feature_column_ops_test.py 文件源码

def testPredictionsWithMultivalentColumnButNoCross(self):
    language = tf.contrib.layers.sparse_column_with_keys(
        column_name="language",
        keys=["english", "turkish", "hindi"])
    with tf.Graph().as_default():
      features = {
          "language": tf.SparseTensor(values=["hindi", "english"],
                                      indices=[[0, 0], [0, 1]],
                                      shape=[1, 2])
      }
      output, column_to_variable, bias = (
          tf.contrib.layers.weighted_sum_from_feature_columns(features,
                                                              [language],
                                                              num_outputs=1))
      with self.test_session() as sess:
        tf.initialize_all_variables().run()
        tf.initialize_all_tables().run()

        # score: 0.1 + language_weight['hindi'] + language_weight['english']
        sess.run(bias.assign([0.1]))
        sess.run(column_to_variable[language][0].assign([[0.1], [0.3], [0.2]]))
        self.assertAllClose(output.eval(), [[0.4]])