code: def test_xavier_normal(self):
      n_inputs, n_outputs = 30, 30
  
      xavier_normal = init.XavierNormal()
      weight = self.eval(xavier_normal.sample((n_inputs, n_outputs)))
  
      self.assertNormalyDistributed(weight)
      self.assertAlmostEqual(weight.mean(), 0, places=1)
      self.assertAlmostEqual(
          weight.std(),
          math.sqrt(1.0 / (n_inputs + n_outputs)),
          places=2,
      )
  
imports: import math
  from scipy import stats
  import numpy
  from neupy import init
  from neupy.init import identify_fans
  from base import BaseTestCase
label_desc: Use image node_id 1 for calling the XavierInitializeTestCase obj's underlying member method code with example usage: obj.test_xavier_normal() without return types