code: def test_random_normal(self):
      utils.set_random_seed(1337)
      shape = (25, 20)
      mean = 0.0
      stddev = 1.0
      seed = 1234
      initializer = initializers.RandomNormal(
          mean=mean, stddev=stddev, seed=seed
      )
      values = initializer(shape=shape)
      self.assertEqual(initializer.mean, mean)
      self.assertEqual(initializer.stddev, stddev)
      self.assertEqual(initializer.seed, seed)
      self.assertEqual(values.shape, shape)
      self.assertAllClose(
          np.std(backend.convert_to_numpy(values)), stddev, atol=1e-1
      )
  
      self.run_class_serialization_test(initializer)
  
      # Test that a fixed seed yields the same results each call.
      initializer = initializers.RandomNormal(
          mean=mean, stddev=stddev, seed=1337
      )
      values = initializer(shape=shape)
      next_values = initializer(shape=shape)
      self.assertAllClose(values, next_values)
  
      # Test that a SeedGenerator yields different results each call.
      initializer = initializers.RandomNormal(
          mean=mean,
          stddev=stddev,
          seed=backend.random.SeedGenerator(1337),
      )
      values = initializer(shape=shape)
      next_values = initializer(shape=shape)
      self.assertNotAllClose(values, next_values)
  
      # Test serialization with SeedGenerator
      initializer = initializers.RandomNormal(
          mean=mean,
          stddev=stddev,
          seed=backend.random.SeedGenerator(1337),
      )
      values = initializer(shape=shape)
  
      # Test that unseeded generator gets different results after cloning
      initializer = initializers.RandomNormal(
          mean=mean, stddev=stddev, seed=None
      )
      values = initializer(shape=shape)
      cloned_initializer = initializers.RandomNormal.from_config(
          initializer.get_config()
      )
      new_values = cloned_initializer(shape=shape)
      self.assertNotAllClose(values, new_values)
  
      # Test that seeded generator gets same results after cloning
      initializer = initializers.RandomNormal(
          mean=mean, stddev=stddev, seed=1337
      )
      values = initializer(shape=shape)
      cloned_initializer = initializers.RandomNormal.from_config(
          initializer.get_config()
      )
      new_values = cloned_initializer(shape=shape)
      self.assertAllClose(values, new_values)
  
file_path: keras/keras/initializers/random_initializers_test.py
imports: import numpy
  from keras import backend
  from keras import initializers
  from keras import testing
  from keras import utils
label_desc: Use image node_id 1 for calling the InitializersTest obj's underlying member method code with example usage: obj.test_random_normal() without return types