[Predator] Making the Y sets conditional for loglinear models

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

 # Copyright 2016 The Chromium Authors. All rights reserved.
 # Use of this source code is governed by a BSD-style license that can be
 # found in the LICENSE file.
 
 import random
 import unittest
 
 from crash.loglinear.feature import FeatureValue
 from crash.loglinear.model import ToFeatureFunction
 
@@ skipping 25 matching lines @@
     def feature1(x):
       return lambda y: FeatureValue('feature1', y == ((x % 2) == 1), None, None)
 
     def feature2(x):
       return lambda y: FeatureValue('feature2', y == (x <= 7), None, None)
 
     self._feature_list = [feature0, feature1, feature2]
     self._feature_function = ToFeatureFunction(self._feature_list)
     self._qty_features = len(self._feature_list)
     self._X = range(10)
-    self._Y = [False, True]
+    self._Y = lambda _x: [False, True]
     self._weights = [random.random() for _ in xrange(self._qty_features)]