feature_column_ops_test.py 文件源码

def testSparseColumnWithKeysWithDenseInputTensor(self):
    keys_sparse = tf.contrib.layers.sparse_column_with_keys(
        "wire", ["marlo", "omar", "stringer", "rick"])
    wire_tensor = tf.constant([["omar", "stringer"], ["marlo", "rick"]])

    features = {"wire": wire_tensor}
    output = feature_column_ops._Transformer(features).transform(keys_sparse)

    with self.test_session():
      tf.initialize_all_tables().run()
      # While the input is a dense Tensor, the output should be a SparseTensor.
      self.assertIsInstance(output, tf.SparseTensor)
      self.assertEqual(output.dtype, tf.int64)
      self.assertAllEqual(output.values.eval(), [1, 2, 0, 3])
      self.assertAllEqual(output.indices.eval(),
                          [[0, 0], [0, 1], [1, 0], [1, 1]])
      self.assertAllEqual(output.shape.eval(), [2, 2])