Node* read_1 = MakeRead(root, "R1");

  root.graph()->AddControlEdge(write_0, neutral_0);
  root.graph()->AddControlEdge(neutral_0, read_0);
  root.graph()->AddControlEdge(read_0, write_1);
  root.graph()->AddControlEdge(write_1, neutral_1);
  root.graph()->AddControlEdge(neutral_1, read_1);

  FixupSourceAndSinkEdges(root.graph());
  std::unique_ptr<Graph> graph(new Graph(OpRegistry::Global()));

  }
  func.return %graph#0, %graph#1, %graph#2, %graph#3 : !tf_res, !tf_res, tensor<f32>, tensor<f32>
}

// CHECK-LABEL: func @unconnected_while_cond
func.func @unconnected_while_cond(%arg0: !tf_res, %arg1: !tf_res, %arg2: tensor<f32>, %arg3: tensor<f32>) -> (tensor<i32>) {
  %graph = tf_executor.graph {
    %island, %ctrl = tf_executor.island {

  TF_Status* s = TF_NewStatus();
  TF_Graph* graph = TF_NewGraph();

  // Create a simple graph.
  Placeholder(graph, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  ASSERT_TRUE(TF_GraphOperationByName(graph, "feed") != nullptr);
  TF_Operation* oper = ScalarConst(3, graph, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  ASSERT_TRUE(TF_GraphOperationByName(graph, "scalar") != nullptr);
  Neg(oper, graph, s);

			return true
		}
	}
	return false
}

// Graph returns the graph of module requirements loaded from the current
// root modules (as reported by RootModules).
//
// Graph always makes a best effort to load the requirement graph despite any
// errors, and always returns a non-nil *ModuleGraph.
//
// If the requirements of any relevant module fail to load, Graph also
// returns a non-nil error of type *mvs.BuildListError.

#include "tensorflow/core/framework/node_def_util.h"
#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/graph/algorithm.h"
#include "tensorflow/core/graph/control_flow.h"
#include "tensorflow/core/graph/graph.h"
#include "tensorflow/core/graph/graph_def_builder.h"
#include "tensorflow/core/graph/tensor_id.h"
#include "tensorflow/core/lib/gtl/map_util.h"
#include "tensorflow/core/lib/hash/hash.h"

}

using deadness_analysis_internal::ComputePredicates;
using deadness_analysis_internal::PredicateMapTy;

Status AnalyzeDeadness(Graph* graph,
                       std::unique_ptr<DeadnessAnalysis>* result) {
  FixupSourceAndSinkEdges(graph);
  return DeadnessAnalysis::Run(*graph, result);
}

ops::Switch CreateSwitch(const Scope& root, const string& prefix) {

// API for driving Graph execution.

typedef struct TF_Session TF_Session;

// Return a new execution session with the associated graph, or NULL on
// error. Does not take ownership of any input parameters.
//
// *`graph` must be a valid graph (not deleted or nullptr). `graph` will be
// kept alive for the lifetime of the returned TF_Session. New nodes can still
// be added to `graph` after this call.

  }
  return %graph#0, %graph#1, %graph#2, %graph#3, %graph#4, %graph#5 : !tf_res, !tf_res, tensor<f32>, tensor<f32>, tensor<i32>, tensor<i32>
}
```
### `-tf-executor-graph-pruning`

_Prunes unreachable ops in a tf_executor.graph_

This pass removes ops from a `tf_executor.graph` that are not transitively, via

    )

  def _contains_quantized_function_call(
      self, graphdef: graph_pb2.GraphDef
  ) -> bool:
    """Determines if the graph def has quantized function call.

    Args:
      graphdef: A GraphDef object.

    Returns:
      True if and only if the graph def contains a quantized function call.
    """
    return any(map(self._is_quantized_function, graphdef.library.function))

#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/graph/algorithm.h"
#include "tensorflow/core/graph/control_flow.h"
#include "tensorflow/core/graph/graph_node_util.h"
#include "tensorflow/core/graph/tensor_id.h"
#include "tensorflow/core/lib/hash/hash.h"

// ALGORITHM OVERVIEW
// ==================
//
// We map every output produced by each node in the TensorFlow graph (including