code: def _check_dimensions(self, partition):
      provider = cifar100.Provider(seed=4)
      input_fn = provider.get_input_fn(
          partition, tf.contrib.learn.ModeKeys.TRAIN, batch_size=3
      )
      data, labels = input_fn()
      self.assertIn(cifar100.FEATURES, data)
      features = data[cifar100.FEATURES]
      init = tf.group(
          tf.global_variables_initializer(),
          tf.local_variables_initializer(),
      )
      with self.test_session() as sess:
          sess.run(init)
          self.assertEqual((3, 32, 32, 3), sess.run(features).shape)
          self.assertEqual((3, 1), sess.run(labels).shape)
  
file_path: adanet/research/improve_nas/trainer/cifar100_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from adanet.research.improve_nas.trainer import cifar100
  import tensorflow.compat.v1
label_desc: Use image node_id 1 for calling the Cifar100Test obj's underlying member method code with example usage: obj._check_dimensions(partition) without return types