code: def test_initializer():
      # Check if the initializer for gamma and beta is working correctly
      layer = GroupNormalization(
          groups=32,
          beta_initializer="random_normal",
          beta_constraint="NonNeg",
          gamma_initializer="random_normal",
          gamma_constraint="NonNeg",
      )
  
      model = _create_and_fit_sequential_model(layer, (64,))
  
      weights = np.array(model.layers[0].get_weights())
      negativ = weights[weights < 0.0]
      assert len(negativ) == 0
  
imports: import pytest
  import numpy
  import tensorflow
  from tensorflow_addons.layers.normalizations import FilterResponseNormalization
  from tensorflow_addons.layers.normalizations import GroupNormalization
  from tensorflow_addons.layers.normalizations import InstanceNormalization
label_desc: Use image node_id 13 for calling a global function with example usage: test_initializer() without return types