feature_column_ops_test.py 文件源码

def testParseExample(self):
    bucket = tf.contrib.layers.bucketized_column(
        tf.contrib.layers.real_valued_column("price", dimension=3),
        boundaries=[0., 10., 100.])
    wire_cast = tf.contrib.layers.sparse_column_with_keys(
        "wire_cast", ["marlo", "omar", "stringer"])
    # buckets 2, 3, 0
    data = tf.train.Example(features=tf.train.Features(feature={
        "price": tf.train.Feature(float_list=tf.train.FloatList(value=[20., 110,
                                                                       -3])),
        "wire_cast": tf.train.Feature(bytes_list=tf.train.BytesList(value=[
            b"stringer", b"marlo"
        ])),
    }))
    output = tf.contrib.layers.parse_feature_columns_from_examples(
        serialized=[data.SerializeToString()],
        feature_columns=[bucket, wire_cast])
    self.assertIn(bucket, output)
    self.assertIn(wire_cast, output)
    with self.test_session():
      tf.initialize_all_tables().run()
      self.assertAllEqual(output[bucket].eval(), [[2, 3, 0]])
      self.assertAllEqual(output[wire_cast].indices.eval(), [[0, 0], [0, 1]])
      self.assertAllEqual(output[wire_cast].values.eval(), [2, 0])