class_docstr: Tests tabular hot-flips on classification tasks.
class_docstr_tok: ["Tests","tabular","hot-flips","on","classification","tasks","."]
docstr: Tests that the returned values are indeed counterfactuals.
code: def test_output_is_counterfactuals(self):
      """Tests that the returned values are indeed counterfactuals."""
  
      output = self._gen.generate(
          example=self._example,
          model=self._model,
          dataset=self._dataset,
          config=self._config,
      )
      self.assertGreaterEqual(len(output), 1)
      target_prediction = self._predict_and_return_argmax_label(
          self._example
      )
      for cf_example in output:
          cf_prediction = self._predict_and_return_argmax_label(
              cf_example
          )
          self.assertNotEqual(cf_prediction, target_prediction)
  
imports: from unittest import mock
  from absl.testing import absltest
  from lit_nlp.api import dataset
  from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.components import minimal_targeted_counterfactuals
  from lit_nlp.lib import caching
  import numpy
  import scipy.special
label_desc: Use image node_id 10 for calling the ClassificationTabularMtcTest obj's underlying member method code with example usage: obj.test_output_is_counterfactuals() without return types