// `cond_output` and `body_outputs`.
//
// If `status` is OK, the caller must call either TF_FinishWhile or
// TF_AbortWhile on the returned TF_WhileParams. If `status` isn't OK, the
// returned TF_WhileParams is not valid, and the caller should not call
// TF_FinishWhile() or TF_AbortWhile().
//
// Missing functionality (TODO):
// - Gradients
// - Reference-type inputs

    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
    params->body_outputs[0] = {add2, 0};
    params->body_outputs[1] = params->body_inputs[1];

    // Finalize while loop
    TF_FinishWhile(params.get(), s_, &outputs[0]);
    EXPECT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  }

  // Define function, use it in graph, and run
  DefineT(-1, {}, {{feed1, 0}, {feed2, 0}}, {outputs[0]}, {});

    outputs[i] = {ToOperation(loop_outputs[i].node()), loop_outputs[i].index()};
  }
}

}  // namespace
#endif  // !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)

void TF_FinishWhile(const TF_WhileParams* params, TF_Status* status,
                    TF_Output* outputs) {
#if defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
  status->status = tensorflow::errors::Unimplemented(