code: def test_groupnorm_correctness_1d():
      np.random.seed(0x2020)
      model = tf.keras.models.Sequential()
      norm = GroupNormalization(input_shape=(10,), groups=2)
      model.add(norm)
      model.compile(loss="mse", optimizer="rmsprop")
  
      x = np.random.normal(loc=5.0, scale=10.0, size=(1000, 10))
      model.fit(x, x, epochs=5, verbose=0)
      out = model.predict(x)
      out -= norm.beta.numpy()
      out /= norm.gamma.numpy()
  
      np.testing.assert_allclose(out.mean(), 0.0, atol=1e-1)
      np.testing.assert_allclose(out.std(), 1.0, atol=1e-1)
  
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 17 for calling a global function with example usage: test_groupnorm_correctness_1d() without return types