feature_column_ops_test.py 文件源码

def testMulticlassWithSparseColumn(self):
    with tf.Graph().as_default():
      column = tf.contrib.layers.sparse_column_with_keys(
          column_name="language",
          keys=["english", "arabic", "hindi", "russian", "swahili"])
      features = {
          "language": tf.SparseTensor(
              values=["hindi", "english", "arabic", "russian"],
              indices=[[0, 0], [1, 0], [2, 0], [3, 0]],
              shape=[4, 1])
      }
      output, column_to_variable, _ = (
          tf.contrib.layers.weighted_sum_from_feature_columns(features,
                                                              [column],
                                                              num_outputs=3))
      with self.test_session() as sess:
        tf.initialize_all_variables().run()
        tf.initialize_all_tables().run()
        weights = column_to_variable[column][0]
        self.assertEqual(weights.get_shape(), (5, 3))
        sess.run(weights.assign([[0.1, 0.4, 0.7], [0.2, 0.5, 0.8],
                                 [0.3, 0.6, 0.9], [0.4, 0.7, 1.0], [0.5, 0.8,
                                                                    1.1]]))
        self.assertAllClose(output.eval(), [[0.3, 0.6, 0.9], [0.1, 0.4, 0.7],
                                            [0.2, 0.5, 0.8], [0.4, 0.7, 1.0]])