diff options
Diffstat (limited to 'tensorflow/contrib/layers/python/layers/feature_column_ops_test.py')
-rw-r--r-- | tensorflow/contrib/layers/python/layers/feature_column_ops_test.py | 36 |
1 files changed, 23 insertions, 13 deletions
diff --git a/tensorflow/contrib/layers/python/layers/feature_column_ops_test.py b/tensorflow/contrib/layers/python/layers/feature_column_ops_test.py index 1d0f45357e..33aa3c8b09 100644 --- a/tensorflow/contrib/layers/python/layers/feature_column_ops_test.py +++ b/tensorflow/contrib/layers/python/layers/feature_column_ops_test.py @@ -341,9 +341,12 @@ class InputLayerTest(tf.test.TestCase): # Makes sure that trying to use different initializers with the same # embedding column explicitly fails. - with self.assertRaises(ValueError): - tf.contrib.layers.input_from_feature_columns( - features, [embedded_sparse, embedded_sparse_alternate]) + with self.test_session(): + with self.assertRaisesRegexp( + ValueError, + "Duplicate feature column key found for column: wire_embedding"): + tf.contrib.layers.input_from_feature_columns( + features, [embedded_sparse, embedded_sparse_alternate]) def testSparseColumn(self): hashed_sparse = tf.contrib.layers.sparse_column_with_hash_bucket("wire", 10) @@ -351,9 +354,11 @@ class InputLayerTest(tf.test.TestCase): indices=[[0, 0], [1, 0], [1, 1]], shape=[2, 2]) features = {"wire": wire_tensor} - with self.assertRaises(ValueError): - tf.initialize_all_variables().run() - tf.contrib.layers.input_layer(features, [hashed_sparse]) + with self.test_session(): + with self.assertRaisesRegexp( + ValueError, "Error creating input layer for column: wire"): + tf.initialize_all_variables().run() + tf.contrib.layers.input_from_feature_columns(features, [hashed_sparse]) def testCrossedColumn(self): a = tf.contrib.layers.sparse_column_with_hash_bucket("aaa", @@ -366,9 +371,11 @@ class InputLayerTest(tf.test.TestCase): indices=[[0, 0], [1, 0], [1, 1]], shape=[2, 2]) features = {"aaa": wire_tensor, "bbb": wire_tensor} - with self.assertRaises(ValueError): - tf.initialize_all_variables().run() - tf.contrib.layers.input_layer(features, [crossed]) + with self.test_session(): + with self.assertRaisesRegexp( + ValueError, "Error creating input layer for column: aaa_X_bbb"): + tf.initialize_all_variables().run() + tf.contrib.layers.input_from_feature_columns(features, [crossed]) def testAllColumns(self): real_valued = tf.contrib.layers.real_valued_column("income", 3) @@ -477,10 +484,13 @@ class WeightedSumTest(tf.test.TestCase): shape=[2, 2]) features = {"wire": wire_tensor} embeded_sparse = tf.contrib.layers.embedding_column(hashed_sparse, 10) - with self.assertRaises(ValueError): - tf.initialize_all_variables().run() - tf.contrib.layers.weighted_sum_from_feature_columns(features, - [embeded_sparse]) + with self.test_session(): + with self.assertRaisesRegexp( + ValueError, "Error creating weighted sum for column: wire_embedding"): + tf.initialize_all_variables().run() + tf.contrib.layers.weighted_sum_from_feature_columns(features, + [embeded_sparse], + num_outputs=5) def testRealValuedColumnWithMultiDimensions(self): real_valued = tf.contrib.layers.real_valued_column("price", 2) |