feature_column_ops_test.py 文件源码

def testEmbeddingColumnWithMultipleInitializersFails(self):
    hashed_sparse = tf.contrib.layers.sparse_column_with_hash_bucket("wire", 10)
    wire_tensor = tf.SparseTensor(values=["omar", "stringer", "marlo"],
                                  indices=[[0, 0], [1, 0], [1, 1]],
                                  shape=[2, 2])
    features = {"wire": wire_tensor}
    embedded_sparse = tf.contrib.layers.embedding_column(
        hashed_sparse,
        10,
        initializer=tf.truncated_normal_initializer(mean=42,
                                                    stddev=1337))
    embedded_sparse_alternate = tf.contrib.layers.embedding_column(
        hashed_sparse,
        10,
        initializer=tf.truncated_normal_initializer(mean=1337,
                                                    stddev=42))

    # Makes sure that trying to use different initializers with the same
    # embedding column explicitly fails.
    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])