code: def test_global_pooling(self, use_cpu_only, backend, op, data_format):
      shape = None
      if op in {
          tf.keras.layers.GlobalAveragePooling1D,
          tf.keras.layers.GlobalMaxPool1D,
      }:
          shape = np.random.randint(low=2, high=4, size=3)
      elif op in {
          tf.keras.layers.GlobalAveragePooling2D,
          tf.keras.layers.GlobalMaxPool2D,
      }:
          shape = np.random.randint(low=2, high=4, size=4)
      elif op in {
          tf.keras.layers.GlobalAveragePooling3D,
          tf.keras.layers.GlobalMaxPool3D,
      }:
          shape = np.random.randint(low=2, high=4, size=5)
      model = tf.keras.Sequential(
          [op(batch_input_shape=shape, data_format=data_format)]
      )
      run_compare_tf_keras(
          model,
          [random_gen(shape, rand_min=-10, rand_max=10)],
          use_cpu_only=use_cpu_only,
          backend=backend,
      )
  
imports: import random
  from coremltools.converters.mil import testing_reqs
  from coremltools.converters.mil.frontend.tensorflow2.test.testing_utils import run_compare_tf_keras
  from coremltools.converters.mil.testing_reqs import *
label_desc: Use image node_id 1 for calling the TestPooling obj's underlying member method code with example usage: obj.test_global_pooling(use_cpu_only, backend, op, data_format) without return types