np.array([2, 3]), np.array([[0.1, 0.4],
                                                              [0.8, 0.6]]),
                                   np.array([0.3, 0.7])), 1.35)
  assert np.isclose(compute_output(np.array([1, 2]), np.array([[0.2, 0.5],
                                                              [0.4, 0.3]]),
                                   np.array([0.5, 0.2])), 0.83)
  assert np.isclose(compute_output(np.array([3, 4]), np.array([[0.1, 0.2],
                                                              [0.3, 0.4]]),
                                   np.array([0.4, 0.6])), 1.52)