docstr: Tests if the explanation contains a linear model score.
docstr_tok: ["Tests","if","the","explanation","contains","a","linear","model","score","."]
code: def test_explain_returns_explanation_with_score(self):
      """Tests if the explanation contains a linear model score."""
  
      def _predict_fn(sentences):
          return np.random.uniform(0.0, 1.0, [len(list(sentences)), 2])
  
      explanation = lime.explain(
          "Test sentence",
          _predict_fn,
          class_to_explain=1,
          num_samples=5,
          return_score=True,
      )
      self.assertIsNotNone(explanation.score)
  
imports: import collections
  import functools
  from absl.testing import absltest
  from absl.testing import parameterized
  from lime import lime_text
  from lit_nlp.components.citrus import lime
  from lit_nlp.components.citrus import utils
  import numpy
  from scipy import special
  from scipy import stats
label_desc: Use image node_id 10 for calling the LimeTest obj's underlying member method code with example usage: obj.test_explain_returns_explanation_with_score() and returns: np