if (params.cond_graph == nullptr || params.body_graph == nullptr ||
      params.cond_graph->parent == nullptr ||
      params.cond_graph->parent != params.body_graph->parent ||
      params.cond_graph->parent_inputs != params.body_graph->parent_inputs ||
      params.ninputs <= 0 || params.cond_inputs == nullptr ||
      params.body_inputs == nullptr || params.body_outputs == nullptr) {
    s->status = InvalidArgument(

}

// Populates `body_nodes` with the nodes that will become function's body.
// Performs various checks.
Status ComputeBodyNodes(
    const TF_Graph* fn_body, const char* fn_name, int num_opers,
    const TF_Operation* const* opers,
    const std::unordered_map<const Node*, std::vector<int>>& input_nodes,
    std::vector<const Node*>* body_nodes)
    TF_EXCLUSIVE_LOCKS_REQUIRED(fn_body->mu) {
  if (num_opers == -1) {

    *   Set as much partial shape as we can infer statically within the gradient
        impl of the gather op.
    *   Gradient of `tf.while_loop` emits `StatelessWhile` op if `cond` and body
        functions are stateless. This allows multiple gradients while ops to run
        in parallel under distribution strategy.
    *   Speed up `GradientTape` in eager mode by auto-generating list of op