EXPECT_EQ(string(""), string(TF_OperationDevice(add)));
  EXPECT_EQ(1, TF_OperationNumOutputs(add));
  EXPECT_EQ(TF_INT32, TF_OperationOutputType(TF_Output{add, 0}));
  EXPECT_EQ(1, TF_OperationOutputListLength(add, "sum", s));
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  EXPECT_EQ(2, TF_OperationNumInputs(add));
  EXPECT_EQ(2, TF_OperationInputListLength(add, "inputs", s));
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

        Keras training loops like `fit`/`evaluate`, the unreduced vector loss is
        passed to the optimizer but the reported loss will be a scalar value.
    *   `SUM`: Scalar sum of weighted losses. 4. `SUM_OVER_BATCH_SIZE`: Scalar
        `SUM` divided by number of elements in losses. This reduction type is
        not supported when used with `tf.distribute.Strategy` outside of