experiments/STT-tensorflow
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Remove test to un-red nightly builds as suggested in b/151378056

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PiperOrigin-RevId: 301829065
Change-Id: I88a9d159faa9169de2854e69cc116af29943c74e
This commit is contained in:
Christian Sigg 2020-03-19 09:18:57 -07:00 committed by TensorFlower Gardener
parent 7b649ad65c
commit ce3925cf58
1 changed files with 0 additions and 25 deletions
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25
tensorflow/tools/compatibility/testdata/test_file_v1_12.py vendored
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@ -80,31 +80,6 @@ class TestUpgrade(test_util.TensorFlowTestCase):
logits=[0.1, 0.8], labels=[0, 1]) logits=[0.1, 0.8], labels=[0, 1])
self.assertAllClose(out, 0.40318608) self.assertAllClose(out, 0.40318608)
def testLinearClassifier(self):
if _TEST_VERSION == 2 and self._tf_api_version == 1:
# Skip if we converted this file to v2 but running with tf v1.
# In this case, conversion script adds reference to
# tf.keras.losses.Reduction which is not available in v1.
self.skipTest(
'After converting to 2.0, this test does not work with '
'TensorFlow 1.x.')
return
feature_column = tf.feature_column.numeric_column(
'feature', shape=(1,))
classifier = tf.estimator.LinearClassifier(
n_classes=2, feature_columns=[feature_column])
data = {'feature': [1, 20, 3]}
target = [0, 1, 0]
classifier.train(
input_fn=lambda: (data, target),
steps=100)
scores = classifier.evaluate(
input_fn=lambda: (data, target),
steps=100)
self.assertGreater(scores['accuracy'], 0.99)
def testUniformUnitScalingInitializer(self): def testUniformUnitScalingInitializer(self):
init = tf.initializers.uniform_unit_scaling(0.5, seed=1) init = tf.initializers.uniform_unit_scaling(0.5, seed=1)
self.assertArrayNear( self.assertArrayNear(