input: Write a python function to normalize a 2D numpy array by subtracting the mean of each row.
  assert np.allclose(normalize_array(np.array([[ 10, 11, 17, 16, 14],
                                               [ 2, 6, 3, 5, 0],
                                               [ 17, 20, 9, 18, 21]])), 
                     np.array([[ 3.4, 3.4, 9.8, 9.8, 7.8],
                               [-1.6, 0.4, -3.6, -2.6, -4.6],
                               [ 5.4, 8.4, -1.6, 6.4, 9.4]]))
  assert np.allclose(normalize_array(np.array([[ 1, 2, 3],
                                               [ 4, 5, 6],
                                               [ 7, 8, 9]])), 
                     np.array([[-1,  0,  1],
                               [-1,  0,  1],
                               [-1,  0,  1]]))
  assert np.allclose(normalize_array(np.array([[ 5, 10, 15],
                                               [20, 25, 30]])), 
                     np.array([[-5,  0,  5],
                               [-5,  0,  5]]))
output: import numpy as np
  
  def normalize_array(arr):
      row_means = np.mean(arr, axis=1, keepdims=True)
      normalized_arr = arr - row_means
      return normalized_arr