code: def testDifferentSizedImages(self):
      # Due to global average pooling, different sized images should work fine
      # as long they are above some minimum size.
      convnet = cifar10_convnet.Cifar10ConvNet()
  
      small_image = tf.constant(
          np.random.randn(4, 32, 32, 3), dtype=tf.float32
      )
      small_output = convnet(small_image, is_training=True)
      self.assertEqual(small_output["logits"].shape, [4, 10])
  
      # Change height, width and batch size
      big_image = tf.constant(
          np.random.randn(12, 64, 64, 3), dtype=tf.float32
      )
      big_output = convnet(big_image, is_training=True)
      self.assertEqual(big_output["logits"].shape, [12, 10])
  
file_path: sonnet/sonnet/src/nets/cifar10_convnet_test.py
imports: from absl.testing import parameterized
  import numpy
  from sonnet.src import test_utils
  from sonnet.src.nets import cifar10_convnet
  import tensorflow
label_desc: Use image node_id 5 for calling the ModelTest obj's underlying member method code with example usage: obj.testDifferentSizedImages() without return types