code: def test_apply_no_average_pooling(self):
      device, data_format = resnet50_test_util.device_and_data_format()
      model = resnet50.ResNet50(
          data_format, average_pooling=False, include_top=False
      )
      with tf.device(device):
          images, _ = resnet50_test_util.random_batch(2, data_format)
          output = model(images, training=False)
      output_shape = (
          (2, 2048, 7, 7)
          if data_format == "channels_first"
          else (2, 7, 7, 2048)
      )
      self.assertEqual(output_shape, output.shape)
  
imports: import gc
  import os
  import tempfile
  import time
  import tensorflow
  from tensorflow.python.client import device_lib
  from tensorflow.python.eager import context
  from tensorflow.python.eager import record
  from tensorflow.python.eager.benchmarks.resnet50 import resnet50
  from tensorflow.python.eager.benchmarks.resnet50 import resnet50_test_util
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 8 for calling the ResNet50Test obj's underlying member method code with example usage: obj.test_apply_no_average_pooling() without return types