code: def testSliceNetImageToText(self):
      x = np.random.randint(256, size=(3, 5, 5, 3))
      y = np.random.randint(10, size=(3, 5, 1, 1))
      hparams = slicenet.slicenet_params1_tiny()
      hparams.add_hparam("data_dir", "")
      problem = registry.problem("image_ms_coco_characters")
      p_hparams = problem.get_hparams(hparams)
      hparams.problem_hparams = p_hparams
      with self.test_session() as session:
          features = {
              "inputs": tf.constant(x, dtype=tf.int32),
              "targets": tf.constant(y, dtype=tf.int32),
              "target_space_id": tf.constant(1, dtype=tf.int32),
          }
          model = slicenet.SliceNet(
              hparams, tf_estimator.ModeKeys.TRAIN, p_hparams
          )
          logits, _ = model(features)
          session.run(tf.global_variables_initializer())
          res = session.run(logits)
      self.assertEqual(res.shape, (3, 5, 1, 1, 258))
  
file_path: tensor2tensor/tensor2tensor/models/slicenet_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  from tensor2tensor.data_generators import cifar
  from tensor2tensor.data_generators import mscoco
  from tensor2tensor.layers import modalities
  from tensor2tensor.models import slicenet
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 2 for calling the SliceNetTest obj's underlying member method code with example usage: obj.testSliceNetImageToText() without return types