[Predator] Move ``SingleFeatureScore`` to LLM.

appengine/findit/crash/loglinear/test/training_test.py

Index: appengine/findit/crash/loglinear/test/training_test.py
diff --git a/appengine/findit/crash/loglinear/test/training_test.py b/appengine/findit/crash/loglinear/test/training_test.py
index afb8ecc5fb9297b82312cfdd0de11673f749e68f..db4ad2ffe43c9fdc31f04b121775c514f795dfab 100644
--- a/appengine/findit/crash/loglinear/test/training_test.py
+++ b/appengine/findit/crash/loglinear/test/training_test.py
@@ -4,7 +4,6 @@
 
 import numpy as np
 
-from crash.loglinear.model import ToFeatureFunction
 from crash.loglinear.training import TrainableLogLinearModel
 from crash.loglinear.test.loglinear_testcase import LoglinearTestCase
 
@@ -35,14 +34,6 @@ class TrainableLogLinearModelTest(LoglinearTestCase):
 
     self.assertRaises(TypeError, _WeightSettingExpression)
 
-  def testWeightsSetterShapeMismatch(self):
-    def _WeightSettingExpression():
-      """Wrap the ``self._model.weights = stuff`` expression."""
-      # This np.ndarray has the wrong shape.
-      self._model.weights = np.array([[1,2], [3,4]])
-
-    self.assertRaises(TypeError, _WeightSettingExpression)
-
   def testTrainWeights(self):
     """Tests that ``TrainWeights`` actually improves the loglikelihood.