code: def test_predict_on_empty_data(self):
      test_set = TransformersDataset([], None)
  
      model_args = TransformerModelArguments(
          "sshleifer/tiny-distilroberta-base"
      )
      clf = TransformerBasedClassification(model_args, 2)
      # here would be a clf.fit call, which omit due to the runtime costs
  
      predictions = clf.predict(test_set)
      self.assertEqual(0, predictions.shape[0])
      self.assertTrue(np.issubdtype(predictions.dtype, np.integer))
  
imports: import unittest
  import pytest
  import numpy
  from unittest.mock import patch
  from small_text.base import LABEL_UNLABELED
  from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
  from small_text.training.early_stopping import EarlyStopping, EarlyStoppingOrCondition
  from small_text.training.metrics import Metric
  from small_text.utils.logging import VERBOSITY_MORE_VERBOSE
label_desc: Use image node_id 13 for calling the TestTransformerBasedClassification obj's underlying member method code with example usage: obj.test_predict_on_empty_data() without return types