code: def test_reshape():
      def run_reshape_test(axis, group, input_shape, expected_shape):
          group_layer = GroupNormalization(groups=group, axis=axis)
          group_layer._set_number_of_groups_for_instance_norm(
              input_shape
          )
  
          inputs = np.ones(input_shape)
          tensor_input_shape = tf.convert_to_tensor(input_shape)
          (
              reshaped_inputs,
              group_shape,
          ) = group_layer._reshape_into_groups(
              inputs, (10, 10, 10), tensor_input_shape
          )
          for i in range(len(expected_shape)):
              assert group_shape[i] == expected_shape[i]
  
      input_shape = (10, 10, 10)
      expected_shape = [10, 10, 5, 2]
      run_reshape_test(2, 5, input_shape, expected_shape)
  
      input_shape = (10, 10, 10)
      expected_shape = [10, 2, 5, 10]
      run_reshape_test(1, 2, input_shape, expected_shape)
  
      input_shape = (10, 10, 10)
      expected_shape = [10, 10, 10]
      run_reshape_test(1, -1, input_shape, expected_shape)
  
      input_shape = (10, 10, 10)
      expected_shape = [10, 1, 10, 10]
      run_reshape_test(1, 1, input_shape, expected_shape)
  
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 5 for calling a global function with example usage: test_reshape() without return types