def test_parse_original_feature_from_example_binary(self):
example = tf.train.Example()
example.features.feature["img"].bytes_list.value.extend([b"\xef"])
original_feature = inference_utils.parse_original_feature_from_example(
example, "img")
self.assertEqual("img", original_feature.feature_name)
self.assertEqual([b"\xef"], original_feature.original_value)
def test_parse_original_feature_from_example_binary(self):
example = tf.train.Example()
example.features.feature['img'].bytes_list.value.extend([b'\xef'])
original_feature = inference_utils.parse_original_feature_from_example(
example, 'img')
self.assertEqual('img', original_feature.feature_name)
self.assertEqual([b'\xef'], original_feature.original_value)
def test_parse_original_feature_from_example(self):
example = test_utils.make_fake_example()
original_feature = inference_utils.parse_original_feature_from_example(
example, 'repeated_float')
self.assertEqual('repeated_float', original_feature.feature_name)
self.assertEqual([1.0, 2.0, 3.0, 4.0], original_feature.original_value)
self.assertEqual('float_list', original_feature.feature_type)
self.assertEqual(4, original_feature.length)
original_feature = inference_utils.parse_original_feature_from_example(
example, 'repeated_int')
self.assertEqual('repeated_int', original_feature.feature_name)
self.assertEqual([10, 20], original_feature.original_value)
self.assertEqual('int64_list', original_feature.feature_type)
self.assertEqual(2, original_feature.length)
original_feature = inference_utils.parse_original_feature_from_example(
example, 'single_int')
self.assertEqual('single_int', original_feature.feature_name)
self.assertEqual([0], original_feature.original_value)
self.assertEqual('int64_list', original_feature.feature_type)
self.assertEqual(1, original_feature.length)
def test_make_mutant_tuples_float_list(self):
example = self.make_and_write_fake_example()
index_to_mutate = 1
num_mutants = 10
viz_params = inference_utils.VizParams(
x_min=1,
x_max=10,
examples=[example],
num_mutants=num_mutants,
feature_index_pattern=None,
)
original_feature = inference_utils.parse_original_feature_from_example(
example, "repeated_float")
mutant_features, mutant_examples = inference_utils.make_mutant_tuples(
[example],
original_feature,
index_to_mutate=index_to_mutate,
viz_params=viz_params,
)
# Check that values in mutant_features and mutant_examples are as expected.
expected_values = np.linspace(1, 10, num_mutants)
np.testing.assert_almost_equal(
expected_values,
[
mutant_feature.mutant_value
for mutant_feature in mutant_features
],
)
np.testing.assert_almost_equal(
expected_values,
[
mutant_example.features.feature["repeated_float"].float_list.
value[index_to_mutate] for mutant_example in mutant_examples
],
)
# Check that the example (other than the mutant value) is the same.
for expected_value, mutant_example in zip(expected_values,
mutant_examples):
mutant_values = test_utils.value_from_example(
mutant_example, "repeated_float")
original_values = test_utils.value_from_example(
example, "repeated_float")
original_values[index_to_mutate] = expected_value
self.assertEqual(original_values, mutant_values)
