// otherwise returns nullopt.
std::optional<absl::string_view> GetXlaClusterForNode(const Node& node);

// Removes `node_def` its XLA cluster (by clearing its _XlaCluster attribute).
void RemoveFromXlaCluster(NodeDef* node_def);

// Removes `node` its XLA cluster (by clearing its _XlaCluster attribute).
void RemoveFromXlaCluster(Node* node);

          }
        }
      }
    }
  }

  // Upgrade nodes in the GraphDef.
  for (auto& node_def : *gdef.mutable_node()) {
    const OpDef* op_def = nullptr;
    TF_RETURN_IF_ERROR(flib_def->LookUpOpDef(node_def.op(), &op_def));
    // TODO(b/197144710): improve the shared_name attr, each op may use the
    // shared_name differently.

  Status operator()(const std::vector<OutputTensor>&,
                    std::unique_ptr<Graph>* graph,
                    std::vector<int>* input_permutation,
                    std::vector<int>* output_permutation, NodeDef* node_def);

 private:
  string xla_cluster_attr_name_;
  string outside_compilation_attr_name_;
  string xla_cluster_name_;
  string new_function_name_;
};

// Belows are the attributes in TFE.
// TFE Arguments and Results (Got from "_Arg",
// "_Retval", .etc)
//  NodeDef.device <-> "tf.device"
//  NodeDef.attr <-> "tf."
//
// TFE general operations
//  NodeDef.device <-> "device"
//
// The following two functions are only used for mapping/excluding attributes
// which are inconsistent between TFG and TFE.
//

  }

  tf_core_op_expansion_node_counter->GetCell()->IncrementBy(1);

  LOG_FIRST_N(INFO, 1) << "Run Node Expansion Passes";

  // Get the FunctionDef and insert that into the context
  const NodeDef& ndef = orig_op->MutableAttrs()->BuildNodeDef();
  auto& ctx = orig_op->EagerContext();
  Fprint128 cache_key =
      orig_op->MutableAttrs()->CacheKey(orig_op->DeviceName());

    node_name = std::string(attr.getValue());
  }
  absl::StatusOr<std::unique_ptr<tensorflow::NodeDef>> node_def =
      tensorflow::ConvertTFDialectOpToNodeDef(
          inst, node_name.c_str(), /*ignore_unregistered_attrs=*/true);
  RETURN_FAILURE_IF_ERROR(node_def.status());

  const FallbackState& fallback_state = GetDefaultFallbackState();

    // returned by _Retval nodes.
    std::unique_ptr<Graph> graph_;

    // Which device are these nodes on? Used to assign a device to the call
    // node.
    string device_;

    // NodeDef for the function call node.
    NodeDef call_node_def_;

    // Name that is used for the call node. This may not be
    // call_node_def_.name() if the client supplies a rewrite lambda.
    string function_def_name_;

                       std::unique_ptr<Graph>* graph_ptr,
                       std::vector<int>* input_permutation,
                       std::vector<int>* output_permutation,
                       NodeDef* call_def) {
  Graph* graph = graph_ptr->get();
  const int num_args = input_permutation->size();
  const int num_retvals = output_permutation->size();

  std::vector<Node*> args;
  std::vector<Node*> retvals;

  EXPECT_TRUE(neg == neg2);
  NodeDef node_def2;
  ASSERT_TRUE(GetNodeDef(neg2, &node_def2));
  EXPECT_EQ(node_def.DebugString(), node_def2.DebugString());

  TF_Operation* feed2 = TF_GraphOperationByName(graph, "feed");
  EXPECT_TRUE(feed == feed2);
  ASSERT_TRUE(GetNodeDef(feed, &node_def));
  ASSERT_TRUE(GetNodeDef(feed2, &node_def2));
  EXPECT_EQ(node_def.DebugString(), node_def2.DebugString());

  node_def.set_name(op->Name());
  node_def.set_op(op->Name());
  for (int i = 0; i < num_inputs; ++i) {
    node_def.add_input("dummy_input");
  }
  OperationFromInterface(op)->Attrs().FillAttrValueMap(node_def.mutable_attr());

  const tensorflow::OpRegistrationData* op_reg_data;
  status->status =
      tensorflow::OpRegistry::Global()->LookUp(node_def.op(), &op_reg_data);