class_docstr: Tests tabular hot-flips on classification tasks.
class_docstr_tok: ["Tests","tabular","hot-flips","on","classification","tasks","."]
docstr: Tests the case when the passed model is not supported.
code: def test_unsupported_model(self):
      """Tests the case when the passed model is not supported."""
      mocked_model = mock.MagicMock()
      output_spec = {"preds": lit_types.ImageBytes}
      mocked_model.output_spec = mock.MagicMock(
          return_value=output_spec
      )
  
      with self.assertRaisesRegex(
          ValueError,
          "Only classification and regression models are supported",
      ):
          self._gen.generate(
              example=self._example,
              model=mocked_model,
              dataset=self._dataset,
              config=self._config,
          )
  
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 5 for calling the ClassificationTabularMtcTest obj's underlying member method code with example usage: obj.test_unsupported_model() without return types