def testIter(self):
"""Tests overloading operator ``__iter__``."""
weights = {'a': Weight(0.2), 'b': Weight(0.4), 'c': Weight(3.2)}
meta_weight = MetaWeight(weights)
self.assertSetEqual(set(iter(meta_weight)), set(iter(weights)))
for key, value in meta_weight.iteritems():
self.assertEqual(value, weights[key])
def testLen(self):
"""Tests overloading operator ``__len__``."""
self.assertEqual(
len(MetaWeight({
'a': Weight(0.5),
'b': Weight(0.23)
})), 2)
def RedefineClassifierIfLargeRegressionRange(self, analysis):
"""Disable features for revisions in regression range > 100 commits.
For crash with big regression range, it's easy to get false positives if we
enable TouchCrashedComponentFeature and TouchCrashedDirectoryFeature,
Because it has a big chance to hit these features and cause false positives.
So we should disable these 2 features.
"""
if (analysis.commit_count_in_regression_range <
_BIG_REGRESSION_RANGE_COMMITS_THRESHOLD):
return
get_repository = self._predator.changelist_classifier._get_repository
meta_weight = MetaWeight({
'TouchCrashedFileMeta':
MetaWeight({
'MinDistance': Weight(1.),
'TopFrameIndex': Weight(1.),
'TouchCrashedFile': Weight(1.),
}),
})
meta_feature = WrapperMetaFeature([
TouchCrashedFileMetaFeature([
MinDistanceFeature(get_repository),
TopFrameIndexFeature(),
TouchCrashedFileFeature()
])
])
self._predator.changelist_classifier = ChangelistClassifier(
get_repository, meta_feature, meta_weight)
def setUp(self):
"""Set up some basic parts of our loglinear model.
These parts describe a silly model for detecting whether an integer
in [0..9] is the number 7. So ``X`` is the set of integers [0..9],
and ``Y`` is the set of ``bool`` values. The independent variable
is boolean-valued because we only have two categories: "yes, x ==
7" and "no, x != 7". This doesn't take advantage of the fact that
loglinear models can categorize larger sets of labels, but it's good
enough for testing purposes.
In addition to specifying ``X`` and ``Y``, we also specify a set of
features and choose some random weights for them.
"""
super(LinearTestCase, self).setUp()
self._meta_feature = WrapperMetaFeature([Feature0(),
Feature1(),
Feature2(),
WrapperMetaFeature([Feature3(),
Feature4()])])
self._meta_weight = MetaWeight(
{
'Feature0': Weight(random.random()),
'Feature1': Weight(random.random()),
'Feature2': Weight(random.random()),
'WrapperFeature': MetaWeight(
{
'Feature3': Weight(random.random()),
'Feature4': Weight(random.random())
})
})
self._X = range(10)
self._Y = lambda _x: [False, True]
def __init__(self, get_repository, config):
"""Set the paramaters of the model - i.e. the weights and features.
For some explanation of why the paramaters were set this way see these docs:
https://docs.google.com/a/google.com/document/d/1TdDEDlUJX81-5yvB9IfdJFq5-kJBb_DwAgDH9cGfNao/edit?usp=sharing
https://docs.google.com/a/google.com/document/d/1FHaghBX_FANjtiUP7D1pihZGxzEYdXA3Y7t0rSA4bWU/edit?usp=sharing
As well as the following CLs:
https://chromium-review.googlesource.com/c/599071
https://chromium-review.googlesource.com/c/585784
"""
super(PredatorForUMASamplingProfiler,
self).__init__(get_repository, config)
meta_weight = MetaWeight({
'TouchCrashedFileMeta':
MetaWeight({
'MinDistance': Weight(2.),
'TopFrameIndex': Weight(0.),
'TouchCrashedFile': Weight(1.),
})
})
min_distance_feature = MinDistanceFeature(get_repository)
top_frame_index_feature = TopFrameIndexFeature()
touch_crashed_file_feature = TouchCrashedFileFeature()
meta_feature = WrapperMetaFeature([
TouchCrashedFileMetaFeature([
min_distance_feature, top_frame_index_feature,
touch_crashed_file_feature
],
include_renamed_paths=True)
])
self._predator = Predator(
ChangelistClassifier(get_repository, meta_feature, meta_weight),
self._component_classifier, self._project_classifier)
def testEqual(self):
"""Tests ``__eq__`` and ``__ne__``."""
self.assertTrue(
MetaWeight({'f1': Weight(0.008)}) == MetaWeight(
{'f1': Weight(0.008)}))
self.assertFalse(
MetaWeight({'f1': MetaWeight({'f2': Weight(0.008)})}) ==
MetaWeight({'f1': MetaWeight({'f2': Weight(0.1)})}))
self.assertFalse(MetaWeight({'f1': Weight(0.008)}) == MetaWeight({}))
def testMultiply(self):
"""Tests overloading operators ``__mul__`` and ``__rmul__``"""
self.assertEqual(
MetaWeight({
'f1': Weight(0.8),
'f2': Weight(0.4)
}) * MetaFeatureValue('f', {
'f1': 2.,
'f2': 1.
}), 2.)
self.assertEqual(
MetaFeatureValue('f', {
'f1': 0.8,
'f2': 0.4
}) * MetaWeight({
'f1': Weight(2.),
'f2': Weight(1.)
}), 2.)
self.assertEqual(
MetaWeight({
'f1': Weight(0.8),
'f3': Weight(0.0)
}) * MetaFeatureValue('f', {
'f1': Weight(2.),
'f2': Weight(9),
'f3': Weight(10)
}), 1.6)
def testFilterReasonWithWeight(self):
meta_weight = MetaWeight({
'f1': Weight(2.),
'f2': Weight(0.),
'f3': Weight(1.)
})
reason = MetaDict({'f1': ['reason1', 'reason3'], 'f2': ['reason2']})
model = UnnormalizedLogLinearModel(None, meta_weight)
self.assertListEqual(model.FilterReasonWithWeight(reason),
['reason1', 'reason3'])
def testquadrance(self):
"""Tests ``quadrance`` property."""
self.assertEqual(
MetaWeight({
'a': Weight(0.3),
'b': Weight(0.2)
}).quadrance, 0.13)
self.assertEqual(
MetaWeight({
'a': Weight(0.3),
'b': Weight(-0.3)
}).quadrance, 0.18)
def testIsZero(self):
"""Tests ``IsZero`` method."""
self.assertTrue(
MetaWeight({
'f1': Weight(0.008),
'f2': Weight(0.00004)
}).IsZero(0.01))
self.assertFalse(
MetaWeight({
'f1': Weight(0.08),
'f2': Weight(0.00004)
}).IsZero(0.001))
def testl1(self):
"""Tests ``l1`` property."""
self.assertEqual(
MetaWeight({
'a': Weight(0.3),
'b': Weight(0.2)
}).l1, 0.5)
self.assertEqual(
MetaWeight({
'a': Weight(0.3),
'b': Weight(-0.3)
}).l1, 0.6)
def testDropZeroWeights(self):
meta_weight = MetaWeight({
'f1':
Weight(0.02),
'f2':
MetaWeight({
'f3': Weight(0.00001),
'f4': Weight(0.0000003)
})
})
meta_weight.DropZeroWeights(epsilon=0.0001)
expected_meta_weight = MetaWeight({'f1': Weight(0.02)})
self.assertTrue(meta_weight == expected_meta_weight)
def setUp(self):
super(ChangelistClassifierTest, self).setUp()
meta_weight = MetaWeight({
'TouchCrashedFileMeta':
MetaWeight({
'MinDistance': Weight(1.),
'TopFrameIndex': Weight(1.),
'TouchCrashedFile': Weight(1.),
})
})
get_repository = GitilesRepository.Factory(self.GetMockHttpClient())
meta_feature = WrapperMetaFeature(
[TouchCrashedFileMetaFeature(get_repository)])
self.changelist_classifier = ChangelistClassifier(
get_repository, meta_feature, meta_weight)
def __init__(self, get_repository, config):
super(FinditForClusterfuzz, self).__init__(get_repository, config)
meta_weight = MetaWeight({
'TouchCrashedFileMeta':
MetaWeight({
'MinDistance': Weight(1.),
'TopFrameIndex': Weight(1.),
'TouchCrashedFile': Weight(1.),
}),
'TouchCrashedDirectory':
Weight(1.),
'TouchCrashedComponent':
Weight(1.)
})
meta_feature = WrapperMetaFeature([
TouchCrashedFileMetaFeature(get_repository),
TouchCrashedDirectoryFeature(),
TouchCrashedComponentFeature(self._component_classifier)
])
self._predator = Predator(
ChangelistClassifier(get_repository, meta_feature, meta_weight),
self._component_classifier, self._project_classifier)
def testl0(self):
"""Tests ``l0`` property."""
self.assertEqual(
MetaWeight({
'a': Weight(0.2),
'b': Weight(0.),
'd': Weight(0.),
'e': Weight(2.)
}).l0, 2)
self.assertEqual(MetaWeight({'a': Weight(0.), 'b': Weight(0.)}).l0, 0)
def __init__(self, get_repository, config):
super(PredatorForClusterfuzz, self).__init__(get_repository, config)
meta_weight = MetaWeight({
'TouchCrashedFileMeta':
MetaWeight({
'MinDistance': Weight(2.),
'TopFrameIndex': Weight(1.),
'TouchCrashedFile': Weight(1.),
}),
'TouchCrashedDirectory':
Weight(1.),
'TouchCrashedComponent':
Weight(1.),
'NumberOfTouchedFiles':
Weight(0.5),
})
min_distance_feature = MinDistanceFeature(get_repository)
top_frame_index_feature = TopFrameIndexFeature()
touch_crashed_file_feature = TouchCrashedFileFeature()
meta_feature = WrapperMetaFeature([
TouchCrashedFileMetaFeature([
min_distance_feature, top_frame_index_feature,
touch_crashed_file_feature
],
options=config.feature_options.get(
'TouchCrashedFileMetaFeature')),
TouchCrashedDirectoryFeature(
options=config.feature_options['TouchCrashedDirectory']),
TouchCrashedComponentFeature(
self._component_classifier,
options=config.feature_options['TouchCrashedComponent']),
NumberOfTouchedFilesFeature()
])
self._predator = Predator(
ChangelistClassifier(get_repository, meta_feature, meta_weight),
self._component_classifier, self._project_classifier)
def _MetaToNumPyArray(self, meta_weight):
"""Converts dict (mapping feature name to weight) to numpy array."""
return np.array(self._serializer.ToList(meta_weight,
default=Weight(0)))
def testquadrance(self):
"""Tests ``quadrance`` property."""
self.assertEqual(Weight(0.3).quadrance, 0.09)
self.assertEqual(Weight(-0.3).quadrance, 0.09)
def testl0(self):
"""Tests ``l0`` property."""
self.assertEqual(Weight(0.2).l0, 1)
self.assertEqual(Weight(0.).l0, 0)
def testLen(self):
"""Tests overloading operator ``__len__``."""
self.assertEqual(len(Weight(0.5)), 1)
def testIsZero(self):
"""Tests ``IsZero`` method."""
self.assertTrue(Weight(0.00001).IsZero(0.001))
self.assertFalse(Weight(0.00001).IsZero(0.000001))
def testMetaWeightSetter(self):
model = LogLinearModel(self._Y, self._meta_feature, self._meta_weight)
new_meta_weight = copy.deepcopy(self._meta_weight)
new_meta_weight['Feature0'] = Weight(2.1)
model.meta_weight = new_meta_weight
self.assertTrue(model.meta_weight == new_meta_weight)
def testMultiply(self):
"""Tests overloading operators ``__mul__`` and ``__rmul__``"""
self.assertEqual((Weight(0.8) * 2.0), 0.8 * 2.0)
self.assertEqual((2.0 * Weight(0.8)), 2.0 * 0.8)
def testl1(self):
"""Tests ``l1`` property."""
self.assertEqual(Weight(0.3).l1, 0.3)
self.assertEqual(Weight(-0.3).l1, 0.3)
def testEqual(self):
"""Tests ``__eq__`` and ``__ne__``."""
self.assertTrue(Weight(0.2) == Weight(0.2))
self.assertTrue(Weight(0.2) != Weight(0.3))
def testFloat(self):
"""Tests convert ``Weight`` to float."""
self.assertEqual(float(Weight(0.8)), 0.8)